NVIDIA Linux OpenCL CUDA RTX SUPER Compute

NVIDIA GeForce RTX SUPER Linux OpenCL/CUDA GPU compute benchmarks by Michael Larabel for a future article.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 1909299-AS-RTXSUPERC34
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Result
Identifier
Performance Per
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Date
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  Test
  Duration
GTX 970
September 28 2019
  1 Hour, 51 Minutes
GTX 980
September 28 2019
  1 Hour, 51 Minutes
GTX 980 Ti
September 26 2019
  1 Hour, 46 Minutes
GTX 1060
September 27 2019
  1 Hour, 47 Minutes
GTX 1070
September 28 2019
  1 Hour, 41 Minutes
GTX 1070 Ti
September 27 2019
  1 Hour, 47 Minutes
GTX 1080
September 28 2019
  1 Hour, 37 Minutes
GTX 1080 Ti
September 28 2019
  1 Hour, 27 Minutes
GTX 1660
September 28 2019
  1 Hour, 47 Minutes
GTX 1660 Ti
September 28 2019
  1 Hour, 44 Minutes
RTX 2060
September 27 2019
  1 Hour, 35 Minutes
RTX 2060 SUPER
September 26 2019
  1 Hour, 38 Minutes
RTX 2070
September 27 2019
  1 Hour, 37 Minutes
RTX 2070 SUPER
September 26 2019
  1 Hour, 40 Minutes
RTX 2080
September 27 2019
  1 Hour, 36 Minutes
RTX 2080 SUPER
September 27 2019
  1 Hour, 38 Minutes
RTX 2080 Ti
September 29 2019
  1 Hour, 27 Minutes
TITAN RTX
September 27 2019
  1 Hour, 28 Minutes
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  1 Hour, 40 Minutes

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GTX 970

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: eVGA NVIDIA GeForce GTX 970 4GB (1163/3505MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 1664
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

GTX 980

Changed Graphics to NVIDIA GeForce GTX 980 4GB (1126/3505MHz).

OpenCL Change: GPU Compute Cores: 2048

GTX 980 Ti

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce GTX 980 Ti 6GB (999/3505MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.3.0-999-generic (x86_64) 20190914, Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2816
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

GTX 1060

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce GTX 1060 6GB (1506/4006MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 1280
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

GTX 1070

Changed Graphics to NVIDIA GeForce GTX 1070 8GB (1506/4006MHz).

OpenCL Change: GPU Compute Cores: 1920

GTX 1070 Ti

Changed Graphics to Zotac NVIDIA GeForce GTX 1070 Ti 8GB (1607/4006MHz).

OpenCL Change: GPU Compute Cores: 2432

GTX 1080

Changed Graphics to NVIDIA GeForce GTX 1080 8GB (1607/5005MHz).

OpenCL Change: GPU Compute Cores: 2560

GTX 1080 Ti

Changed Graphics to NVIDIA GeForce GTX 1080 Ti 11GB (1480/5508MHz).

OpenCL Change: GPU Compute Cores: 3584

GTX 1660

Changed Graphics to ASUS NVIDIA GeForce GTX 1660 6GB (1530/4001MHz).

OpenCL Change: GPU Compute Cores: 1408

GTX 1660 Ti

Changed Graphics to eVGA NVIDIA GeForce GTX 1660 Ti 6GB (1500/6000MHz).

OpenCL Change: GPU Compute Cores: 1536

RTX 2060

Changed Graphics to NVIDIA GeForce RTX 2060 6GB (1365/7000MHz).

OpenCL Change: GPU Compute Cores: 1920

RTX 2060 SUPER

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce RTX 2060 SUPER 8GB (1470/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.3.0-999-generic (x86_64) 20190914, Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2176
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

RTX 2070

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: ASUS NVIDIA GeForce RTX 2070 8GB (1410/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2304
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

RTX 2070 SUPER

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce RTX 2070 SUPER 8GB (1605/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.3.0-999-generic (x86_64) 20190914, Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2560
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

RTX 2080

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: Zotac NVIDIA GeForce RTX 2080 8GB (795/810MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2944
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

RTX 2080 SUPER

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce RTX 2080 SUPER 8GB (1650/7750MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.3.0-999-generic (x86_64) 20190914, Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 3072
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

RTX 2080 Ti

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce RTX 2080 Ti 11GB (1350/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 4352
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

TITAN RTX

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA TITAN RTX 24GB (1350/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.3.0-999-generic (x86_64) 20190914, Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 4608
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

NVIDIA Linux OpenCL CUDA RTX SUPER ComputeOpenBenchmarking.orgPhoronix Test SuiteIntel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads)ASUS PRIME Z390-A (0802 BIOS)Intel Cannon Lake PCH16384MBSamsung SSD 970 EVO 250GBeVGA NVIDIA GeForce GTX 970 4GB (1163/3505MHz)NVIDIA GeForce GTX 980 4GB (1126/3505MHz)NVIDIA GeForce GTX 980 Ti 6GB (999/3505MHz)NVIDIA GeForce GTX 1060 6GB (1506/4006MHz)NVIDIA GeForce GTX 1070 8GB (1506/4006MHz)Zotac NVIDIA GeForce GTX 1070 Ti 8GB (1607/4006MHz)NVIDIA GeForce GTX 1080 8GB (1607/5005MHz)NVIDIA GeForce GTX 1080 Ti 11GB (1480/5508MHz)ASUS NVIDIA GeForce GTX 1660 6GB (1530/4001MHz)eVGA NVIDIA GeForce GTX 1660 Ti 6GB (1500/6000MHz)NVIDIA GeForce RTX 2060 6GB (1365/7000MHz)NVIDIA GeForce RTX 2060 SUPER 8GB (1470/7000MHz)ASUS NVIDIA GeForce RTX 2070 8GB (1410/7000MHz)NVIDIA GeForce RTX 2070 SUPER 8GB (1605/7000MHz)Zotac NVIDIA GeForce RTX 2080 8GB (795/810MHz)NVIDIA GeForce RTX 2080 SUPER 8GB (1650/7750MHz)NVIDIA GeForce RTX 2080 Ti 11GB (1350/7000MHz)NVIDIA TITAN RTX 24GB (1350/7000MHz)Realtek ALC1220Acer B286HKIntel I219-VUbuntu 19.045.0.0-29-generic (x86_64)5.3.0-999-generic (x86_64) 20190914GNOME Shell 3.32.2X Server 1.20.4NVIDIA 435.214.6.0GCC 8.3.0ext43840x2160ProcessorMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelsDesktopDisplay ServerDisplay DriverOpenGLCompilerFile-SystemScreen ResolutionNVIDIA Linux OpenCL CUDA RTX SUPER Compute BenchmarksSystem Logs- --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v - Scaling Governor: intel_pstate performance- GTX 970: GPU Compute Cores: 1664- GTX 980: GPU Compute Cores: 2048- GTX 980 Ti: GPU Compute Cores: 2816- GTX 1060: GPU Compute Cores: 1280- GTX 1070: GPU Compute Cores: 1920- GTX 1070 Ti: GPU Compute Cores: 2432- GTX 1080: GPU Compute Cores: 2560- GTX 1080 Ti: GPU Compute Cores: 3584- GTX 1660: GPU Compute Cores: 1408- GTX 1660 Ti: GPU Compute Cores: 1536- RTX 2060: GPU Compute Cores: 1920- RTX 2060 SUPER: GPU Compute Cores: 2176- RTX 2070: GPU Compute Cores: 2304- RTX 2070 SUPER: GPU Compute Cores: 2560- RTX 2080: GPU Compute Cores: 2944- RTX 2080 SUPER: GPU Compute Cores: 3072- RTX 2080 Ti: GPU Compute Cores: 4352- TITAN RTX: GPU Compute Cores: 4608- GTX 970, GTX 980, GTX 980 Ti, GTX 1060, GTX 1070, GTX 1070 Ti, GTX 1080, GTX 1080 Ti, GTX 1660, GTX 1660 Ti, RTX 2060, RTX 2070, RTX 2070 SUPER, RTX 2080, RTX 2080 SUPER, RTX 2080 Ti, TITAN RTX: Python 2.7.16 + Python 3.7.3 - l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

GTX 970GTX 980GTX 980 TiGTX 1060GTX 1070GTX 1070 TiGTX 1080GTX 1080 TiGTX 1660GTX 1660 TiRTX 2060RTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTXLogarithmic Result OverviewPhoronix Test SuiteclpeakSHOC Scalable HeterOgeneous ComputingLuxMarkPlaidMLOctaneBenchcl-memFAHBenchDarktableRodiniaLeelaChessZeroNAMD CUDAJuliaGPUViennaCL

GTX 970GTX 980GTX 980 TiGTX 1060GTX 1070GTX 1070 TiGTX 1080GTX 1080 TiGTX 1660GTX 1660 TiRTX 2060RTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTXLogarithmic Per Watt Result OverviewPhoronix Test SuiteclpeakPlaidMLcl-memSHOC Scalable HeterOgeneous ComputingJuliaGPUViennaCLFAHBenchLuxMarkLeelaChessZeroOctaneBenchP.W.G.MP.W.G.MP.W.G.MP.W.G.MP.W.G.MP.W.G.MP.W.G.MP.W.G.MP.W.G.MP.W.G.M

