AMD Ryzen Threadripper 3970X 32-Core testing with a ASUS ROG ZENITH II EXTREME (1802 BIOS) and AMD Radeon RX 5700 8GB on Ubuntu 22.04 via the Phoronix Test Suite.
Compare your own system(s) to this result file with the
Phoronix Test Suite by running the command:
phoronix-test-suite benchmark 2403165-NE-DFGG2384950
{
"title": "dfgg",
"last_modified": "2024-03-16 09:13:51",
"description": "AMD Ryzen Threadripper 3970X 32-Core testing with a ASUS ROG ZENITH II EXTREME (1802 BIOS) and AMD Radeon RX 5700 8GB on Ubuntu 22.04 via the Phoronix Test Suite.",
"systems": {
"a": {
"identifier": "a",
"hardware": {
"Processor": "AMD Ryzen Threadripper 3970X 32-Core @ 3.70GHz (32 Cores \/ 64 Threads)",
"Motherboard": "ASUS ROG ZENITH II EXTREME (1802 BIOS)",
"Chipset": "AMD Starship\/Matisse",
"Memory": "4 x 16GB DDR4-3600MT\/s Corsair CMT64GX4M4Z3600C16",
"Disk": "Samsung SSD 980 PRO 500GB",
"Graphics": "AMD Radeon RX 5700 8GB (1750\/875MHz)",
"Audio": "AMD Navi 10 HDMI Audio",
"Monitor": "ASUS VP28U",
"Network": "Aquantia AQC107 NBase-T\/IEEE + Intel I211 + Intel Wi-Fi 6 AX200"
},
"software": {
"OS": "Ubuntu 22.04",
"Kernel": "6.5.0-21-generic (x86_64)",
"Desktop": "GNOME Shell 42.2",
"Display Server": "X Server + Wayland",
"OpenGL": "4.6 Mesa 22.0.1 (LLVM 13.0.1 DRM 3.54)",
"Vulkan": "1.2.204",
"Compiler": "GCC 11.4.0",
"File-System": "ext4",
"Screen Resolution": "3840x2160"
},
"user": "phoronix",
"timestamp": "2024-03-15 21:38:54",
"client_version": "10.8.4",
"data": {
"compiler-configuration": "--build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --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++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=\/build\/gcc-11-XeT9lY\/gcc-11-11.4.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-11-XeT9lY\/gcc-11-11.4.0\/debian\/tmp-gcn\/usr --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-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v",
"cpu-scaling-governor": "acpi-cpufreq schedutil (Boost: Enabled)",
"cpu-microcode": "0x830107a",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.10.12",
"security": "gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT enabled with STIBP protection + spec_rstack_overflow: Mitigation of safe RET + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected"
}
},
"b": {
"identifier": "b",
"hardware": {
"Processor": "AMD Ryzen Threadripper 3970X 32-Core @ 3.70GHz (32 Cores \/ 64 Threads)",
"Motherboard": "ASUS ROG ZENITH II EXTREME (1802 BIOS)",
"Chipset": "AMD Starship\/Matisse",
"Memory": "4 x 16GB DDR4-3600MT\/s Corsair CMT64GX4M4Z3600C16",
"Disk": "Samsung SSD 980 PRO 500GB",
"Graphics": "AMD Radeon RX 5700 8GB (1750\/875MHz)",
"Audio": "AMD Navi 10 HDMI Audio",
"Monitor": "ASUS VP28U",
"Network": "Aquantia AQC107 NBase-T\/IEEE + Intel I211 + Intel Wi-Fi 6 AX200"
},
"software": {
"OS": "Ubuntu 22.04",
"Kernel": "6.5.0-21-generic (x86_64)",
"Desktop": "GNOME Shell 42.2",
"Display Server": "X Server + Wayland",
"OpenGL": "4.6 Mesa 22.0.1 (LLVM 13.0.1 DRM 3.54)",
"Vulkan": "1.2.204",
"Compiler": "GCC 11.4.0",
"File-System": "ext4",
"Screen Resolution": "3840x2160"
},
"user": "phoronix",
"timestamp": "2024-03-16 06:28:22",
"client_version": "10.8.4",
"data": {
"compiler-configuration": "--build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --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++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=\/build\/gcc-11-XeT9lY\/gcc-11-11.4.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-11-XeT9lY\/gcc-11-11.4.0\/debian\/tmp-gcn\/usr --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-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v",
"cpu-scaling-governor": "acpi-cpufreq schedutil (Boost: Enabled)",
"cpu-microcode": "0x830107a",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.10.12",
"security": "gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT enabled with STIBP protection + spec_rstack_overflow: Mitigation of safe RET + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected"
}
},
"c": {
"identifier": "c",
"hardware": {
"Processor": "AMD Ryzen Threadripper 3970X 32-Core @ 3.70GHz (32 Cores \/ 64 Threads)",
"Motherboard": "ASUS ROG ZENITH II EXTREME (1802 BIOS)",
"Chipset": "AMD Starship\/Matisse",
"Memory": "4 x 16GB DDR4-3600MT\/s Corsair CMT64GX4M4Z3600C16",
"Disk": "Samsung SSD 980 PRO 500GB",
"Graphics": "AMD Radeon RX 5700 8GB (1750\/875MHz)",
"Audio": "AMD Navi 10 HDMI Audio",
"Monitor": "ASUS VP28U",
"Network": "Aquantia AQC107 NBase-T\/IEEE + Intel I211 + Intel Wi-Fi 6 AX200"
},
"software": {
"OS": "Ubuntu 22.04",
"Kernel": "6.5.0-21-generic (x86_64)",
"Desktop": "GNOME Shell 42.2",
"Display Server": "X Server + Wayland",
"OpenGL": "4.6 Mesa 22.0.1 (LLVM 13.0.1 DRM 3.54)",
"Vulkan": "1.2.204",
"Compiler": "GCC 11.4.0",
"File-System": "ext4",
"Screen Resolution": "3840x2160"
},
"user": "phoronix",
"timestamp": "2024-03-16 08:32:50",
"client_version": "10.8.4",
"data": {
"compiler-configuration": "--build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --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++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=\/build\/gcc-11-XeT9lY\/gcc-11-11.4.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-11-XeT9lY\/gcc-11-11.4.0\/debian\/tmp-gcn\/usr --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-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v",
"cpu-scaling-governor": "acpi-cpufreq schedutil (Boost: Enabled)",
"cpu-microcode": "0x830107a",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.10.12",
"security": "gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT enabled with STIBP protection + spec_rstack_overflow: Mitigation of safe RET + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected"
}
}
},
"results": {
"f7ef6dae6a4577a8b3a8d9197d0045eae3fa6d3b": {
"identifier": "pts\/srsran-2.2.0",
"title": "srsRAN Project",
"app_version": "23.10.1-20240219",
"arguments": "tests\/benchmarks\/phy\/upper\/channel_processors\/pdsch_processor_benchmark -m throughput_total -R 350 -B 10 -P 4port_4layer_scs30_100MHz_256qam",
"description": "Test: PDSCH Processor Benchmark, Throughput Total",
"scale": "Mbps",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 11658,
"raw_values": [
11704.100000000000363797880709171295166015625,
11619.29999999999927240423858165740966796875,
11650.600000000000363797880709171295166015625
],
"test_run_times": [
16.089999999999999857891452847979962825775146484375,
16.1700000000000017053025658242404460906982421875,
16.14999999999999857891452847979962825775146484375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
},
"b": {
"value": 11575.899999999999636202119290828704833984375,
"test_run_times": [
16.219999999999998863131622783839702606201171875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
},
"c": {
"value": 11512.100000000000363797880709171295166015625,
"test_run_times": [
16.3900000000000005684341886080801486968994140625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
}
}
},
"ea8b49e85cf01c80dbd51608551e0d04536767dc": {