NVIDIA Linux OpenCL CUDA RTX SUPER Computeshoc: OpenCL - Max SP Flopsoctanebench: Total Scoreluxmark: GPU - Microphoneluxmark: GPU - Luxball HDRluxmark: GPU - Hotelfahbench: plaidml: Yes - Inference - NASNer Large - OpenCLplaidml: Yes - Inference - VGG19 - OpenCLplaidml: Yes - Inference - DenseNet 201 - OpenCLrodinia: OpenCL Myocyteplaidml: Yes - Inference - VGG16 - OpenCLclpeak: Double-Precision Doubleplaidml: No - Inference - VGG19 - OpenCLplaidml: Yes - Inference - Inception V3 - OpenCLlczero: OpenCLplaidml: No - Inference - VGG16 - OpenCLplaidml: No - Inference - Inception V3 - OpenCLplaidml: Yes - Inference - ResNet 50 - OpenCLnamd-cuda: ATPase Simulation - 327,506 Atomsplaidml: No - Inference - ResNet 50 - OpenCLplaidml: No - Inference - IMDB LSTM - OpenCLrodinia: OpenCL Particle Filtercl-mem: Readjuliagpu: GPUplaidml: Yes - Inference - Mobilenet - OpenCLcl-mem: Copycl-mem: Writeplaidml: No - Inference - Mobilenet - OpenCLdarktable: Masskrug - OpenCLclpeak: Integer Compute INTdarktable: Boat - OpenCLclpeak: Single-Precision Floatdarktable: Server Room - OpenCLviennacl: OpenCL LU Factorizationshoc: OpenCL - FFT SPclpeak: Global Memory Bandwidthshoc: OpenCL - MD5 HashGTX 970GTX 980GTX 980 TiGTX 1060GTX 1070GTX 1070 TiGTX 1080GTX 1080 TiGTX 1660GTX 1660 TiRTX 2060RTX 2060 SUPERRTX 2070RTX 2070 SUPERRTX 2080RTX 2080 SUPERRTX 2080 TiTITAN RTX4362.3195.60798511732273091.5321.4239.3479.7145.4849.76137.4747.7088.16207.8460.3294.72116.050.36368181.87204.3212.99142.10169258044.90841.48124.77132.60671.495.781140.294.423888.163.1656.95411.29143.486.505052.73109.708914132463048102.8624.2443.6392.9247.3855.70159.6853.49101.92280.9968.95105.64142.140.33110203.91231.6611.69164.50181882709.77973.39143.40151.50759.435.741312.063.924476.693.1059.21458.35164.257.496213.97142.2011096168713885116.0230.6456.13111.4652.1371.26196.6068.47116.31466.8487.39135.14162.630.28675247.47270.009.95265.33195653728.471202.77216.83241.50990.124.121610.283.275538.751.5162.01725.98263.229.224788.9291.447086122452648102.6123.1644.3791.0734.6956.07149.5854.7897.83262.4169.31104.44130.640.31789196.00224.8911.93153.50182188318.67908.43137.20144.57726.304.071267.893.654199.711.2858.67326.68146.627.267115.39132.869983172903870140.2933.0763.56127.0235.1080.27223.9176.89141.55642.1297.32147.17196.010.23957276.89315.378.26205.27216942144.931288.94182.00190.90987.693.921685.052.896269.491.1163.86478.54196.4710.617715.42141.3510259169254170138.2135.4173.12130.1538.7092.03242.6390.34147.04753.69114.03153.34205.850.22269294.36333.037.88205.27220447755.871371.21182.70190.031009.263.972076.932.936770.971.1764.68525.89197.2611.709407.75147.988716137883807155.2240.3883.83143.5334.87106.09297.94101.00173.791146.75128.05184.80240.620.20978337.47399.006.49228.80237914974.401544.50205.93214.671123.853.942430.742.728314.291.0966.67614.69222.0914.2513230.77212.0413721216895649198.2556.64115.03191.3135.91145.42414.96138.68228.681886.30175.37257.55333.540.19669496.24523.984.96337.53262248899.332162.58283.20340.271672.733.923301.892.2911720.571.0569.09982.23328.9019.725329.84118.499794151623733126.6428.9952.52102.8330.9766.24168.4467.24137.66335.8684.83116.90156.500.25031228.14287.6811.87162.90230919642.131160.52145.37148.87814.654.014657.793.354610.011.1865.10452.89157.6011.875893.41132.2811003161473805139.8134.1258.03114.5830.6773.18185.1273.35161.33420.0492.45140.05172.680.23185259.43315.8310.82250.23239300837.601394.05208.50208.671002.004.024775.452.924793.661.1566.06665.66234.6712.987320.73164.5213754216834833183.4141.1171.07154.1931.1189.55231.4488.04193.75704.69110.93167.87220.440.20250319.25389.408.90296.20251925176.901694.07237.77241.201232.473.735269.012.225329.070.8367.92818.44275.8616.048378.87205.2318509300936148205.2048.9680.82179.5130.42102.58263.11101.17219.76998.17128.22199.43250.980.19336374.71440.797.87395.67264172441.471983.82287.80333.201531.013.687023.071.957089.500.7569.17971.24367.9218.228528.70206.8818441300976150204.7149.9483.56176.4931.64105.60268.32103.89220.99999.75131.54198.03251.070.19440376.73446.237.75395.70267086274.531969.50284.43322.671516.963.677161.481.937198.640.7569.41976.78368.9618.779869.34220.7620499297346565229.1255.2497.82190.0130.76123.20310.27122.32239.611604.21154.64215.85283.980.19501421.58499.696.82395.67275868151.172264.97291.87319.571649.173.718570.601.938502.710.8070.451088.17369.1121.7810952.77222.8819916291646590242.7558.47105.54189.2831.65133.20345.81129.58268.331879.99164.05238.73305.760.19307441.24548.836.22395.70280162469.672292.38289.20331.501663.873.719660.921.908883.900.8070.961100.00368.4724.0712015.50233.5620164301796839256.8364.80115.44200.3830.63145.65378.98143.02301.112105.26180.45259.26327.800.19385468.70589.865.74436.27286818331.272437.48301.23345.771762.003.6910404.711.8210335.500.7971.471203.57405.0026.5616656.20309.0428631429749215301.8984.97154.20254.4531.05194.83521.90186.19363.163032.10234.65343.49424.070.18909634.09758.214.39544.33299834728.802750.57324.40441.232335.463.6613609.331.6413532.740.7572.711485.73506.3334.9117334.00322.7630756465469836301.9387.17162.05263.1331.69204.67547.97196.44373.713126.48247.83347.93433.810.18867648.36790.774.24566.70303198573.972842.38322.20495.372466.663.6613841.251.6414203.870.7472.961578.29528.8936.39OpenBenchmarking.org

SHOC Scalable HeterOgeneous Computing

The CUDA and OpenCL version of Vetter's Scalable HeterOgeneous Computing benchmark suite. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: Max SP FlopsTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10604K8K12K16K20KSE +/- 91.95, N = 3SE +/- 87.95, N = 3SE +/- 61.30, N = 3SE +/- 29.32, N = 3SE +/- 51.02, N = 3SE +/- 45.97, N = 3SE +/- 27.40, N = 3SE +/- 19.13, N = 3SE +/- 11.70, N = 3SE +/- 3.92, N = 3SE +/- 0.74, N = 3SE +/- 0.04, N = 3SE +/- 13.79, N = 3SE +/- 3.93, N = 3SE +/- 3.00, N = 3SE +/- 0.84, N = 3SE +/- 1.89, N = 3SE +/- 6.34, N = 317334.0016656.2012015.5010952.779869.348528.708378.877320.736213.975052.734362.315893.415329.8413230.779407.757715.427115.394788.921. (CXX) g++ options: -O2 -lSHOCCommonMPI -lSHOCCommonOpenCL -lSHOCCommon -lOpenCL -lrt -pthread -lmpi_cxx -lmpi

OctaneBench

OctaneBench is a test of the OctaneRender on the GPU and requires the use of NVIDIA CUDA. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterOctaneBench 4.00cTotal ScoreTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106070140210280350322.76309.04233.56222.88220.76206.88205.23164.52142.20109.7095.60132.28118.49212.04147.98141.35132.8691.44

LuxMark

LuxMark is a multi-platform OpenGL benchmark using LuxRender. LuxMark supports targeting different OpenCL devices and has multiple scenes available for rendering. LuxMark is a fully open-source OpenCL program with real-world rendering examples. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: MicrophoneTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10607K14K21K28K35KSE +/- 168.12, N = 3SE +/- 21.50, N = 3SE +/- 108.17, N = 3SE +/- 11.68, N = 3SE +/- 16.84, N = 3SE +/- 26.44, N = 3SE +/- 43.34, N = 3SE +/- 3.84, N = 3SE +/- 49.74, N = 3SE +/- 18.25, N = 3SE +/- 2.00, N = 3SE +/- 2.33, N = 3SE +/- 1.33, N = 3SE +/- 19.33, N = 3SE +/- 1.20, N = 3SE +/- 15.50, N = 3SE +/- 4.91, N = 3SE +/- 1.53, N = 3307562863120164199162049918441185091375411096891479851100397941372187161025999837086

OpenBenchmarking.orgScore, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: Luxball HDRTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106010K20K30K40K50KSE +/- 20.92, N = 3SE +/- 166.33, N = 3SE +/- 0.88, N = 3SE +/- 7.51, N = 3SE +/- 98.93, N = 3SE +/- 7.54, N = 3SE +/- 4.93, N = 3SE +/- 0.67, N = 3SE +/- 39.15, N = 3SE +/- 26.16, N = 3SE +/- 6.23, N = 3SE +/- 19.86, N = 3SE +/- 35.04, N = 3SE +/- 7.67, N = 3SE +/- 17.98, N = 3SE +/- 36.50, N = 3SE +/- 1.00, N = 3SE +/- 4.00, N = 3465464297430179291642973430097300932168316871132461173216147151622168913788169251729012245

OpenBenchmarking.orgScore, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: HotelTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10602K4K6K8K10KSE +/- 1.73, N = 3SE +/- 4.37, N = 3SE +/- 0.58, N = 3SE +/- 0.88, N = 3SE +/- 1.86, N = 3SE +/- 0.67, N = 3SE +/- 0.67, N = 3SE +/- 8.00, N = 3SE +/- 2.73, N = 3SE +/- 1.86, N = 3SE +/- 0.58, N = 3SE +/- 7.09, N = 3SE +/- 0.67, N = 3SE +/- 3.51, N = 3SE +/- 1.20, N = 3SE +/- 3.76, N = 3983692156839659065656150614848333885304827303805373356493807417038702648

FAHBench

FAHBench is a Folding@Home benchmark on the GPU. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNs Per Day, More Is BetterFAHBench 2.3.2TITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106070140210280350SE +/- 0.71, N = 3SE +/- 0.90, N = 3SE +/- 0.78, N = 3SE +/- 0.99, N = 3SE +/- 0.60, N = 3SE +/- 0.64, N = 3SE +/- 0.34, N = 3SE +/- 0.61, N = 3SE +/- 0.04, N = 3SE +/- 0.08, N = 3SE +/- 0.03, N = 3SE +/- 0.15, N = 3SE +/- 0.27, N = 3SE +/- 0.43, N = 3SE +/- 0.53, N = 3SE +/- 0.05, N = 3SE +/- 0.43, N = 3SE +/- 0.17, N = 3301.93301.89256.83242.75229.12204.71205.20183.41116.02102.8691.53139.81126.64198.25155.22138.21140.29102.61

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: NASNer Large - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106020406080100SE +/- 0.25, N = 3SE +/- 0.21, N = 3SE +/- 0.08, N = 3SE +/- 0.15, N = 3SE +/- 0.05, N = 3SE +/- 0.13, N = 3SE +/- 0.14, N = 3SE +/- 0.08, N = 3SE +/- 0.10, N = 3SE +/- 0.15, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.11, N = 3SE +/- 0.08, N = 3SE +/- 0.02, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 387.1784.9764.8058.4755.2449.9448.9641.1130.6424.2421.4234.1228.9956.6440.3835.4133.0723.16

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG19 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10604080120160200SE +/- 0.48, N = 3SE +/- 0.36, N = 3SE +/- 0.21, N = 3SE +/- 0.44, N = 3SE +/- 0.16, N = 3SE +/- 0.35, N = 3SE +/- 0.23, N = 3SE +/- 0.19, N = 3SE +/- 0.77, N = 3SE +/- 0.62, N = 4SE +/- 0.18, N = 3SE +/- 0.12, N = 3SE +/- 0.08, N = 3SE +/- 0.44, N = 3SE +/- 0.28, N = 3SE +/- 0.03, N = 3SE +/- 0.19, N = 3SE +/- 0.12, N = 3162.05154.20115.44105.5497.8283.5680.8271.0756.1343.6339.3458.0352.52115.0383.8373.1263.5644.37

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: DenseNet 201 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060120180240300SE +/- 0.18, N = 3SE +/- 0.10, N = 3SE +/- 0.07, N = 3SE +/- 0.17, N = 3SE +/- 0.14, N = 3SE +/- 0.22, N = 3SE +/- 0.03, N = 3SE +/- 0.05, N = 3SE +/- 0.18, N = 3SE +/- 0.12, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.10, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.05, N = 3SE +/- 0.15, N = 3263.13254.45200.38189.28190.01176.49179.51154.19111.4692.9279.71114.58102.83191.31143.53130.15127.0291.07

Rodinia

Rodinia is a suite focused upon accelerating compute-intensive applications with accelerators. CUDA, OpenMP, and OpenCL parallel models are supported by the included applications. This profile utilizes the OpenCL and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 2.4Test: OpenCL MyocyteTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10601224364860SE +/- 0.04, N = 3SE +/- 0.07, N = 3SE +/- 0.04, N = 3SE +/- 0.04, N = 3SE +/- 0.15, N = 3SE +/- 0.03, N = 3SE +/- 0.04, N = 3SE +/- 0.05, N = 3SE +/- 0.18, N = 3SE +/- 0.05, N = 3SE +/- 0.06, N = 3SE +/- 0.05, N = 3SE +/- 0.08, N = 3SE +/- 0.03, N = 3SE +/- 0.04, N = 3SE +/- 0.14, N = 3SE +/- 0.08, N = 3SE +/- 0.10, N = 331.6931.0530.6331.6530.7631.6430.4231.1152.1347.3845.4830.6730.9735.9134.8738.7035.1034.691. (CXX) g++ options: -O2 -lOpenCL

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG16 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10604080120160200SE +/- 0.57, N = 3SE +/- 0.51, N = 3SE +/- 0.29, N = 3SE +/- 0.57, N = 3SE +/- 0.28, N = 3SE +/- 0.39, N = 3SE +/- 0.35, N = 3SE +/- 0.23, N = 3SE +/- 1.12, N = 3SE +/- 0.83, N = 4SE +/- 0.21, N = 3SE +/- 0.14, N = 3SE +/- 0.17, N = 3SE +/- 0.62, N = 3SE +/- 0.40, N = 3SE +/- 0.08, N = 3SE +/- 0.30, N = 3SE +/- 0.18, N = 3204.67194.83145.65133.20123.20105.60102.5889.5571.2655.7049.7673.1866.24145.42106.0992.0380.2756.07

clpeak

Clpeak is designed to test the peak capabilities of OpenCL devices. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterclpeakOpenCL Test: Double-Precision DoubleTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 1060120240360480600SE +/- 1.16, N = 3SE +/- 1.46, N = 3SE +/- 0.03, N = 3SE +/- 0.92, N = 3SE +/- 0.77, N = 3SE +/- 0.81, N = 3SE +/- 0.71, N = 3SE +/- 0.01, N = 3SE +/- 0.35, N = 3SE +/- 0.07, N = 3SE +/- 0.03, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 1.14, N = 3SE +/- 0.76, N = 3SE +/- 0.02, N = 3SE +/- 0.71, N = 3SE +/- 0.14, N = 3547.97521.90378.98345.81310.27268.32263.11231.44196.60159.68137.47185.12168.44414.96297.94242.63223.91149.581. (CXX) g++ options: -O3 -rdynamic -lOpenCL

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG19 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10604080120160200SE +/- 0.54, N = 3SE +/- 0.41, N = 3SE +/- 0.22, N = 3SE +/- 0.42, N = 3SE +/- 0.23, N = 3SE +/- 0.25, N = 3SE +/- 0.19, N = 3SE +/- 0.17, N = 3SE +/- 0.65, N = 3SE +/- 0.47, N = 3SE +/- 0.01, N = 3SE +/- 0.12, N = 3SE +/- 0.17, N = 3SE +/- 0.35, N = 3SE +/- 0.16, N = 3SE +/- 0.06, N = 3SE +/- 0.11, N = 3SE +/- 0.08, N = 3196.44186.19143.02129.58122.32103.89101.1788.0468.4753.4947.7073.3567.24138.68101.0090.3476.8954.78

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: Inception V3 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106080160240320400SE +/- 0.48, N = 3SE +/- 0.44, N = 3SE +/- 0.23, N = 3SE +/- 0.59, N = 3SE +/- 0.10, N = 3SE +/- 0.43, N = 3SE +/- 0.44, N = 3SE +/- 0.37, N = 3SE +/- 0.26, N = 3SE +/- 0.27, N = 3SE +/- 0.01, N = 3SE +/- 0.05, N = 3SE +/- 0.27, N = 3SE +/- 0.21, N = 3SE +/- 0.30, N = 3SE +/- 0.06, N = 3SE +/- 0.18, N = 3SE +/- 0.20, N = 3373.71363.16301.11268.33239.61220.99219.76193.75116.31101.9288.16161.33137.66228.68173.79147.04141.5597.83

LeelaChessZero

LeelaChessZero (lc0 / lczero) is a chess engine automated vian neural networks. This test profile can be used for OpenCL, CUDA + cuDNN, and BLAS (CPU-based) benchmarking. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgNodes Per Second, More Is BetterLeelaChessZero 0.22.0Backend: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10607001400210028003500SE +/- 28.21, N = 3SE +/- 8.77, N = 3SE +/- 29.82, N = 3SE +/- 21.60, N = 3SE +/- 17.64, N = 7SE +/- 16.93, N = 15SE +/- 18.12, N = 15SE +/- 1.84, N = 3SE +/- 5.67, N = 15SE +/- 2.79, N = 3SE +/- 1.93, N = 15SE +/- 5.83, N = 15SE +/- 4.05, N = 15SE +/- 32.29, N = 3SE +/- 14.70, N = 3SE +/- 8.69, N = 6SE +/- 12.32, N = 15SE +/- 3.68, N = 43126.483032.102105.261879.991604.21999.75998.17704.69466.84280.99207.84420.04335.861886.301146.75753.69642.12262.411. (CXX) g++ options: -lpthread

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG16 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106050100150200250SE +/- 0.40, N = 3SE +/- 0.50, N = 3SE +/- 0.28, N = 3SE +/- 0.73, N = 3SE +/- 0.29, N = 3SE +/- 0.43, N = 3SE +/- 0.34, N = 3SE +/- 0.32, N = 3SE +/- 1.36, N = 3SE +/- 0.79, N = 3SE +/- 0.05, N = 3SE +/- 0.24, N = 3SE +/- 0.21, N = 3SE +/- 0.62, N = 3SE +/- 0.38, N = 3SE +/- 0.06, N = 3SE +/- 0.17, N = 3SE +/- 0.12, N = 3247.83234.65180.45164.05154.64131.54128.22110.9387.3968.9560.3292.4584.83175.37128.05114.0397.3269.31

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Inception V3 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106080160240320400SE +/- 0.42, N = 3SE +/- 0.38, N = 3SE +/- 0.10, N = 3SE +/- 0.57, N = 3SE +/- 0.07, N = 3SE +/- 0.29, N = 3SE +/- 0.25, N = 3SE +/- 0.23, N = 3SE +/- 0.07, N = 3SE +/- 0.17, N = 3SE +/- 0.16, N = 3SE +/- 0.23, N = 3SE +/- 0.12, N = 3SE +/- 0.14, N = 3SE +/- 0.38, N = 3SE +/- 0.06, N = 3SE +/- 0.09, N = 3SE +/- 0.10, N = 3347.93343.49259.26238.73215.85198.03199.43167.87135.14105.6494.72140.05116.90257.55184.80153.34147.17104.44

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: ResNet 50 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106090180270360450SE +/- 0.70, N = 3SE +/- 1.04, N = 3SE +/- 0.12, N = 3SE +/- 0.60, N = 3SE +/- 0.71, N = 3SE +/- 0.53, N = 3SE +/- 0.48, N = 3SE +/- 0.16, N = 3SE +/- 0.06, N = 3SE +/- 0.26, N = 3SE +/- 0.00, N = 3SE +/- 0.06, N = 3SE +/- 0.31, N = 3SE +/- 0.42, N = 3SE +/- 0.11, N = 3SE +/- 0.08, N = 3SE +/- 0.28, N = 3SE +/- 0.16, N = 3433.81424.07327.80305.76283.98251.07250.98220.44162.63142.14116.05172.68156.50333.54240.62205.85196.01130.64

NAMD CUDA

NAMD is a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD was developed by the Theoretical and Computational Biophysics Group in the Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign. This version of the NAMD test profile uses CUDA GPU acceleration. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgdays/ns, Fewer Is BetterNAMD CUDA 2.13ATPase Simulation - 327,506 AtomsTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.08180.16360.24540.32720.409SE +/- 0.00297, N = 3SE +/- 0.00238, N = 3SE +/- 0.00233, N = 3SE +/- 0.00199, N = 3SE +/- 0.00245, N = 3SE +/- 0.00250, N = 3SE +/- 0.00245, N = 3SE +/- 0.00147, N = 4SE +/- 0.00105, N = 3SE +/- 0.00159, N = 3SE +/- 0.00026, N = 4SE +/- 0.00192, N = 3SE +/- 0.00287, N = 3SE +/- 0.00044, N = 3SE +/- 0.00088, N = 5SE +/- 0.00075, N = 6SE +/- 0.00195, N = 3SE +/- 0.00303, N = 30.188670.189090.193850.193070.195010.194400.193360.202500.286750.331100.363680.231850.250310.196690.209780.222690.239570.31789

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: ResNet 50 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 1060140280420560700SE +/- 0.75, N = 3SE +/- 0.63, N = 3SE +/- 0.61, N = 3SE +/- 0.25, N = 3SE +/- 0.19, N = 3SE +/- 0.27, N = 3SE +/- 0.53, N = 3SE +/- 0.39, N = 3SE +/- 0.58, N = 3SE +/- 0.02, N = 3SE +/- 0.06, N = 3SE +/- 0.47, N = 3SE +/- 0.16, N = 3SE +/- 0.72, N = 3SE +/- 0.32, N = 3SE +/- 0.09, N = 3SE +/- 0.15, N = 3SE +/- 0.07, N = 3648.36634.09468.70441.24421.58376.73374.71319.25247.47203.91181.87259.43228.14496.24337.47294.36276.89196.00

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10602004006008001000SE +/- 2.25, N = 3SE +/- 1.01, N = 3SE +/- 1.47, N = 3SE +/- 1.63, N = 3SE +/- 0.67, N = 3SE +/- 0.21, N = 3SE +/- 0.31, N = 3SE +/- 0.37, N = 3SE +/- 0.56, N = 3SE +/- 0.50, N = 3SE +/- 0.03, N = 3SE +/- 0.15, N = 3SE +/- 0.01, N = 3SE +/- 0.74, N = 3SE +/- 0.31, N = 3SE +/- 0.49, N = 3SE +/- 0.13, N = 3SE +/- 0.17, N = 3790.77758.21589.86548.83499.69446.23440.79389.40270.00231.66204.32315.83287.68523.98399.00333.03315.37224.89

Rodinia

Rodinia is a suite focused upon accelerating compute-intensive applications with accelerators. CUDA, OpenMP, and OpenCL parallel models are supported by the included applications. This profile utilizes the OpenCL and OpenMP test binaries at the moment. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterRodinia 2.4Test: OpenCL Particle FilterTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10603691215SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.04, N = 3SE +/- 0.07, N = 3SE +/- 0.02, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.07, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 34.244.395.746.226.827.757.878.909.9511.6912.9910.8211.874.966.497.888.2611.931. (CXX) g++ options: -O2 -lOpenCL

cl-mem

A basic OpenCL memory benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: ReadTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 1060120240360480600SE +/- 0.40, N = 3SE +/- 0.38, N = 3SE +/- 0.27, N = 3SE +/- 0.25, N = 3SE +/- 0.22, N = 3SE +/- 0.25, N = 3SE +/- 0.22, N = 3SE +/- 0.20, N = 3SE +/- 0.12, N = 3SE +/- 0.10, N = 3SE +/- 1.50, N = 8SE +/- 0.07, N = 3SE +/- 0.00, N = 3SE +/- 0.20, N = 3SE +/- 0.12, N = 3SE +/- 0.07, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3566.70544.33436.27395.70395.67395.70395.67296.20265.33164.50142.10250.23162.90337.53228.80205.27205.27153.501. (CC) gcc options: -O2 -flto -lOpenCL