"identifier": "pts\/srsran-2.2.0",
"title": "srsRAN Project",
"app_version": "23.10.1-20240219",
"arguments": "tests\/benchmarks\/phy\/upper\/channel_processors\/pdsch_processor_benchmark -m throughput_thread -R 350 -B 10 -T 1 -P 4port_4layer_scs30_100MHz_256qam",
"description": "Test: PDSCH Processor Benchmark, Throughput Thread",
"scale": "Mbps",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 484.5,
"raw_values": [
484.30000000000001136868377216160297393798828125,
487.6000000000000227373675443232059478759765625,
481.6000000000000227373675443232059478759765625
],
"test_run_times": [
6.30999999999999960920149533194489777088165283203125,
6.28000000000000024868995751603506505489349365234375,
6.339999999999999857891452847979962825775146484375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
},
"b": {
"value": 490.6000000000000227373675443232059478759765625,
"test_run_times": [
6.2400000000000002131628207280300557613372802734375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
},
"c": {
"value": 484.3999999999999772626324556767940521240234375,
"test_run_times": [
6.29000000000000003552713678800500929355621337890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
}
}
},
"07874bd30a80753be1d28881eddc0428fcb350ae": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 4 -n 160 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160",
"description": "Encoder Mode: Preset 4 - Input: Bosphorus 4K",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 4.69800000000000039790393202565610408782958984375,
"raw_values": [
4.6730000000000000426325641456060111522674560546875,
4.657000000000000028421709430404007434844970703125,
4.76499999999999968025576890795491635799407958984375
],
"test_run_times": [
38.07000000000000028421709430404007434844970703125,
38.1400000000000005684341886080801486968994140625,
37.3599999999999994315658113919198513031005859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 4.7460000000000004405364961712621152400970458984375,
"test_run_times": [
37.49000000000000198951966012828052043914794921875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 4.76199999999999956656893118633888661861419677734375,
"test_run_times": [
37.38000000000000255795384873636066913604736328125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"2d6461041456af39b5df4efcec7f39f3157f549d": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 8 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160",
"description": "Encoder Mode: Preset 8 - Input: Bosphorus 4K",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 45.48899999999999721467247582040727138519287109375,
"raw_values": [
45.70400000000000062527760746888816356658935546875,
45.5390000000000014779288903810083866119384765625,
45.22399999999999664623828721232712268829345703125
],
"test_run_times": [
16.35000000000000142108547152020037174224853515625,
16.3599999999999994315658113919198513031005859375,
16.449999999999999289457264239899814128875732421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 46.030000000000001136868377216160297393798828125,
"test_run_times": [
16.199999999999999289457264239899814128875732421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 45.72399999999999664623828721232712268829345703125,
"test_run_times": [
16.28999999999999914734871708787977695465087890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"b7dbdc4a31deb7c3fd3898dbe6df6073d5bae0ee": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 12 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160",
"description": "Encoder Mode: Preset 12 - Input: Bosphorus 4K",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 107.1830000000000069348971010185778141021728515625,
"raw_values": [
107.2900000000000062527760746888816356658935546875,
107.4009999999999962483343551866710186004638671875,
106.8589999999999946567186270840466022491455078125
],
"test_run_times": [
8.0299999999999993605115378159098327159881591796875,
8.0299999999999993605115378159098327159881591796875,
8.0600000000000004973799150320701301097869873046875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 107.3370000000000032969182939268648624420166015625,
"test_run_times": [
8.03999999999999914734871708787977695465087890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 108.614000000000004320099833421409130096435546875,
"test_run_times": [
7.980000000000000426325641456060111522674560546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"685f4e221e2e654e3714ee352fed82e506e17245": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 13 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160",
"description": "Encoder Mode: Preset 13 - Input: Bosphorus 4K",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 106.59399999999999408828443847596645355224609375,
"raw_values": [
105.5799999999999982946974341757595539093017578125,
106.55500000000000682121026329696178436279296875,
107.6470000000000055706550483591854572296142578125
],
"test_run_times": [
8.1300000000000007815970093361102044582366943359375,
8.089999999999999857891452847979962825775146484375,
8.0099999999999997868371792719699442386627197265625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 107.775000000000005684341886080801486968994140625,
"test_run_times": [
7.9900000000000002131628207280300557613372802734375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 108.2289999999999992041921359486877918243408203125,
"test_run_times": [
7.980000000000000426325641456060111522674560546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"dc904a5f05b6af7d9d2f0cb350633ab3906286e0": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 4 -n 160 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080",
"description": "Encoder Mode: Preset 4 - Input: Bosphorus 1080p",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 12.55799999999999982946974341757595539093017578125,
"raw_values": [
12.4700000000000006394884621840901672840118408203125,
12.5540000000000002700062395888380706310272216796875,
12.6489999999999991331378623726777732372283935546875
],
"test_run_times": [
15.089999999999999857891452847979962825775146484375,
15,
14.9000000000000003552713678800500929355621337890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 12.2690000000000001278976924368180334568023681640625,
"test_run_times": [
15.2799999999999993605115378159098327159881591796875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 12.5879999999999991899812812334857881069183349609375,
"test_run_times": [
14.96000000000000085265128291212022304534912109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"e25f1395e53b97de67de5cb714bfadc6f1a32e2b": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 8 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080",
"description": "Encoder Mode: Preset 8 - Input: Bosphorus 1080p",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 83.4659999999999939745976007543504238128662109375,
"raw_values": [
82.5139999999999957935870043002068996429443359375,
83.712999999999993860910763032734394073486328125,
84.1700000000000017053025658242404460906982421875