JuliaGPU

JuliaGPU is an OpenCL benchmark with this version containing various PTS-specific enhancements. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSamples/sec, More Is BetterJuliaGPU 1.2pts1OpenCL Device: GPUTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060M120M180M240M300MSE +/- 489061.14, N = 3SE +/- 78810.54, N = 3SE +/- 1165562.77, N = 3SE +/- 169596.23, N = 3SE +/- 389272.10, N = 3SE +/- 633693.84, N = 3SE +/- 369711.60, N = 3SE +/- 121354.48, N = 3SE +/- 78142.08, N = 3SE +/- 52667.10, N = 3SE +/- 383961.59, N = 3SE +/- 495295.96, N = 3SE +/- 197521.26, N = 3SE +/- 540298.84, N = 3SE +/- 341457.11, N = 3SE +/- 97519.45, N = 3SE +/- 76295.47, N = 3SE +/- 137674.47, N = 3303198573.97299834728.80286818331.27280162469.67275868151.17267086274.53264172441.47251925176.90195653728.47181882709.77169258044.90239300837.60230919642.13262248899.33237914974.40220447755.87216942144.93182188318.671. (CC) gcc options: -O3 -march=native -ftree-vectorize -funroll-loops -lglut -lOpenCL -lGL -lm

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10606001200180024003000SE +/- 4.02, N = 3SE +/- 13.82, N = 3SE +/- 6.75, N = 3SE +/- 4.68, N = 3SE +/- 4.73, N = 3SE +/- 5.21, N = 3SE +/- 10.89, N = 3SE +/- 3.62, N = 3SE +/- 1.24, N = 3SE +/- 2.37, N = 3SE +/- 1.43, N = 3SE +/- 2.77, N = 3SE +/- 1.34, N = 3SE +/- 7.35, N = 3SE +/- 4.27, N = 3SE +/- 0.80, N = 3SE +/- 4.57, N = 3SE +/- 2.37, N = 32842.382750.572437.482292.382264.971969.501983.821694.071202.77973.39841.481394.051160.522162.581544.501371.211288.94908.43

cl-mem

A basic OpenCL memory benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: CopyTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106070140210280350SE +/- 0.67, N = 3SE +/- 0.40, N = 3SE +/- 0.13, N = 3SE +/- 0.15, N = 3SE +/- 0.17, N = 3SE +/- 0.24, N = 3SE +/- 0.31, N = 3SE +/- 0.12, N = 3SE +/- 0.17, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3SE +/- 0.15, N = 3SE +/- 0.03, N = 3SE +/- 0.25, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.06, N = 3SE +/- 0.06, N = 3322.20324.40301.23289.20291.87284.43287.80237.77216.83143.40124.77208.50145.37283.20205.93182.70182.00137.201. (CC) gcc options: -O2 -flto -lOpenCL

OpenBenchmarking.orgGB/s, More Is Bettercl-mem 2017-01-13Benchmark: WriteTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 1060110220330440550SE +/- 1.39, N = 3SE +/- 0.35, N = 3SE +/- 0.54, N = 3SE +/- 0.15, N = 3SE +/- 0.43, N = 3SE +/- 1.00, N = 3SE +/- 0.82, N = 3SE +/- 0.40, N = 3SE +/- 0.06, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.12, N = 3SE +/- 0.03, N = 3SE +/- 0.28, N = 3SE +/- 0.03, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.03, N = 3495.37441.23345.77331.50319.57322.67333.20241.20241.50151.50132.60208.67148.87340.27214.67190.03190.90144.571. (CC) gcc options: -O2 -flto -lOpenCL

PlaidML

This test profile uses PlaidML deep learning framework developed by Intel for offering up various benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgFPS, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10605001000150020002500SE +/- 13.68, N = 3SE +/- 6.28, N = 3SE +/- 2.80, N = 3SE +/- 4.17, N = 3SE +/- 1.25, N = 3SE +/- 1.46, N = 3SE +/- 1.59, N = 3SE +/- 2.11, N = 3SE +/- 0.07, N = 3SE +/- 0.24, N = 3SE +/- 0.75, N = 3SE +/- 0.86, N = 3SE +/- 1.38, N = 3SE +/- 5.20, N = 3SE +/- 1.27, N = 3SE +/- 0.73, N = 3SE +/- 1.57, N = 3SE +/- 0.63, N = 32466.662335.461762.001663.871649.171516.961531.011232.47990.12759.43671.491002.00814.651672.731123.851009.26987.69726.30

Darktable

Darktable is an open-source photography / workflow application this will use any system-installed Darktable program or on Windows will automatically download the pre-built binary from the project. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterDarktable 2.6.0Test: Masskrug - Acceleration: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10601.30052.6013.90155.2026.5025SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.02, N = 33.663.663.693.713.713.673.683.734.125.745.784.024.013.923.943.973.924.07

clpeak

Clpeak is designed to test the peak capabilities of OpenCL devices. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGIOPS, More Is BetterclpeakOpenCL Test: Integer Compute INTTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10603K6K9K12K15KSE +/- 156.59, N = 15SE +/- 57.62, N = 3SE +/- 83.79, N = 15SE +/- 4.11, N = 3SE +/- 81.60, N = 15SE +/- 84.78, N = 15SE +/- 76.65, N = 15SE +/- 63.11, N = 3SE +/- 23.09, N = 3SE +/- 0.38, N = 3SE +/- 19.67, N = 3SE +/- 64.34, N = 15SE +/- 32.97, N = 3SE +/- 29.87, N = 15SE +/- 26.46, N = 3SE +/- 0.72, N = 3SE +/- 24.36, N = 3SE +/- 13.36, N = 1513841.2513609.3310404.719660.928570.607161.487023.075269.011610.281312.061140.294775.454657.793301.892430.742076.931685.051267.891. (CXX) g++ options: -O3 -rdynamic -lOpenCL

Darktable

Darktable is an open-source photography / workflow application this will use any system-installed Darktable program or on Windows will automatically download the pre-built binary from the project. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterDarktable 2.6.0Test: Boat - Acceleration: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.99451.9892.98353.9784.9725SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 31.641.641.821.901.931.931.952.223.273.924.422.923.352.292.722.932.893.65

clpeak

Clpeak is designed to test the peak capabilities of OpenCL devices. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterclpeakOpenCL Test: Single-Precision FloatTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10603K6K9K12K15KSE +/- 228.75, N = 15SE +/- 207.30, N = 3SE +/- 124.22, N = 3SE +/- 7.41, N = 3SE +/- 76.18, N = 15SE +/- 81.15, N = 15SE +/- 84.87, N = 15SE +/- 77.72, N = 3SE +/- 44.36, N = 15SE +/- 46.38, N = 8SE +/- 40.24, N = 15SE +/- 61.47, N = 15SE +/- 7.83, N = 3SE +/- 5.50, N = 3SE +/- 3.14, N = 3SE +/- 7.63, N = 3SE +/- 3.03, N = 3SE +/- 1.88, N = 314203.8713532.7410335.508883.908502.717198.647089.505329.075538.754476.693888.164793.664610.0111720.578314.296770.976269.494199.711. (CXX) g++ options: -O3 -rdynamic -lOpenCL

Darktable

Darktable is an open-source photography / workflow application this will use any system-installed Darktable program or on Windows will automatically download the pre-built binary from the project. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterDarktable 2.6.0Test: Server Room - Acceleration: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.7111.4222.1332.8443.555SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 8SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 4SE +/- 0.01, N = 3SE +/- 0.00, N = 3SE +/- 0.01, N = 3SE +/- 0.01, N = 30.740.750.790.800.800.750.750.831.513.103.161.151.181.051.091.171.111.28

ViennaCL

ViennaCL is an open-source linear algebra library written in C++ and with support for OpenCL and OpenMP. This test profile uses ViennaCL OpenCL support and runs the included computational benchmark. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterViennaCL 1.4.2OpenCL LU FactorizationTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10601632486480SE +/- 0.60, N = 3SE +/- 0.72, N = 3SE +/- 0.26, N = 3SE +/- 0.07, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 3SE +/- 0.06, N = 3SE +/- 0.21, N = 3SE +/- 0.02, N = 3SE +/- 0.04, N = 3SE +/- 0.11, N = 3SE +/- 0.05, N = 3SE +/- 0.02, N = 3SE +/- 0.31, N = 3SE +/- 0.20, N = 3SE +/- 0.01, N = 3SE +/- 0.03, N = 3SE +/- 0.05, N = 372.9672.7171.4770.9670.4569.4169.1767.9262.0159.2156.9566.0665.1069.0966.6764.6863.8658.671. (CXX) g++ options: -rdynamic -lOpenCL

SHOC Scalable HeterOgeneous Computing

The CUDA and OpenCL version of Vetter's Scalable HeterOgeneous Computing benchmark suite. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGFLOPS, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: FFT SPTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106030060090012001500SE +/- 1.38, N = 3SE +/- 2.79, N = 3SE +/- 0.78, N = 3SE +/- 0.39, N = 3SE +/- 0.27, N = 3SE +/- 2.90, N = 3SE +/- 3.09, N = 3SE +/- 0.56, N = 3SE +/- 3.01, N = 3SE +/- 1.09, N = 3SE +/- 0.48, N = 3SE +/- 1.57, N = 3SE +/- 0.27, N = 3SE +/- 1.06, N = 3SE +/- 3.58, N = 3SE +/- 0.19, N = 3SE +/- 6.42, N = 4SE +/- 3.50, N = 71578.291485.731203.571100.001088.17976.78971.24818.44725.98458.35411.29665.66452.89982.23614.69525.89478.54326.681. (CXX) g++ options: -O2 -lSHOCCommonMPI -lSHOCCommonOpenCL -lSHOCCommon -lOpenCL -lrt -pthread -lmpi_cxx -lmpi

clpeak

Clpeak is designed to test the peak capabilities of OpenCL devices. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGBPS, More Is BetterclpeakOpenCL Test: Global Memory BandwidthTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 1060110220330440550SE +/- 0.66, N = 3SE +/- 0.44, N = 3SE +/- 0.08, N = 3SE +/- 0.22, N = 3SE +/- 0.33, N = 3SE +/- 0.07, N = 3SE +/- 0.11, N = 3SE +/- 0.24, N = 3SE +/- 0.52, N = 3SE +/- 0.03, N = 3SE +/- 0.06, N = 3SE +/- 0.17, N = 3SE +/- 0.00, N = 3SE +/- 0.71, N = 3SE +/- 0.09, N = 3SE +/- 0.00, N = 3SE +/- 0.18, N = 3SE +/- 0.06, N = 3528.89506.33405.00368.47369.11368.96367.92275.86263.22164.25143.48234.67157.60328.90222.09197.26196.47146.621. (CXX) g++ options: -O3 -rdynamic -lOpenCL

SHOC Scalable HeterOgeneous Computing

The CUDA and OpenCL version of Vetter's Scalable HeterOgeneous Computing benchmark suite. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgGHash/s, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: MD5 HashTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 1060816243240SE +/- 0.06, N = 3SE +/- 0.12, N = 3SE +/- 0.02, N = 3SE +/- 0.01, N = 3SE +/- 0.05, N = 3SE +/- 0.03, N = 3SE +/- 0.02, N = 3SE +/- 0.03, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.00, N = 3SE +/- 0.04, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 3SE +/- 0.02, N = 3SE +/- 0.00, N = 336.3934.9126.5624.0721.7818.7718.2216.049.227.496.5012.9811.8719.7214.2511.7010.617.261. (CXX) g++ options: -O2 -lSHOCCommonMPI -lSHOCCommonOpenCL -lSHOCCommon -lOpenCL -lrt -pthread -lmpi_cxx -lmpi

System Power Consumption Monitor

OpenBenchmarking.orgWattsSystem Power Consumption MonitorPhoronix Test Suite System MonitoringTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106070140210280350Min: 50.6 / Avg: 227.86 / Max: 371.4Min: 49.7 / Avg: 227.4 / Max: 374Min: 46 / Avg: 173.42 / Max: 330.5Min: 47.5 / Avg: 181.54 / Max: 342.9Min: 45.5 / Avg: 134.05 / Max: 323.3Min: 46 / Avg: 164.53 / Max: 321.3Min: 45.4 / Avg: 158.95 / Max: 312Min: 46.1 / Avg: 153.75 / Max: 303.8Min: 53.6 / Avg: 199.07 / Max: 370.3Min: 49.8 / Avg: 167.77 / Max: 329.4Min: 48.8 / Avg: 157.71 / Max: 306.3Min: 45.4 / Avg: 127.55 / Max: 273.9Min: 43.1 / Avg: 115.15 / Max: 262.4Min: 49.6 / Avg: 207.86 / Max: 380Min: 44.9 / Avg: 162.99 / Max: 328.3Min: 48.6 / Avg: 131.89 / Max: 259.9Min: 43.8 / Avg: 150.54 / Max: 286.9Min: 44.3 / Avg: 128.45 / Max: 269.5

GPU Temperature Monitor

OpenBenchmarking.orgCelsiusGPU Temperature MonitorPhoronix Test Suite System MonitoringTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10601632486480Min: 37 / Avg: 62.01 / Max: 80Min: 31 / Avg: 60.94 / Max: 77Min: 34 / Avg: 53.35 / Max: 70Min: 30 / Avg: 66.02 / Max: 83Min: 27 / Avg: 43.67 / Max: 69Min: 28 / Avg: 58.64 / Max: 77Min: 29 / Avg: 54.33 / Max: 75Min: 32 / Avg: 57.94 / Max: 72Min: 36 / Avg: 71.62 / Max: 85Min: 29 / Avg: 68.53 / Max: 81Min: 28 / Avg: 52.34 / Max: 68Min: 30 / Avg: 50.73 / Max: 65Min: 28 / Avg: 56.71 / Max: 77Min: 34 / Avg: 67.92 / Max: 84Min: 30 / Avg: 63.66 / Max: 77Min: 39 / Avg: 48.41 / Max: 61Min: 28 / Avg: 61.94 / Max: 76Min: 30 / Avg: 58.15 / Max: 74

OctaneBench

OpenBenchmarking.orgWatts, Fewer Is BetterOctaneBench 4.00cSystem Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060120180240300Min: 55.3 / Avg: 326.69 / Max: 357.7Min: 51.7 / Avg: 322.94 / Max: 355.5Min: 47.8 / Avg: 225.1 / Max: 261.8Min: 50 / Avg: 239.21 / Max: 278.1Min: 49 / Avg: 211.57 / Max: 245.6Min: 47.1 / Avg: 215.17 / Max: 242.1Min: 46.5 / Avg: 210.53 / Max: 232.6Min: 49.8 / Avg: 188.5 / Max: 218.2Min: 128.3 / Avg: 220.62 / Max: 240Min: 53.6 / Avg: 178.66 / Max: 203.2Min: 50.8 / Avg: 160.22 / Max: 180Min: 47.1 / Avg: 145.79 / Max: 161.1Min: 46.3 / Avg: 127.11 / Max: 144.7Min: 130.6 / Avg: 236.94 / Max: 265Min: 48.3 / Avg: 167.77 / Max: 228.3Min: 52.2 / Avg: 132.45 / Max: 182.7Min: 86 / Avg: 157.88 / Max: 173.8Min: 44.9 / Avg: 120.33 / Max: 135.2

OpenBenchmarking.orgScore Per Watt, More Is BetterOctaneBench 4.00cTotal ScoreTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.24080.48160.72240.96321.2040.990.961.040.931.040.960.970.870.640.610.600.910.930.890.881.070.840.76

LeelaChessZero

OpenBenchmarking.orgWatts, Fewer Is BetterLeelaChessZero 0.22.0System Power Consumption MonitorTITAN RTXRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106070140210280350Min: 53.3 / Avg: 197.7 / Max: 371.4Min: 47.5 / Avg: 170.9 / Max: 315Min: 52.8 / Avg: 175.13 / Max: 286.6Min: 47.2 / Avg: 178.69 / Max: 276Min: 48.6 / Avg: 172.95 / Max: 253.7Min: 45.5 / Avg: 151.83 / Max: 241.9Min: 49.1 / Avg: 147.07 / Max: 231.4Min: 59.1 / Avg: 216.14 / Max: 319.4Min: 51.8 / Avg: 153.94 / Max: 247.5Min: 82.3 / Avg: 164.63 / Max: 252.9Min: 47.9 / Avg: 134.26 / Max: 195.9Min: 46.5 / Avg: 118.46 / Max: 180.4Min: 106.6 / Avg: 215.46 / Max: 320.5Min: 48.8 / Avg: 161.47 / Max: 252.9Min: 52 / Avg: 128.59 / Max: 197.7Min: 71.9 / Avg: 152.4 / Max: 214.7Min: 47.2 / Avg: 138.37 / Max: 187.2

OpenBenchmarking.orgNodes Per Second Per Watt, More Is BetterLeelaChessZero 0.22.0Backend: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10604812162015.8114.0012.3210.738.985.786.574.792.161.831.263.132.848.757.105.864.211.90

PlaidML

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060120180240300Min: 53.2 / Avg: 260.22 / Max: 361.7Min: 52.9 / Avg: 251.39 / Max: 354Min: 49.5 / Avg: 224.18 / Max: 302.6Min: 49.9 / Avg: 230.45 / Max: 288.2Min: 47.5 / Avg: 199.98 / Max: 276.8Min: 49.7 / Avg: 197.21 / Max: 252.5Min: 55 / Avg: 193.52 / Max: 240.6Min: 50.1 / Avg: 192.21 / Max: 230.7Min: 119.7 / Avg: 273.57 / Max: 330.8Min: 55.7 / Avg: 208.34 / Max: 246.7Min: 75.4 / Avg: 201.26 / Max: 220.7Min: 48.3 / Avg: 167.7 / Max: 196.3Min: 46 / Avg: 160.67 / Max: 185.8Min: 55.7 / Avg: 245.95 / Max: 321.1Min: 89.9 / Avg: 209.47 / Max: 253.5Min: 52.4 / Avg: 180.41 / Max: 207.7Min: 84.2 / Avg: 180.68 / Max: 209.8Min: 45.1 / Avg: 170.04 / Max: 188.8

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG19 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.16880.33760.50640.67520.8440.750.740.640.560.610.530.520.460.250.260.240.440.420.560.480.500.430.32

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060120180240300Min: 52.4 / Avg: 239.94 / Max: 363Min: 52.7 / Avg: 239.16 / Max: 354.3Min: 47.7 / Avg: 218.91 / Max: 299.1Min: 48.9 / Avg: 201.23 / Max: 285.7Min: 47.2 / Avg: 191.71 / Max: 276.3Min: 48.4 / Avg: 193.79 / Max: 250.6Min: 53.3 / Avg: 181.51 / Max: 239.5Min: 48.4 / Avg: 179.22 / Max: 228.5Min: 56.5 / Avg: 270.73 / Max: 328.7Min: 90.4 / Avg: 213.83 / Max: 251.4Min: 94.5 / Avg: 195.88 / Max: 219.3Min: 46.4 / Avg: 163.81 / Max: 195.7Min: 45.6 / Avg: 146.27 / Max: 182Min: 51.8 / Avg: 234.29 / Max: 318.4Min: 46.2 / Avg: 209.24 / Max: 254.3Min: 52.3 / Avg: 169.99 / Max: 205.7Min: 50 / Avg: 172.78 / Max: 208.8Min: 69.4 / Avg: 166.46 / Max: 190

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: VGG16 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.23180.46360.69540.92721.1591.030.980.820.820.810.680.710.620.320.320.310.560.580.750.610.670.560.42

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080GTX 1070 TiGTX 1070GTX 106050100150200250Min: 52.6 / Avg: 166.27 / Max: 275.3Min: 51.8 / Avg: 130.6 / Max: 207.8Min: 56.5 / Avg: 138.96 / Max: 215.1Min: 49.2 / Avg: 136.18 / Max: 192.6Min: 54.9 / Avg: 136.39 / Max: 187.2Min: 49.2 / Avg: 125.65 / Max: 186.5Min: 57.1 / Avg: 192.1 / Max: 249.1Min: 100 / Avg: 162.49 / Max: 218.7Min: 94.4 / Avg: 160.18 / Max: 203.4Min: 46.6 / Avg: 100.43 / Max: 150.5Min: 46.3 / Avg: 96.5 / Max: 135.8Min: 48.5 / Avg: 142.23 / Max: 208.8Min: 52.4 / Avg: 128.8 / Max: 152Min: 50.4 / Avg: 132.86 / Max: 187.3Min: 46.3 / Avg: 122.88 / Max: 159.6

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10601.14532.29063.43594.58125.72655.094.564.523.953.673.683.233.101.411.431.283.142.983.002.812.592.371.83

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorTITAN RTXRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060120180240300Min: 52.7 / Avg: 128.84 / Max: 167.9Min: 49.4 / Avg: 162.94 / Max: 270.3Min: 52 / Avg: 137.63 / Max: 231.8Min: 46.8 / Avg: 145.98 / Max: 249.6Min: 47.5 / Avg: 122.1 / Max: 239.9Min: 55.4 / Avg: 144.71 / Max: 231.4Min: 48.6 / Avg: 147.64 / Max: 221.8Min: 129.1 / Avg: 233.7 / Max: 292Min: 53 / Avg: 176.69 / Max: 244.6Min: 83.3 / Avg: 172.91 / Max: 233.2Min: 47.9 / Avg: 141.14 / Max: 182.8Min: 46.3 / Avg: 119.8 / Max: 159.7Min: 56.4 / Avg: 186.43 / Max: 312.7Min: 48.4 / Avg: 149.71 / Max: 246.6Min: 52.2 / Avg: 140.17 / Max: 177.3Min: 89.6 / Avg: 153.55 / Max: 208.4Min: 45.9 / Avg: 132.6 / Max: 182.3

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: ResNet 50 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10601.13182.26363.39544.52725.6595.033.703.183.212.893.092.592.161.061.151.051.841.902.662.252.101.801.48