],
"test_run_times": [
9.4000000000000003552713678800500929355621337890625,
9.32000000000000028421709430404007434844970703125,
9.2799999999999993605115378159098327159881591796875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 84.22100000000000363797880709171295166015625,
"test_run_times": [
9.25
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 83.6880000000000023874235921539366245269775390625,
"test_run_times": [
9.3100000000000004973799150320701301097869873046875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"cf74c258930ce6572b669052b6a298b7e2c32c02": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 12 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080",
"description": "Encoder Mode: Preset 12 - Input: Bosphorus 1080p",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 297.09399999999999408828443847596645355224609375,
"raw_values": [
297.12799999999998590283212251961231231689453125,
293.16500000000002046363078989088535308837890625,
300.990000000000009094947017729282379150390625
],
"test_run_times": [
2.899999999999999911182158029987476766109466552734375,
2.930000000000000159872115546022541821002960205078125,
2.87999999999999989341858963598497211933135986328125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 298.3980000000000245563569478690624237060546875,
"test_run_times": [
2.87999999999999989341858963598497211933135986328125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 298.83899999999999863575794734060764312744140625,
"test_run_times": [
2.87000000000000010658141036401502788066864013671875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"fa830dfe04cd3079e6f88420aec30f0bb9868cfb": {
"identifier": "pts\/svt-av1-2.12.0",
"title": "SVT-AV1",
"app_version": "2.0",
"arguments": "--preset 13 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080",
"description": "Encoder Mode: Preset 13 - Input: Bosphorus 1080p",
"scale": "Frames Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 369.31099999999997862687450833618640899658203125,
"raw_values": [
370.17599999999998772182152606546878814697265625,
367.80099999999998772182152606546878814697265625,
369.9569999999999936335370875895023345947265625
],
"test_run_times": [
2.470000000000000195399252334027551114559173583984375,
2.4900000000000002131628207280300557613372802734375,
2.470000000000000195399252334027551114559173583984375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 368.721999999999979991116560995578765869140625,
"test_run_times": [
2.470000000000000195399252334027551114559173583984375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 365.61299999999999954525264911353588104248046875,
"test_run_times": [
2.4900000000000002131628207280300557613372802734375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"a94fc255324a86f95ba5207758d45b3e012d6e50": {
"identifier": "pts\/build-linux-kernel-1.16.0",
"title": "Timed Linux Kernel Compilation",
"app_version": "6.8",
"arguments": "defconfig",
"description": "Build: defconfig",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 46.70400000000000062527760746888816356658935546875,
"raw_values": [
49.02199999999999846522769075818359851837158203125,
46.24600000000000221689333557151257991790771484375,
46.1809999999999973852027324028313159942626953125,
46.215000000000003410605131648480892181396484375,
46.292000000000001591615728102624416351318359375,
46.27000000000000312638803734444081783294677734375
],
"test_run_times": [
49.02000000000000312638803734444081783294677734375,
46.25,
46.17999999999999971578290569595992565155029296875,
46.21000000000000085265128291212022304534912109375,
46.28999999999999914734871708787977695465087890625,
46.27000000000000312638803734444081783294677734375
]
},
"b": {
"value": 49.29599999999999937472239253111183643341064453125,
"test_run_times": [
49.2999999999999971578290569595992565155029296875
]
},
"c": {
"value": 49.24300000000000210320649784989655017852783203125,
"test_run_times": [
49.24000000000000198951966012828052043914794921875
]
}
}
},
"cb81925dba817594f846f03a3bc29a81ef048649": {
"identifier": "pts\/build-linux-kernel-1.16.0",
"title": "Timed Linux Kernel Compilation",
"app_version": "6.8",
"arguments": "allmodconfig",
"description": "Build: allmodconfig",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 488.89499999999998181010596454143524169921875,
"raw_values": [
490.971999999999979991116560995578765869140625,
487.7730000000000245563569478690624237060546875,
487.94099999999997407940099947154521942138671875
],
"test_run_times": [
490.970000000000027284841053187847137451171875,
487.76999999999998181010596454143524169921875,
487.93999999999999772626324556767940521240234375
]
},
"b": {
"value": 490.3220000000000027284841053187847137451171875,
"test_run_times": [
490.31999999999999317878973670303821563720703125
]
},
"c": {
"value": 490.0760000000000218278728425502777099609375,
"test_run_times": [
490.07999999999998408384271897375583648681640625
]
}
}
},
"cf383fd884ee444349b5cf03c7b5fac725ae7e7a": {
"identifier": "pts\/compress-pbzip2-1.6.1",
"title": "Parallel BZIP2 Compression",
"app_version": "1.1.13",
"description": "FreeBSD-13.0-RELEASE-amd64-memstick.img Compression",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 2.8459050000000001290345608140341937541961669921875,
"raw_values": [
3.1220330000000000580939740757457911968231201171875,
2.770033000000000189544380191364325582981109619140625,
2.8936820000000000874251782079227268695831298828125,
2.876590999999999898051328273140825331211090087890625,
2.92075800000000018741275198408402502536773681640625,
2.724091000000000040159875425160862505435943603515625,
2.954705000000000136850530907395295798778533935546875,
2.8456419999999997827444531139917671680450439453125,
2.750643000000000171212377608753740787506103515625,
2.580264000000000113033138404716737568378448486328125,
2.908758000000000176754610947682522237300872802734375,
2.70172599999999984987653078860603272914886474609375,
2.89298900000000003274180926382541656494140625,
2.97171800000000008168399290298111736774444580078125,
2.77494700000000005246647560852579772472381591796875
],
"test_run_times": [
3.25,
2.910000000000000142108547152020037174224853515625,
2.9900000000000002131628207280300557613372802734375,
2.979999999999999982236431605997495353221893310546875,
3.020000000000000017763568394002504646778106689453125,
2.819999999999999840127884453977458178997039794921875,
3.089999999999999857891452847979962825775146484375,
2.939999999999999946709294817992486059665679931640625,
2.850000000000000088817841970012523233890533447265625,
2.720000000000000195399252334027551114559173583984375,
3,
2.79999999999999982236431605997495353221893310546875,
2.9900000000000002131628207280300557613372802734375,
3.069999999999999840127884453977458178997039794921875,
2.87999999999999989341858963598497211933135986328125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O2 -pthread -lbz2 -lpthread"
}
}
},
"b": {
"value": 2.811453999999999897596580922254361212253570556640625,
"test_run_times": [