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060120180240300Min: 56.2 / Avg: 178.56 / Max: 327.6Min: 51.8 / Avg: 206.66 / Max: 321.6Min: 49.6 / Avg: 170.73 / Max: 255.1Min: 49.4 / Avg: 176.08 / Max: 254.9Min: 49.5 / Avg: 161.34 / Max: 234.9Min: 49.8 / Avg: 167.7 / Max: 230.4Min: 54.4 / Avg: 162.79 / Max: 223.8Min: 47.6 / Avg: 150.66 / Max: 214.3Min: 126.5 / Avg: 220.09 / Max: 281.6Min: 56.7 / Avg: 188.31 / Max: 242.7Min: 81.4 / Avg: 182.54 / Max: 219.9Min: 46.3 / Avg: 136.65 / Max: 177.5Min: 46.3 / Avg: 123.06 / Max: 152.7Min: 128 / Avg: 191.53 / Max: 304Min: 84.7 / Avg: 196.13 / Max: 242.5Min: 51.1 / Avg: 141.76 / Max: 172.5Min: 84.3 / Avg: 149.15 / Max: 206.1Min: 46.9 / Avg: 150.12 / Max: 180

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Inception V3 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.43880.87761.31641.75522.1941.951.661.521.361.341.181.231.110.610.560.521.020.951.340.941.080.990.70

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106061218243023.2322.6316.6014.1619.7014.8412.9811.676.645.535.2011.209.5610.229.3511.309.657.59

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060120180240300Min: 52.8 / Avg: 227.24 / Max: 356.3Min: 52.9 / Avg: 210.77 / Max: 350.6Min: 49.1 / Avg: 194.92 / Max: 278.5Min: 52.6 / Avg: 181.66 / Max: 277.7Min: 47.2 / Avg: 198.27 / Max: 271.7Min: 48.7 / Avg: 189.06 / Max: 250.5Min: 57.1 / Avg: 209.61 / Max: 237.5Min: 48.9 / Avg: 179.62 / Max: 228Min: 71.2 / Avg: 244.52 / Max: 316.6Min: 53.3 / Avg: 201.25 / Max: 246.9Min: 89.6 / Avg: 193.7 / Max: 220.3Min: 48.2 / Avg: 154.23 / Max: 191.6Min: 45.5 / Avg: 136.67 / Max: 171.6Min: 120.6 / Avg: 236.48 / Max: 318.6Min: 91.2 / Avg: 194.23 / Max: 252.2Min: 51.9 / Avg: 158.16 / Max: 196.1Min: 70.7 / Avg: 170.23 / Max: 208.9Min: 45.9 / Avg: 157.15 / Max: 187.3

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG19 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.16430.32860.49290.65720.82150.710.730.590.580.490.440.390.400.230.220.200.380.380.490.430.460.370.28

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060120180240300Min: 53.8 / Avg: 216.91 / Max: 353.5Min: 52.7 / Avg: 188.04 / Max: 345.4Min: 49.4 / Avg: 181.31 / Max: 274.6Min: 54.1 / Avg: 173.35 / Max: 273.1Min: 46.7 / Avg: 187.65 / Max: 267.6Min: 48.1 / Avg: 174.02 / Max: 249.3Min: 54 / Avg: 187.95 / Max: 233.7Min: 48.1 / Avg: 163.79 / Max: 226.4Min: 55.1 / Avg: 244.29 / Max: 316.2Min: 69.1 / Avg: 196.2 / Max: 247.2Min: 51.5 / Avg: 184.27 / Max: 233.4Min: 47.3 / Avg: 151.58 / Max: 191.5Min: 45.6 / Avg: 137.8 / Max: 169.2Min: 118 / Avg: 235.58 / Max: 316.5Min: 88.2 / Avg: 189.28 / Max: 251.8Min: 95.2 / Avg: 160.1 / Max: 191.4Min: 47.7 / Avg: 162.2 / Max: 207.3Min: 45.8 / Avg: 152.31 / Max: 187.6

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: VGG16 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.2340.4680.7020.9361.170.941.040.800.770.660.610.550.550.290.280.270.480.480.620.560.570.490.37

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106050100150200250Min: 52.7 / Avg: 173.29 / Max: 277.5Min: 52.4 / Avg: 173.16 / Max: 273Min: 48.8 / Avg: 141.86 / Max: 214.3Min: 51.5 / Avg: 146.49 / Max: 216.5Min: 49.1 / Avg: 124.58 / Max: 203.3Min: 51.5 / Avg: 138.71 / Max: 203.8Min: 55.8 / Avg: 142.16 / Max: 204.9Min: 49 / Avg: 134.34 / Max: 190.3Min: 57 / Avg: 191.08 / Max: 247.4Min: 53.5 / Avg: 157.67 / Max: 213.1Min: 52.1 / Avg: 148.78 / Max: 190.2Min: 48.2 / Avg: 115.16 / Max: 152Min: 45.8 / Avg: 106.92 / Max: 138.1Min: 109.8 / Avg: 203.83 / Max: 255.3Min: 49.1 / Avg: 151.63 / Max: 200.9Min: 53.5 / Avg: 128.35 / Max: 157.6Min: 48.3 / Avg: 135.38 / Max: 188.6Min: 45.7 / Avg: 125.77 / Max: 157.6

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: DenseNet 201 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.34430.68861.03291.37721.72151.521.471.411.291.531.271.261.150.580.590.540.990.960.940.951.010.940.72

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060120180240300Min: 51.3 / Avg: 235.38 / Max: 341.7Min: 50.4 / Avg: 231.53 / Max: 336Min: 46.7 / Avg: 204.84 / Max: 277Min: 49.7 / Avg: 201.32 / Max: 272.7Min: 46.5 / Avg: 184.51 / Max: 249.7Min: 48 / Avg: 190.9 / Max: 247Min: 54.2 / Avg: 192.58 / Max: 235.4Min: 48.1 / Avg: 176.3 / Max: 224.1Min: 124.3 / Avg: 237.03 / Max: 284.6Min: 99.4 / Avg: 199.9 / Max: 241.3Min: 94.8 / Avg: 192.64 / Max: 216.8Min: 46.5 / Avg: 154.44 / Max: 184.5Min: 44.8 / Avg: 135.27 / Max: 159.9Min: 107 / Avg: 238.78 / Max: 315.7Min: 48.2 / Avg: 203.49 / Max: 246Min: 51.4 / Avg: 151.49 / Max: 175.5Min: 83.7 / Avg: 182.29 / Max: 211.2Min: 75.4 / Avg: 157.49 / Max: 178.6

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: NASNer Large - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.08330.16660.24990.33320.41650.370.370.320.290.300.260.250.230.130.120.110.220.210.240.200.230.180.15

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106050100150200250Min: 55.6 / Avg: 169.21 / Max: 293Min: 51.5 / Avg: 167.74 / Max: 291.7Min: 48.5 / Avg: 147.96 / Max: 225.2Min: 50.7 / Avg: 139.72 / Max: 234.8Min: 47.9 / Avg: 135.09 / Max: 211.7Min: 49 / Avg: 148.17 / Max: 210.6Min: 54.4 / Avg: 144.26 / Max: 207.2Min: 47.9 / Avg: 142.09 / Max: 199.4Min: 127.5 / Avg: 205.03 / Max: 260.5Min: 52.8 / Avg: 183.08 / Max: 228.8Min: 81.7 / Avg: 163.48 / Max: 201.2Min: 47.3 / Avg: 117.8 / Max: 162Min: 44.8 / Avg: 109.89 / Max: 143.5Min: 55.7 / Avg: 189.84 / Max: 284.9Min: 94.6 / Avg: 159.56 / Max: 227.4Min: 51.5 / Avg: 131.42 / Max: 162.8Min: 77.9 / Avg: 157.58 / Max: 202.6Min: 68.7 / Avg: 129.36 / Max: 164

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: ResNet 50 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.5761.1521.7282.3042.882.562.532.222.192.101.691.741.550.790.780.711.471.421.761.511.571.241.01

OpenBenchmarking.orgWatts, Fewer Is BetterPlaidMLSystem Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106050100150200250Min: 51.1 / Avg: 182.86 / Max: 282.6Min: 50.7 / Avg: 178.03 / Max: 280Min: 48.4 / Avg: 151.02 / Max: 226.9Min: 49 / Avg: 153.24 / Max: 230.1Min: 46.6 / Avg: 139.53 / Max: 205.1Min: 47.6 / Avg: 141.04 / Max: 207.9Min: 53 / Avg: 147.84 / Max: 203.6Min: 48.8 / Avg: 144.1 / Max: 197.4Min: 128.3 / Avg: 193.81 / Max: 239.9Min: 99.3 / Avg: 168.06 / Max: 211.7Min: 72.9 / Avg: 158.81 / Max: 190.7Min: 46.7 / Avg: 122.59 / Max: 164Min: 44.4 / Avg: 112.99 / Max: 143Min: 125.6 / Avg: 201.87 / Max: 257Min: 84.5 / Avg: 158.48 / Max: 204.6Min: 51 / Avg: 131.33 / Max: 154.1Min: 70.5 / Avg: 148.83 / Max: 185.2Min: 55.5 / Avg: 124.66 / Max: 155.7

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: Inception V3 - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.4590.9181.3771.8362.2952.042.041.991.751.721.571.491.340.600.610.561.321.221.131.101.120.950.78

OpenBenchmarking.orgFPS Per Watt, More Is BetterPlaidMLFP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCLTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106061218243022.1926.7125.0626.2124.7521.3520.6818.207.677.176.9816.0614.7915.2114.0214.1612.359.57

cl-mem

OpenBenchmarking.orgGB/s Per Watt, More Is Bettercl-mem 2017-01-13Benchmark: WriteTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.83481.66962.50443.33924.1743.133.462.852.742.603.712.612.241.481.031.072.331.612.021.641.761.541.44

OpenBenchmarking.orgGB/s Per Watt, More Is Bettercl-mem 2017-01-13Benchmark: ReadTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.86631.73262.59893.46524.33153.373.383.853.263.473.283.092.761.761.191.052.671.692.101.901.861.681.34

clpeak

OpenBenchmarking.orgWatts, Fewer Is BetterclpeakSystem Power Consumption MonitorTITAN RTXRTX 2080 SUPERRTX 2070 SUPERRTX 2070RTX 2060 SUPERGTX 1660 TiGTX 1080 TiGTX 106070140210280350Min: 52.5 / Avg: 207.88 / Max: 366.7Min: 47.9 / Avg: 144.19 / Max: 288.8Min: 47.5 / Avg: 141.91 / Max: 279.4Min: 47.8 / Avg: 135.68 / Max: 254.5Min: 47.4 / Avg: 86.98 / Max: 242.5Min: 46.4 / Avg: 77.81 / Max: 158.1Min: 52.4 / Avg: 199.89 / Max: 328.7Min: 66.2 / Avg: 117.06 / Max: 191

OpenBenchmarking.orgGIOPS Per Watt, More Is BetterclpeakOpenCL Test: Integer Compute INTTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106030609012015066.5854.7672.16123.0760.3952.7880.7463.259.008.449.1961.3879.9416.5226.8225.5923.8910.83