2.910000000000000142108547152020037174224853515625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O2 -pthread -lbz2 -lpthread"
}
}
},
"c": {
"value": 2.894648999999999805510242367745377123355865478515625,
"test_run_times": [
3.029999999999999804600747665972448885440826416015625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O2 -pthread -lbz2 -lpthread"
}
}
}
}
},
"7e0a0b59e46d596b26cb4b6781f8ea1acfb478d3": {
"identifier": "pts\/primesieve-1.10.0",
"title": "Primesieve",
"app_version": "12.1",
"arguments": "1e12",
"description": "Length: 1e12",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 5.5030000000000001136868377216160297393798828125,
"raw_values": [
5.493999999999999772626324556767940521240234375,
5.5069999999999996731503415503539144992828369140625,
5.5090000000000003410605131648480892181396484375
],
"test_run_times": [
5.5099999999999997868371792719699442386627197265625,
5.519999999999999573674358543939888477325439453125,
5.519999999999999573674358543939888477325439453125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"b": {
"value": 5.52099999999999990762944435118697583675384521484375,
"test_run_times": [
5.53000000000000024868995751603506505489349365234375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"c": {
"value": 5.5129999999999999005240169935859739780426025390625,
"test_run_times": [
5.519999999999999573674358543939888477325439453125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
}
}
},
"bac88c0115a98dbe6c3bea68025021e4ad108581": {
"identifier": "pts\/primesieve-1.10.0",
"title": "Primesieve",
"app_version": "12.1",
"arguments": "1e13",
"description": "Length: 1e13",
"scale": "Seconds",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 68.3539999999999992041921359486877918243408203125,
"raw_values": [
68.1470000000000055706550483591854572296142578125,
68.537000000000006139089236967265605926513671875,
68.3790000000000048885340220294892787933349609375
],
"test_run_times": [
68.159999999999996589394868351519107818603515625,
68.5499999999999971578290569595992565155029296875,
68.3900000000000005684341886080801486968994140625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"b": {
"value": 68.2240000000000037516656448133289813995361328125,
"test_run_times": [
68.2399999999999948840923025272786617279052734375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"c": {
"value": 68.1269999999999953388396534137427806854248046875,
"test_run_times": [
68.1400000000000005684341886080801486968994140625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
}
}
},
"947610139beb46c152f74ada08833bfe9728062d": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/document_classification\/obert-base\/pytorch\/huggingface\/imdb\/base-none --scenario async",
"description": "Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 30.303799999999998959765434847213327884674072265625,
"raw_values": [
30.5311999999999983401721692644059658050537109375,
30.245999999999998664179656771011650562286376953125,
30.13419999999999987494447850622236728668212890625
],
"test_run_times": [
45.659999999999996589394868351519107818603515625,
44.27000000000000312638803734444081783294677734375,
44.409999999999996589394868351519107818603515625
]
},
"b": {
"value": 30.542100000000001358557710773311555385589599609375,
"test_run_times": [
44.4200000000000017053025658242404460906982421875
]
},
"c": {
"value": 30.443999999999999062083588796667754650115966796875,
"test_run_times": [
44.469999999999998863131622783839702606201171875
]
}
}
},
"6f6400821c5c8b1463564cdf0dcc6fc2fc0a66f6": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/document_classification\/obert-base\/pytorch\/huggingface\/imdb\/base-none --scenario async",
"description": "Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 525.4017000000000052750692702829837799072265625,
"raw_values": [
521.4217999999999619831214658915996551513671875,
525.495400000000017826096154749393463134765625,
529.28800000000001091393642127513885498046875
],
"test_run_times": [
45.659999999999996589394868351519107818603515625,
44.27000000000000312638803734444081783294677734375,
44.409999999999996589394868351519107818603515625
]
},
"b": {
"value": 522.352200000000038926373235881328582763671875,
"test_run_times": [
44.4200000000000017053025658242404460906982421875
]
},
"c": {
"value": 524.8704999999999927240423858165740966796875,
"test_run_times": [
44.469999999999998863131622783839702606201171875
]
}
}
},
"5a36b450b1f8e7b3be90e33289141057ce6391e4": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/document_classification\/obert-base\/pytorch\/huggingface\/imdb\/base-none --scenario sync",
"description": "Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 17.642900000000000915179043659009039402008056640625,
"raw_values": [
17.625699999999998368593878694809973239898681640625,
17.661899999999999266719896695576608180999755859375,
17.64099999999999823785401531495153903961181640625
],
"test_run_times": [
44.50999999999999801048033987171947956085205078125,
44.43999999999999772626324556767940521240234375,
44.4200000000000017053025658242404460906982421875
]
},
"b": {
"value": 17.714800000000000324007487506605684757232666015625,
"test_run_times": [
44.38000000000000255795384873636066913604736328125
]
},
"c": {
"value": 17.6991000000000013869794202037155628204345703125,
"test_run_times": [
44.4200000000000017053025658242404460906982421875
]
}
}
},
"fa0e1332a3568488061a24e2db603659f1c6501e": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/document_classification\/obert-base\/pytorch\/huggingface\/imdb\/base-none --scenario sync",
"description": "Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 56.6724999999999994315658113919198513031005859375,
"raw_values": [
56.727699999999998681232682429254055023193359375,
56.61160000000000280806489172391593456268310546875,
56.678100000000000591171556152403354644775390625
],
"test_run_times": [
44.50999999999999801048033987171947956085205078125,
44.43999999999999772626324556767940521240234375,
44.4200000000000017053025658242404460906982421875
]
},
"b": {
"value": 56.44239999999999923829818726517260074615478515625,
"test_run_times": [
44.38000000000000255795384873636066913604736328125
]
},
"c": {
"value": 56.49210000000000064801497501321136951446533203125,
"test_run_times": [
44.4200000000000017053025658242404460906982421875
]
}
}
},
"a5ba11a554d6383c4486b0661fdd16e9399e857f": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/sentiment_analysis\/oberta-base\/pytorch\/huggingface\/sst2\/pruned90_quant-none --input_shapes='[1,128]' --scenario async",
"description": "Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 672.3402999999999565261532552540302276611328125,
"raw_values": [
673.0892000000000052750692702829837799072265625,
672.4365999999999985448084771633148193359375,
671.4951999999999543433659709990024566650390625
],
"test_run_times": [
47.3599999999999994315658113919198513031005859375,
47.27000000000000312638803734444081783294677734375,
47.219999999999998863131622783839702606201171875
]
},
"b": {
"value": 669.957400000000006912159733474254608154296875,
"test_run_times": [
47.56000000000000227373675443232059478759765625
]
},
"c": {
"value": 672.718200000000024374458007514476776123046875,
"test_run_times": [
47.0799999999999982946974341757595539093017578125
]
}
}
},
"bda84ddf23206af7a77b4a03ef51ef2f11c11b45": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/sentiment_analysis\/oberta-base\/pytorch\/huggingface\/sst2\/pruned90_quant-none --input_shapes='[1,128]' --scenario async",
"description": "Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 23.772200000000001551825334900058805942535400390625,
"raw_values": [
23.746700000000000585487214266322553157806396484375,
23.76780000000000114823706098832190036773681640625,
23.802199999999999135980033315718173980712890625
],
"test_run_times": [
47.3599999999999994315658113919198513031005859375,
47.27000000000000312638803734444081783294677734375,
47.219999999999998863131622783839702606201171875
]
},
"b": {
"value": 23.856700000000000017053025658242404460906982421875,
"test_run_times": [
47.56000000000000227373675443232059478759765625
]
},
"c": {
"value": 23.759499999999999175770426518283784389495849609375,
"test_run_times": [
47.0799999999999982946974341757595539093017578125
]
}
}
},
"855ea67bb65a4f10b8a649ffcc43fbeb7227cae3": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/sentiment_analysis\/oberta-base\/pytorch\/huggingface\/sst2\/pruned90_quant-none --input_shapes='[1,128]' --scenario sync",
"description": "Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 168.529300000000006320988177321851253509521484375,
"raw_values": [
169.393900000000002137312549166381359100341796875,
167.607900000000000773070496506989002227783203125,
168.586000000000012732925824820995330810546875
],
"test_run_times": [
47.5799999999999982946974341757595539093017578125,
47.61999999999999744204615126363933086395263671875,
47.6099999999999994315658113919198513031005859375
]
},
"b": {
"value": 170.45539999999999736246536485850811004638671875,
"test_run_times": [
47.53999999999999914734871708787977695465087890625
]
},
"c": {
"value": 171.447499999999990905052982270717620849609375,
"test_run_times": [
47.47999999999999687361196265555918216705322265625
]
}
}
},
"5bbdba8bdb353a59e581a45b7f7943e3030de63a": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/sentiment_analysis\/oberta-base\/pytorch\/huggingface\/sst2\/pruned90_quant-none --input_shapes='[1,128]' --scenario sync",
"description": "Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Synchronous Single-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 5.9275000000000002131628207280300557613372802734375,
"raw_values": [
5.89679999999999981952214511693455278873443603515625,
5.95990000000000019753088054130785167217254638671875,
5.9259000000000003893774191965349018573760986328125
],
"test_run_times": [
47.5799999999999982946974341757595539093017578125,
47.61999999999999744204615126363933086395263671875,
47.6099999999999994315658113919198513031005859375
]
},
"b": {
"value": 5.861200000000000187583282240666449069976806640625,
"test_run_times": [
47.53999999999999914734871708787977695465087890625
]
},
"c": {
"value": 5.82720000000000037942982089589349925518035888671875,
"test_run_times": [
47.47999999999999687361196265555918216705322265625
]
}
}
},
"9b57be456e41aaad993f0ce7481a5c9c9a04a9ff": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/classification\/resnet_v1-50\/pytorch\/sparseml\/imagenet\/base-none --scenario async",
"description": "Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 320.600599999999985811882652342319488525390625,
"raw_values": [
321.61759999999998171915649436414241790771484375,
320.8962000000000216459739021956920623779296875,
319.28789999999997917257132939994335174560546875
],
"test_run_times": [
38.1400000000000005684341886080801486968994140625,
37.93999999999999772626324556767940521240234375,
38.030000000000001136868377216160297393798828125
]
},
"b": {
"value": 322.23250000000001591615728102624416351318359375,
"test_run_times": [
38.030000000000001136868377216160297393798828125
]
},
"c": {
"value": 324.370400000000017826096154749393463134765625,
"test_run_times": [
37.96000000000000085265128291212022304534912109375
]
}
}
},
"21a28bcec532bfa9a162a2718b6bd205c8afdb1e": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/classification\/resnet_v1-50\/pytorch\/sparseml\/imagenet\/base-none --scenario async",
"description": "Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 49.88380000000000080717654782347381114959716796875,
"raw_values": [
49.72540000000000048885340220294892787933349609375,
49.83760000000000189857018995098769664764404296875,
50.08840000000000003410605131648480892181396484375
],
"test_run_times": [
38.1400000000000005684341886080801486968994140625,
37.93999999999999772626324556767940521240234375,
38.030000000000001136868377216160297393798828125
]
},
"b": {
"value": 49.63029999999999830606611794792115688323974609375,
"test_run_times": [
38.030000000000001136868377216160297393798828125
]
},
"c": {
"value": 49.30380000000000251247911364771425724029541015625,
"test_run_times": [
37.96000000000000085265128291212022304534912109375
]
}
}
},
"1da2e9cb8d7a6eb8e64ede4d748a5c63dbec8559": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/classification\/resnet_v1-50\/pytorch\/sparseml\/imagenet\/base-none --scenario sync",
"description": "Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 143.449299999999993815436027944087982177734375,
"raw_values": [
144.22579999999999245119397528469562530517578125,
143.0919000000000096406438387930393218994140625,
143.03010000000000445652403868734836578369140625
],
"test_run_times": [
42.89999999999999857891452847979962825775146484375,
37.8599999999999994315658113919198513031005859375,
37.99000000000000198951966012828052043914794921875
]
},
"b": {
"value": 147.890099999999989677235134877264499664306640625,
"test_run_times": [
37.909999999999996589394868351519107818603515625
]
},
"c": {
"value": 148.1562999999999874489731155335903167724609375,
"test_run_times": [
37.8299999999999982946974341757595539093017578125
]
}
}
},
"02cfacf2ca4fbbb6b2413969891ed99032c6c05e": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/classification\/resnet_v1-50\/pytorch\/sparseml\/imagenet\/base-none --scenario sync",
"description": "Model: ResNet-50, Baseline - Scenario: Synchronous Single-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 6.963499999999999801048033987171947956085205078125,
"raw_values": [
6.9260000000000001563194018672220408916473388671875,
6.9808000000000003382183422218076884746551513671875,
6.98369999999999979678477757261134684085845947265625
],
"test_run_times": [
42.89999999999999857891452847979962825775146484375,
37.8599999999999994315658113919198513031005859375,
37.99000000000000198951966012828052043914794921875
]
},
"b": {
"value": 6.7538999999999997925215211580507457256317138671875,
"test_run_times": [
37.909999999999996589394868351519107818603515625
]
},
"c": {
"value": 6.7417999999999995708321876008994877338409423828125,
"test_run_times": [
37.8299999999999982946974341757595539093017578125
]
}
}
},