OpenBenchmarking.orgWatts, Fewer Is BetterclpeakSystem Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10604080120160200Min: 51.5 / Avg: 203.24 / Max: 225.1Min: 50.3 / Avg: 197 / Max: 217.1Min: 47.6 / Avg: 151.43 / Max: 166.9Min: 49.8 / Avg: 153.89 / Max: 172.5Min: 47 / Avg: 137.66 / Max: 150.3Min: 46.9 / Avg: 137.5 / Max: 151.9Min: 47.1 / Avg: 142.14 / Max: 150.8Min: 47.9 / Avg: 126.06 / Max: 143Min: 128.4 / Avg: 179.97 / Max: 191.4Min: 51.6 / Avg: 146.12 / Max: 159.1Min: 93.6 / Avg: 140.29 / Max: 146.2Min: 46.4 / Avg: 107.92 / Max: 119.4Min: 43.9 / Avg: 97.25 / Max: 106.6Min: 51.6 / Avg: 166.5 / Max: 193Min: 46.2 / Avg: 135.52 / Max: 152.6Min: 51 / Avg: 113.26 / Max: 124.1Min: 46 / Avg: 117.77 / Max: 137.1Min: 44.7 / Avg: 102.22 / Max: 117.3

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterclpeakOpenCL Test: Double-Precision DoubleTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.60751.2151.82252.433.03752.702.652.502.252.251.951.851.841.091.090.981.721.732.492.202.141.901.46

OpenBenchmarking.orgWatts, Fewer Is BetterclpeakSystem Power Consumption MonitorTITAN RTXRTX 2070 SUPERRTX 2070RTX 2060 SUPERGTX 980 TiGTX 980GTX 970GTX 1660 Ti60120180240300Min: 50.6 / Avg: 137.09 / Max: 308.7Min: 47.5 / Avg: 69.91 / Max: 138.9Min: 48.2 / Avg: 96.86 / Max: 180.2Min: 46.6 / Avg: 63.45 / Max: 103Min: 54.9 / Avg: 131.87 / Max: 194.2Min: 52.5 / Avg: 122.69 / Max: 181.1Min: 51.4 / Avg: 98.78 / Max: 148.8Min: 45.5 / Avg: 67.18 / Max: 127.1

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterclpeakOpenCL Test: Single-Precision FloatTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1080GTX 1070 TiGTX 107050100150200250103.61222.0984.4979.25121.6274.32111.74109.2042.0036.4939.3671.3589.1184.4670.63

OpenBenchmarking.orgGBPS Per Watt, More Is BetterclpeakOpenCL Test: Global Memory BandwidthTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERGTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106036912156.189.154.865.095.413.334.882.021.651.522.243.162.732.261.922.631.84

JuliaGPU

OpenBenchmarking.orgSamples/sec Per Watt, More Is BetterJuliaGPU 1.2pts1OpenCL Device: GPUTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 1060600K1200K1800K2400K3000K1923116.671910018.662379445.262691799.292632329.692271141.792670026.702469451.171099178.251325997.881275493.932880366.362790569.691682592.711906369.992260229.901809790.271658141.69

SHOC Scalable HeterOgeneous Computing

OpenBenchmarking.orgGHash/s Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: MD5 HashTITAN RTXRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080GTX 10600.08330.16660.24990.33320.41650.370.320.210.300.150.120.040.080.050.260.260.150.11

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: FFT SPRTX 2080 TiRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10604812162011.5415.4615.588.6717.5913.236.925.455.1212.255.707.977.876.366.234.00

OpenBenchmarking.orgWatts, Fewer Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10System Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106070140210280350Min: 52 / Avg: 223.03 / Max: 367Min: 51.3 / Avg: 217.17 / Max: 360Min: 47 / Avg: 164.08 / Max: 318.6Min: 48.7 / Avg: 171.33 / Max: 292.2Min: 47.1 / Avg: 150.09 / Max: 265.5Min: 47.9 / Avg: 149.29 / Max: 251.7Min: 46.8 / Avg: 148.63 / Max: 238Min: 47 / Avg: 145.37 / Max: 229.5Min: 126.9 / Avg: 193.91 / Max: 298.6Min: 97.6 / Avg: 160.93 / Max: 243.5Min: 80.6 / Avg: 148.92 / Max: 222.7Min: 46.4 / Avg: 118.75 / Max: 170.7Min: 44.5 / Avg: 106.24 / Max: 161Min: 49.6 / Avg: 199.67 / Max: 326.6Min: 94 / Avg: 157.13 / Max: 259.6Min: 50.5 / Avg: 125.61 / Max: 179.8Min: 78 / Avg: 141.46 / Max: 206.4Min: 74.8 / Avg: 119.53 / Max: 184.8

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterSHOC Scalable HeterOgeneous Computing 2015-11-10Target: OpenCL - Benchmark: Max SP FlopsTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10602040608010077.7276.6973.2363.9365.7657.1356.3850.3632.0531.4029.2949.6350.1766.2659.8761.4350.3040.06

cl-mem

OpenBenchmarking.orgGB/s Per Watt, More Is Bettercl-mem 2017-01-13Benchmark: CopyTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.72681.45362.18042.90723.6342.173.232.832.282.822.442.432.661.451.040.961.961.581.621.651.531.351.25

ViennaCL

OpenBenchmarking.orgGFLOPS Per Watt, More Is BetterViennaCL 1.4.2OpenCL LU FactorizationTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.3150.630.9451.261.5751.351.311.180.710.901.351.400.730.600.790.661.101.080.590.700.710.801.00

Rodinia

OpenBenchmarking.orgWatts, Fewer Is BetterRodinia 2.4System Power Consumption MonitorRTX 2070 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1070 TiGTX 10604080120160200Min: 47 / Avg: 103.36 / Max: 166Min: 47.6 / Avg: 121.91 / Max: 156.6Min: 54.7 / Avg: 167.04 / Max: 233.5Min: 52.6 / Avg: 156.47 / Max: 203.2Min: 50.5 / Avg: 141.83 / Max: 190Min: 46 / Avg: 107.04 / Max: 129.7Min: 45.1 / Avg: 88.85 / Max: 116.6Min: 50.3 / Avg: 101.74 / Max: 149.4Min: 44.7 / Avg: 111.27 / Max: 154.1

OpenBenchmarking.orgWatts, Fewer Is BetterRodinia 2.4System Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 1060306090120150Min: 51.9 / Avg: 158.82 / Max: 169.5Min: 51.1 / Avg: 152.87 / Max: 162.6Min: 46.6 / Avg: 123.16 / Max: 135.3Min: 49.5 / Avg: 131.08 / Max: 142Min: 46.4 / Avg: 116.19 / Max: 128.7Min: 48.1 / Avg: 122.39 / Max: 128.3Min: 46.3 / Avg: 122.27 / Max: 129.5Min: 46.6 / Avg: 112.18 / Max: 123.5Min: 110.1 / Avg: 153.24 / Max: 157.4Min: 88.8 / Avg: 119.77 / Max: 124.7Min: 85.4 / Avg: 117.57 / Max: 120.9Min: 45.9 / Avg: 98.53 / Max: 104.6Min: 45.5 / Avg: 90.35 / Max: 95.7Min: 53.3 / Avg: 137.65 / Max: 146.3Min: 47.4 / Avg: 113.6 / Max: 118.7Min: 49.1 / Avg: 105.1 / Max: 108.7Min: 70.9 / Avg: 107.97 / Max: 112.9Min: 62.8 / Avg: 97.17 / Max: 100.8

LuxMark

OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106070140210280350Min: 57.7 / Avg: 358.16 / Max: 371Min: 54.2 / Avg: 341.41 / Max: 361Min: 50.8 / Avg: 249.5 / Max: 264.2Min: 52.6 / Avg: 269.03 / Max: 281.5Min: 47.6 / Avg: 241.53 / Max: 254.1Min: 51.8 / Avg: 241 / Max: 251.5Min: 47.9 / Avg: 233.07 / Max: 242.2Min: 50.4 / Avg: 210.86 / Max: 220.4Min: 57.2 / Avg: 255.39 / Max: 271.7Min: 51.4 / Avg: 215.19 / Max: 226.6Min: 50.9 / Avg: 198.98 / Max: 206.3Min: 47.2 / Avg: 169.1 / Max: 176.4Min: 46.7 / Avg: 154.16 / Max: 157.9Min: 55.9 / Avg: 282.16 / Max: 295.6Min: 47.9 / Avg: 205.71 / Max: 214.4Min: 51.1 / Avg: 162.66 / Max: 167.9Min: 48.8 / Avg: 197.56 / Max: 206Min: 45.7 / Avg: 155.74 / Max: 161.6

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: HotelTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106061218243027.4626.9927.4124.5027.1825.5226.3822.9215.2114.1613.7222.5024.2220.0218.5125.6419.5917.00

OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060120180240300Min: 60.2 / Avg: 337.98 / Max: 356.9Min: 55.9 / Avg: 318.95 / Max: 337.2Min: 47.8 / Avg: 225.09 / Max: 235.4Min: 53.8 / Avg: 241.11 / Max: 251.4Min: 47.6 / Avg: 220.93 / Max: 232.4Min: 51.5 / Avg: 219.74 / Max: 234.1Min: 49.8 / Avg: 222.76 / Max: 232.3Min: 48.6 / Avg: 190.73 / Max: 198.4Min: 112.5 / Avg: 234.81 / Max: 244.3Min: 51 / Avg: 193.46 / Max: 203.7Min: 51.9 / Avg: 177.8 / Max: 184.4Min: 48 / Avg: 156.46 / Max: 161.4Min: 46 / Avg: 137.52 / Max: 142.7Min: 52.7 / Avg: 237.89 / Max: 245.4Min: 49.1 / Avg: 173.32 / Max: 180.3Min: 50.1 / Avg: 145.89 / Max: 150.4Min: 49 / Avg: 170.27 / Max: 177.6Min: 45.6 / Avg: 138.57 / Max: 144.8

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: MicrophoneTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10602040608010091.0089.7789.5882.6092.7883.9283.0972.1147.2546.0844.9170.3371.2257.6850.2970.3258.6351.14

OpenBenchmarking.orgWatts, Fewer Is BetterLuxMark 3.1System Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060120180240300Min: 53.7 / Avg: 338.9 / Max: 360.6Min: 53.9 / Avg: 326.39 / Max: 340.7Min: 49.4 / Avg: 230.52 / Max: 238Min: 52.5 / Avg: 244.9 / Max: 255.3Min: 47.5 / Avg: 217.27 / Max: 227.7Min: 50.1 / Avg: 230.98 / Max: 243.5Min: 47.2 / Avg: 229.14 / Max: 241Min: 47.4 / Avg: 192.86 / Max: 200.8Min: 130.4 / Avg: 238.82 / Max: 247.5Min: 87.7 / Avg: 195.16 / Max: 205Min: 52.2 / Avg: 180.29 / Max: 185.6Min: 48.2 / Avg: 157.16 / Max: 163.8Min: 45.9 / Avg: 139.49 / Max: 144Min: 107.7 / Avg: 245.73 / Max: 254Min: 75.8 / Avg: 180.11 / Max: 185.5Min: 52.3 / Avg: 151.74 / Max: 155.9Min: 48.6 / Avg: 181.94 / Max: 188.2Min: 76 / Avg: 146.92 / Max: 152

OpenBenchmarking.orgScore Per Watt, More Is BetterLuxMark 3.1OpenCL Device: GPU - Scene: Luxball HDRTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 1060306090120150137.34131.66130.92119.09136.85130.30131.33112.4370.6467.8765.07102.75108.7088.2676.55111.5495.0383.34