"4c16c458467e4713990cbf508dda0ad418740729": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/classification\/resnet_v1-50\/pytorch\/sparseml\/imagenet\/pruned95_uniform_quant-none --scenario async",
"description": "Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 1782.40270000000009531504474580287933349609375,
"raw_values": [
1820.5315000000000509317032992839813232421875,
1771.230499999999892679625190794467926025390625,
1755.446099999999887586454860866069793701171875
],
"test_run_times": [
38.1400000000000005684341886080801486968994140625,
38.13000000000000255795384873636066913604736328125,
38.14999999999999857891452847979962825775146484375
]
},
"b": {
"value": 1813.59470000000010259100235998630523681640625,
"test_run_times": [
38.1099999999999994315658113919198513031005859375
]
},
"c": {
"value": 1833.3638000000000829459168016910552978515625,
"test_run_times": [
38.10000000000000142108547152020037174224853515625
]
}
}
},
"893f2428b81e1c66c35110b1e39867b98d7ffa5b": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/classification\/resnet_v1-50\/pytorch\/sparseml\/imagenet\/pruned95_uniform_quant-none --scenario async",
"description": "Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 8.95139999999999957935870043002068996429443359375,
"raw_values": [
8.762299999999999755573298898525536060333251953125,
9.00339999999999918145476840436458587646484375,
9.0885999999999995679900166578590869903564453125
],
"test_run_times": [
38.1400000000000005684341886080801486968994140625,
38.13000000000000255795384873636066913604736328125,
38.14999999999999857891452847979962825775146484375
]
},
"b": {
"value": 8.797000000000000596855898038484156131744384765625,
"test_run_times": [
38.1099999999999994315658113919198513031005859375
]
},
"c": {
"value": 8.701299999999999812416717759333550930023193359375,
"test_run_times": [
38.10000000000000142108547152020037174224853515625
]
}
}
},
"3b395af9b9d076fb9bff8d47a249ec2fe8331f6e": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/classification\/resnet_v1-50\/pytorch\/sparseml\/imagenet\/pruned95_uniform_quant-none --scenario sync",
"description": "Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 754.327700000000049840309657156467437744140625,
"raw_values": [
755.2740000000000009094947017729282379150390625,
754.4198999999999841747921891510486602783203125,
753.289099999999962165020406246185302734375
],
"test_run_times": [
37.7999999999999971578290569595992565155029296875,
37.75,
37.75999999999999801048033987171947956085205078125
]
},
"b": {
"value": 748.3524999999999636202119290828704833984375,
"test_run_times": [
37.75999999999999801048033987171947956085205078125
]
},
"c": {
"value": 774.0575999999999794454197399318218231201171875,
"test_run_times": [
37.71000000000000085265128291212022304534912109375
]
}
}
},
"314827a2e497fa3e23a149d2aba87047cb19e7e3": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/classification\/resnet_v1-50\/pytorch\/sparseml\/imagenet\/pruned95_uniform_quant-none --scenario sync",
"description": "Model: ResNet-50, Sparse INT8 - Scenario: Synchronous Single-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 1.3211999999999999300115405276301316916942596435546875,
"raw_values": [
1.3192999999999999172217712839483283460140228271484375,
1.3211999999999999300115405276301316916942596435546875,
1.3231999999999999317878973670303821563720703125
],
"test_run_times": [
37.7999999999999971578290569595992565155029296875,
37.75,
37.75999999999999801048033987171947956085205078125
]
},
"b": {
"value": 1.331700000000000105870867628254927694797515869140625,
"test_run_times": [
37.75999999999999801048033987171947956085205078125
]
},
"c": {
"value": 1.287500000000000088817841970012523233890533447265625,
"test_run_times": [
37.71000000000000085265128291212022304534912109375
]
}
}
},
"20f489ce3ebeafb9d92bbb4838ca4c0390d3dd4d": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:llama2-7b-llama2_chat_llama2_pretrain-base_quantized --scenario async",
"description": "Model: Llama2 Chat 7b Quantized - Scenario: Asynchronous Multi-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 2.492199999999999970867747833835892379283905029296875,
"raw_values": [
2.51259999999999994457766661071218550205230712890625,
2.482299999999999950972551232553087174892425537109375,
2.481599999999999806021833137492649257183074951171875
],
"test_run_times": [
67.7900000000000062527760746888816356658935546875,
67.5499999999999971578290569595992565155029296875,
67.4800000000000039790393202565610408782958984375
]
},
"b": {
"value": 2.49549999999999982946974341757595539093017578125,
"test_run_times": [
67.4200000000000017053025658242404460906982421875
]
},
"c": {
"value": 2.49120000000000008100187187665142118930816650390625,
"test_run_times": [
67.3900000000000005684341886080801486968994140625
]
}
}
},
"d7626651777606a7730e9a1546ff6fd717d306f3": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:llama2-7b-llama2_chat_llama2_pretrain-base_quantized --scenario async",
"description": "Model: Llama2 Chat 7b Quantized - Scenario: Asynchronous Multi-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 5886.9548999999997249688021838665008544921875,
"raw_values": [
5842.6459000000004380126483738422393798828125,
5908.7897999999995590769685804843902587890625,
5909.4291000000002895831130445003509521484375
],
"test_run_times": [
67.7900000000000062527760746888816356658935546875,
67.5499999999999971578290569595992565155029296875,
67.4800000000000039790393202565610408782958984375
]
},
"b": {
"value": 5875.85180000000036670826375484466552734375,
"test_run_times": [
67.4200000000000017053025658242404460906982421875
]
},
"c": {
"value": 5888.2218999999995503458194434642791748046875,
"test_run_times": [
67.3900000000000005684341886080801486968994140625
]
}
}
},
"4ad67f37de90d07a80a48a47c3595fdb13a68be8": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:llama2-7b-llama2_chat_llama2_pretrain-base_quantized --scenario sync",
"description": "Model: Llama2 Chat 7b Quantized - Scenario: Synchronous Single-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 5.4551999999999996049382389173842966556549072265625,
"raw_values": [
5.4550999999999998379962562466971576213836669921875,
5.45699999999999985078602549037896096706390380859375,
5.4535999999999997811528373858891427516937255859375
],
"test_run_times": [
52.27000000000000312638803734444081783294677734375,
52.159999999999996589394868351519107818603515625,
52.38000000000000255795384873636066913604736328125
]
},
"b": {
"value": 5.4596000000000000085265128291212022304534912109375,
"test_run_times": [
52.3900000000000005684341886080801486968994140625
]
},
"c": {
"value": 5.45739999999999980673237587325274944305419921875,
"test_run_times": [
52.03999999999999914734871708787977695465087890625
]
}
}
},
"27ad8c70cf928aa19cccf637f113d2e489a4c94a": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:llama2-7b-llama2_chat_llama2_pretrain-base_quantized --scenario sync",
"description": "Model: Llama2 Chat 7b Quantized - Scenario: Synchronous Single-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 183.288099999999985811882652342319488525390625,
"raw_values": [
183.293800000000004501998773775994777679443359375,
183.228800000000006775735528208315372467041015625,
183.341800000000006320988177321851253509521484375
],
"test_run_times": [
52.27000000000000312638803734444081783294677734375,
52.159999999999996589394868351519107818603515625,
52.38000000000000255795384873636066913604736328125
]
},
"b": {
"value": 183.142599999999987403498380444943904876708984375,
"test_run_times": [
52.3900000000000005684341886080801486968994140625
]
},
"c": {
"value": 183.21399999999999863575794734060764312744140625,
"test_run_times": [
52.03999999999999914734871708787977695465087890625
]
}
}
},
"329837c092e993e81c947bb88e5010ebc9891b31": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/classification\/resnet_v1-50\/pytorch\/sparseml\/imagenet\/base-none --scenario async",
"description": "Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 321.29320000000001300577423535287380218505859375,
"raw_values": [
322.5507999999999810825102031230926513671875,
320.77929999999997789927874691784381866455078125,
320.54959999999999809006112627685070037841796875
],
"test_run_times": [
37.909999999999996589394868351519107818603515625,
37.969999999999998863131622783839702606201171875,
37.81000000000000227373675443232059478759765625
]
},
"b": {
"value": 322.04180000000002337401383556425571441650390625,
"test_run_times": [
37.86999999999999744204615126363933086395263671875
]
},
"c": {
"value": 323.607799999999997453414835035800933837890625,
"test_run_times": [
37.92999999999999971578290569595992565155029296875
]
}
}
},
"638213f946adb5ae9135ab4b8b446f7d58664d7f": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/classification\/resnet_v1-50\/pytorch\/sparseml\/imagenet\/base-none --scenario async",
"description": "Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 49.75630000000000308091330225579440593719482421875,
"raw_values": [
49.54650000000000176214598468504846096038818359375,
49.83149999999999835154085303656756877899169921875,
49.89099999999999823785401531495153903961181640625
],
"test_run_times": [
37.909999999999996589394868351519107818603515625,
37.969999999999998863131622783839702606201171875,
37.81000000000000227373675443232059478759765625
]
},
"b": {
"value": 49.66080000000000183035808731801807880401611328125,
"test_run_times": [
37.86999999999999744204615126363933086395263671875
]
},
"c": {
"value": 49.418599999999997862687450833618640899658203125,
"test_run_times": [
37.92999999999999971578290569595992565155029296875
]
}
}
},
"f23135dde731648112460c357dc2312eab3ce978": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/classification\/resnet_v1-50\/pytorch\/sparseml\/imagenet\/base-none --scenario sync",
"description": "Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 144.242400000000003501554601825773715972900390625,
"raw_values": [
143.628500000000002501110429875552654266357421875,
144.170400000000000773070496506989002227783203125,
144.92820000000000391082721762359142303466796875
],
"test_run_times": [
37.89999999999999857891452847979962825775146484375,
37.9500000000000028421709430404007434844970703125,
37.8299999999999982946974341757595539093017578125
]
},
"b": {
"value": 149.199800000000010413714335300028324127197265625,
"test_run_times": [
37.9200000000000017053025658242404460906982421875
]
},
"c": {
"value": 146.22989999999998644852894358336925506591796875,
"test_run_times": [
37.81000000000000227373675443232059478759765625
]
}
}
},
"948f96bcbf119b23cb418fb75b2bd04da31f599f": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/classification\/resnet_v1-50\/pytorch\/sparseml\/imagenet\/base-none --scenario sync",
"description": "Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 6.925399999999999778310666442848742008209228515625,
"raw_values": [
6.9550999999999998379962562466971576213836669921875,
6.92879999999999984794385454733856022357940673828125,
6.89219999999999988204990586382336914539337158203125
],
"test_run_times": [
37.89999999999999857891452847979962825775146484375,
37.9500000000000028421709430404007434844970703125,
37.8299999999999982946974341757595539093017578125
]
},
"b": {
"value": 6.695100000000000051159076974727213382720947265625,
"test_run_times": [
37.9200000000000017053025658242404460906982421875
]
},
"c": {
"value": 6.83070000000000021600499167107045650482177734375,
"test_run_times": [
37.81000000000000227373675443232059478759765625
]
}
}
},
"9f3ae2bc1f10bc938757c19ae97a957a6a9ee97a": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/detection\/yolov5-s\/pytorch\/ultralytics\/coco\/pruned85-none --scenario async",
"description": "Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 158.69540000000000645741238258779048919677734375,
"raw_values": [
160.1354000000000041836756281554698944091796875,
159.247800000000012232703738845884799957275390625,
156.70310000000000627551344223320484161376953125
],
"test_run_times": [
38.280000000000001136868377216160297393798828125,
38.3299999999999982946974341757595539093017578125,
38.35000000000000142108547152020037174224853515625
]
},
"b": {
"value": 158.49930000000000518411980010569095611572265625,
"test_run_times": [
38.159999999999996589394868351519107818603515625
]
},
"c": {
"value": 158.04230000000001155058271251618862152099609375,
"test_run_times": [
38.219999999999998863131622783839702606201171875
]
}
}
},
"7c1c5406d5fd0bc7f453370348b492b3d54aaa76": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/detection\/yolov5-s\/pytorch\/ultralytics\/coco\/pruned85-none --scenario async",
"description": "Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 100.685100000000005593392415903508663177490234375,
"raw_values": [
99.798900000000003274180926382541656494140625,
100.1855000000000046611603465862572193145751953125,
102.0708000000000055251803132705390453338623046875
],
"test_run_times": [
38.280000000000001136868377216160297393798828125,
38.3299999999999982946974341757595539093017578125,
38.35000000000000142108547152020037174224853515625
]
},
"b": {
"value": 100.9073000000000064346750150434672832489013671875,
"test_run_times": [
38.159999999999996589394868351519107818603515625
]
},
"c": {
"value": 101.1004999999999967030817060731351375579833984375,
"test_run_times": [
38.219999999999998863131622783839702606201171875
]
}
}
},
"b2a594486c92f0c4e4b93b0a9dbe5a0be062f298": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/detection\/yolov5-s\/pytorch\/ultralytics\/coco\/pruned85-none --scenario sync",
"description": "Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 93.010999999999995679900166578590869903564453125,
"raw_values": [
93.1941000000000059344529290683567523956298828125,
93.00839999999999463398125953972339630126953125,
92.83039999999999736246536485850811004638671875
],
"test_run_times": [
38.340000000000003410605131648480892181396484375,
38.61999999999999744204615126363933086395263671875,
38.409999999999996589394868351519107818603515625
]
},
"b": {
"value": 93.78919999999999390638549812138080596923828125,
"test_run_times": [