NAMD CUDA

OpenBenchmarking.orgWatts, Fewer Is BetterNAMD CUDA 2.13System Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106070140210280350Min: 54.3 / Avg: 214.96 / Max: 367.7Min: 53.9 / Avg: 251.92 / Max: 374Min: 48.8 / Avg: 219.44 / Max: 330.5Min: 52.9 / Avg: 238.49 / Max: 342.9Min: 47.2 / Avg: 198.42 / Max: 323.3Min: 50 / Avg: 202.69 / Max: 321.3Min: 48.4 / Avg: 233.81 / Max: 312Min: 46.1 / Avg: 197.89 / Max: 303.8Min: 55.9 / Avg: 272.91 / Max: 370.3Min: 52.6 / Avg: 238.95 / Max: 329.4Min: 51.3 / Avg: 258.19 / Max: 306.3Min: 47.7 / Avg: 177.22 / Max: 273.9Min: 44.9 / Avg: 177.54 / Max: 262.4Min: 55.3 / Avg: 266.23 / Max: 380Min: 48.6 / Avg: 253.18 / Max: 326.9Min: 50.3 / Avg: 198.82 / Max: 259.9Min: 48.2 / Avg: 206.59 / Max: 286.9Min: 45.2 / Avg: 198.8 / Max: 269.5

FAHBench

OpenBenchmarking.orgWatts, Fewer Is BetterFAHBench 2.3.2System Power Consumption MonitorTITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 106060120180240300Min: 52.5 / Avg: 226.18 / Max: 324.2Min: 49.7 / Avg: 218.05 / Max: 323.3Min: 64 / Avg: 177.55 / Max: 252.2Min: 47.5 / Avg: 176.01 / Max: 263Min: 46.6 / Avg: 161.4 / Max: 230Min: 46 / Avg: 158.7 / Max: 226.7Min: 48.5 / Avg: 161.35 / Max: 226.3Min: 45.7 / Avg: 151.46 / Max: 214.2Min: 56.3 / Avg: 186.17 / Max: 244.4Min: 49.8 / Avg: 159.19 / Max: 211.9Min: 48.8 / Avg: 147.69 / Max: 193Min: 47.6 / Avg: 127.19 / Max: 170.3Min: 46.5 / Avg: 114.3 / Max: 152.8Min: 77.6 / Avg: 195.24 / Max: 264.4Min: 44.9 / Avg: 154.62 / Max: 208.2Min: 49.1 / Avg: 125.16 / Max: 155Min: 43.8 / Avg: 145.58 / Max: 193.2Min: 66.3 / Avg: 124.04 / Max: 159.6

OpenBenchmarking.orgNs Per Day Per Watt, More Is BetterFAHBench 2.3.2TITAN RTXRTX 2080 TiRTX 2080 SUPERRTX 2080RTX 2070 SUPERRTX 2070RTX 2060 SUPERRTX 2060GTX 980 TiGTX 980GTX 970GTX 1660 TiGTX 1660GTX 1080 TiGTX 1080GTX 1070 TiGTX 1070GTX 10600.32630.65260.97891.30521.63151.331.381.451.381.421.291.271.210.620.650.621.101.111.021.001.100.960.83

94 Results Shown

SHOC Scalable HeterOgeneous Computing
OctaneBench
LuxMark:
  GPU - Microphone
  GPU - Luxball HDR
  GPU - Hotel
FAHBench
PlaidML:
  Yes - Inference - NASNer Large - OpenCL
  Yes - Inference - VGG19 - OpenCL
  Yes - Inference - DenseNet 201 - OpenCL
Rodinia
PlaidML
clpeak
PlaidML:
  No - Inference - VGG19 - OpenCL
  Yes - Inference - Inception V3 - OpenCL
LeelaChessZero
PlaidML:
  No - Inference - VGG16 - OpenCL
  No - Inference - Inception V3 - OpenCL
  Yes - Inference - ResNet 50 - OpenCL
NAMD CUDA
PlaidML:
  No - Inference - ResNet 50 - OpenCL
  No - Inference - IMDB LSTM - OpenCL
Rodinia
cl-mem
JuliaGPU
PlaidML
cl-mem:
  Copy
  Write
PlaidML
Darktable
clpeak
Darktable
clpeak
Darktable
ViennaCL
SHOC Scalable HeterOgeneous Computing
clpeak
SHOC Scalable HeterOgeneous Computing
System Power Consumption Monitor:
  Phoronix Test Suite System Monitoring:
    Watts
    Celsius
  System Power Consumption Monitor:
    Watts
  Total Score:
    Score Per Watt
  System Power Consumption Monitor:
    Watts
  OpenCL:
    Nodes Per Second Per Watt
  System Power Consumption Monitor:
    Watts
  No - Inference - VGG19 - OpenCL:
    FPS Per Watt
  System Power Consumption Monitor:
    Watts
  No - Inference - VGG16 - OpenCL:
    FPS Per Watt
  System Power Consumption Monitor:
    Watts
  No - Inference - IMDB LSTM - OpenCL:
    FPS Per Watt
  System Power Consumption Monitor:
    Watts
  No - Inference - ResNet 50 - OpenCL:
    FPS Per Watt
  System Power Consumption Monitor:
    Watts
  No - Inference - Inception V3 - OpenCL:
    FPS Per Watt
  No - Inference - Mobilenet - OpenCL:
    FPS Per Watt
  System Power Consumption Monitor:
    Watts
  Yes - Inference - VGG19 - OpenCL:
    FPS Per Watt
  System Power Consumption Monitor:
    Watts
  Yes - Inference - VGG16 - OpenCL:
    FPS Per Watt
  System Power Consumption Monitor:
    Watts
  Yes - Inference - DenseNet 201 - OpenCL:
    FPS Per Watt
  System Power Consumption Monitor:
    Watts
  Yes - Inference - NASNer Large - OpenCL:
    FPS Per Watt
  System Power Consumption Monitor:
    Watts
  Yes - Inference - ResNet 50 - OpenCL:
    FPS Per Watt
  System Power Consumption Monitor:
    Watts
  Yes - Inference - Inception V3 - OpenCL:
    FPS Per Watt
  Yes - Inference - Mobilenet - OpenCL:
    FPS Per Watt
  Write:
    GB/s Per Watt
  Read:
    GB/s Per Watt
  System Power Consumption Monitor:
    Watts
  Integer Compute INT:
    GIOPS Per Watt
  System Power Consumption Monitor:
    Watts
  Double-Precision Double:
    GFLOPS Per Watt
  System Power Consumption Monitor:
    Watts
  Single-Precision Float:
    GFLOPS Per Watt
  Global Memory Bandwidth:
    GBPS Per Watt
  GPU:
    Samples/sec Per Watt
  OpenCL - MD5 Hash:
    GHash/s Per Watt
  OpenCL - FFT SP:
    GFLOPS Per Watt
  System Power Consumption Monitor:
    Watts
  OpenCL - Max SP Flops:
    GFLOPS Per Watt
  Copy:
    GB/s Per Watt
  OpenCL LU Factorization:
    GFLOPS Per Watt
  System Power Consumption Monitor:
    Watts
    Watts
    Watts
  GPU - Hotel:
    Score Per Watt
  System Power Consumption Monitor:
    Watts
  GPU - Microphone:
    Score Per Watt
  System Power Consumption Monitor:
    Watts
  GPU - Luxball HDR:
    Score Per Watt
  System Power Consumption Monitor:
    Watts
    Watts
  :
    Ns Per Day Per Watt

GTX 970

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: eVGA NVIDIA GeForce GTX 970 4GB (1163/3505MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 1664
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 28 September 2019 21:18 by user pts.

GTX 980

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce GTX 980 4GB (1126/3505MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2048
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 28 September 2019 13:43 by user pts.

GTX 980 Ti

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce GTX 980 Ti 6GB (999/3505MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.3.0-999-generic (x86_64) 20190914, Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2816
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 26 September 2019 18:04 by user pts.

GTX 1060

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce GTX 1060 6GB (1506/4006MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 1280
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 27 September 2019 22:37 by user pts.

GTX 1070

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce GTX 1070 8GB (1506/4006MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 1920
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 28 September 2019 19:12 by user pts.

GTX 1070 Ti

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: Zotac NVIDIA GeForce GTX 1070 Ti 8GB (1607/4006MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2432
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 27 September 2019 14:42 by user pts.

GTX 1080

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce GTX 1080 8GB (1607/5005MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2560
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 28 September 2019 07:03 by user pts.

GTX 1080 Ti

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce GTX 1080 Ti 11GB (1480/5508MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 3584
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 28 September 2019 09:28 by user pts.

GTX 1660

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: ASUS NVIDIA GeForce GTX 1660 6GB (1530/4001MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 1408
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 28 September 2019 16:56 by user pts.

GTX 1660 Ti

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: eVGA NVIDIA GeForce GTX 1660 Ti 6GB (1500/6000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 1536
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 28 September 2019 11:20 by user pts.

RTX 2060

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce RTX 2060 6GB (1365/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 1920
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 27 September 2019 18:59 by user pts.

RTX 2060 SUPER

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce RTX 2060 SUPER 8GB (1470/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.3.0-999-generic (x86_64) 20190914, Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2176
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 26 September 2019 10:17 by user phoronix.

RTX 2070

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: ASUS NVIDIA GeForce RTX 2070 8GB (1410/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2304
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 27 September 2019 12:10 by user pts.

RTX 2070 SUPER

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce RTX 2070 SUPER 8GB (1605/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.3.0-999-generic (x86_64) 20190914, Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2560
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 26 September 2019 07:22 by user phoronix.

RTX 2080

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: Zotac NVIDIA GeForce RTX 2080 8GB (795/810MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 2944
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 27 September 2019 17:01 by user pts.

RTX 2080 SUPER

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce RTX 2080 SUPER 8GB (1650/7750MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.3.0-999-generic (x86_64) 20190914, Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 3072
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 27 September 2019 05:56 by user pts.

RTX 2080 Ti

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA GeForce RTX 2080 Ti 11GB (1350/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.0.0-29-generic (x86_64), Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 4352
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 29 September 2019 08:48 by user pts.

TITAN RTX

Processor: Intel Core i9-9900K @ 5.00GHz (8 Cores / 16 Threads), Motherboard: ASUS PRIME Z390-A (0802 BIOS), Chipset: Intel Cannon Lake PCH, Memory: 16384MB, Disk: Samsung SSD 970 EVO 250GB, Graphics: NVIDIA TITAN RTX 24GB (1350/7000MHz), Audio: Realtek ALC1220, Monitor: Acer B286HK, Network: Intel I219-V

OS: Ubuntu 19.04, Kernel: 5.3.0-999-generic (x86_64) 20190914, Desktop: GNOME Shell 3.32.2, Display Server: X Server 1.20.4, Display Driver: NVIDIA 435.21, OpenGL: 4.6.0, Compiler: GCC 8.3.0, File-System: ext4, Screen Resolution: 3840x2160

Compiler Notes: --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++ --enable-libmpx --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib --with-tune=generic --without-cuda-driver -v
Processor Notes: Scaling Governor: intel_pstate performance
OpenCL Notes: GPU Compute Cores: 4608
Python Notes: Python 2.7.16 + Python 3.7.3
Security Notes: l1tf: Not affected + mds: Mitigation of Clear buffers; SMT vulnerable + meltdown: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl and seccomp + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Full generic retpoline IBPB: conditional IBRS_FW STIBP: conditional RSB filling

Testing initiated at 27 September 2019 06:15 by user pts.