38.22999999999999687361196265555918216705322265625
]
},
"c": {
"value": 93.8712000000000017507773009128868579864501953125,
"test_run_times": [
38.1400000000000005684341886080801486968994140625
]
}
}
},
"a77140031a418d03f49e6debb4e03cbe7a03a678": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/detection\/yolov5-s\/pytorch\/ultralytics\/coco\/pruned85-none --scenario sync",
"description": "Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Synchronous Single-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 10.74419999999999930651028989814221858978271484375,
"raw_values": [
10.7232000000000002870592652470804750919342041015625,
10.7445000000000003836930773104541003704071044921875,
10.7650000000000005684341886080801486968994140625
],
"test_run_times": [
38.340000000000003410605131648480892181396484375,
38.61999999999999744204615126363933086395263671875,
38.409999999999996589394868351519107818603515625
]
},
"b": {
"value": 10.6547000000000000596855898038484156131744384765625,
"test_run_times": [
38.22999999999999687361196265555918216705322265625
]
},
"c": {
"value": 10.6460000000000007958078640513122081756591796875,
"test_run_times": [
38.1400000000000005684341886080801486968994140625
]
}
}
},
"4b08a77993201615e7cdd48a86e15cf72e9b3352": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/text_classification\/distilbert-none\/pytorch\/huggingface\/mnli\/base-none --scenario async",
"description": "Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 244.460100000000011277734301984310150146484375,
"raw_values": [
245.250300000000009958966984413564205169677734375,
244.284300000000001773514668457210063934326171875,
243.8455999999999903593561612069606781005859375
],
"test_run_times": [
39.89999999999999857891452847979962825775146484375,
39.8900000000000005684341886080801486968994140625,
39.85000000000000142108547152020037174224853515625
]
},
"b": {
"value": 245.345699999999993679011822678148746490478515625,
"test_run_times": [
39.85000000000000142108547152020037174224853515625
]
},
"c": {
"value": 245.96760000000000445652403868734836578369140625,
"test_run_times": [
39.8299999999999982946974341757595539093017578125
]
}
}
},
"7108c1bde12eb0d9c6ff634d37ff517773086268": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/text_classification\/distilbert-none\/pytorch\/huggingface\/mnli\/base-none --scenario async",
"description": "Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 65.4072000000000031150193535722792148590087890625,
"raw_values": [
65.185100000000005593392415903508663177490234375,
65.4680000000000035242919693700969219207763671875,
65.56860000000000354702933691442012786865234375
],
"test_run_times": [
39.89999999999999857891452847979962825775146484375,
39.8900000000000005684341886080801486968994140625,
39.85000000000000142108547152020037174224853515625
]
},
"b": {
"value": 65.1818999999999988403942552395164966583251953125,
"test_run_times": [
39.85000000000000142108547152020037174224853515625
]
},
"c": {
"value": 65.021199999999993224264471791684627532958984375,
"test_run_times": [
39.8299999999999982946974341757595539093017578125
]
}
}
},
"ec149e1403247f5016fb1f96ce6614000e37c266": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/text_classification\/distilbert-none\/pytorch\/huggingface\/mnli\/base-none --scenario sync",
"description": "Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 81.1471999999999979991116560995578765869140625,
"raw_values": [
80.6260999999999938836481305770576000213623046875,
81.2257000000000033423930290155112743377685546875,
81.58969999999999345163814723491668701171875
],
"test_run_times": [
39.81000000000000227373675443232059478759765625,
39.7000000000000028421709430404007434844970703125,
39.78999999999999914734871708787977695465087890625
]
},
"b": {
"value": 84.454599999999999226929503493010997772216796875,
"test_run_times": [
39.659999999999996589394868351519107818603515625
]
},
"c": {
"value": 85.6979999999999932924765744246542453765869140625,
"test_run_times": [
39.74000000000000198951966012828052043914794921875
]
}
}
},
"1968a2c97ff6ff373d30fe5697bcd3ea3912ae50": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/text_classification\/distilbert-none\/pytorch\/huggingface\/mnli\/base-none --scenario sync",
"description": "Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 12.31680000000000063664629124104976654052734375,
"raw_values": [
12.3960000000000007958078640513122081756591796875,
12.30499999999999971578290569595992565155029296875,
12.2493999999999996219912645756267011165618896484375
],
"test_run_times": [
39.81000000000000227373675443232059478759765625,
39.7000000000000028421709430404007434844970703125,
39.78999999999999914734871708787977695465087890625
]
},
"b": {
"value": 11.833800000000000096633812063373625278472900390625,
"test_run_times": [
39.659999999999996589394868351519107818603515625
]
},
"c": {
"value": 11.6624999999999996447286321199499070644378662109375,
"test_run_times": [
39.74000000000000198951966012828052043914794921875
]
}
}
},
"029547d9862776523c5601395a6358610a352681": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/segmentation\/yolact-darknet53\/pytorch\/dbolya\/coco\/pruned90-none --scenario async",
"description": "Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 33.1638999999999981582732289098203182220458984375,
"raw_values": [
33.45779999999999887450030655600130558013916015625,
33.124899999999996680344338528811931610107421875,
32.9089000000000027057467377744615077972412109375
],
"test_run_times": [
41.67999999999999971578290569595992565155029296875,
41.92999999999999971578290569595992565155029296875,
41.9500000000000028421709430404007434844970703125
]
},
"b": {
"value": 33.45450000000000301270119962282478809356689453125,
"test_run_times": [
42.0499999999999971578290569595992565155029296875
]
},
"c": {
"value": 33.32939999999999969304553815163671970367431640625,
"test_run_times": [
41.909999999999996589394868351519107818603515625
]
}
}
},
"a6893edb09ab37f3c2a30cc382eee443bef51652": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/segmentation\/yolact-darknet53\/pytorch\/dbolya\/coco\/pruned90-none --scenario async",
"description": "Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 481.30910000000000081854523159563541412353515625,
"raw_values": [
477.6001999999999725332600064575672149658203125,
481.21980000000002064552973024547100067138671875,
485.10719999999997753548086620867252349853515625
],
"test_run_times": [
41.67999999999999971578290569595992565155029296875,
41.92999999999999971578290569595992565155029296875,
41.9500000000000028421709430404007434844970703125
]
},
"b": {
"value": 477.02600000000001045918907038867473602294921875,
"test_run_times": [
42.0499999999999971578290569595992565155029296875
]
},
"c": {
"value": 479.28890000000001236912794411182403564453125,
"test_run_times": [
41.909999999999996589394868351519107818603515625
]
}
}
},
"2e09524a2afac98ccf359361f18a9bf744359ec7": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/segmentation\/yolact-darknet53\/pytorch\/dbolya\/coco\/pruned90-none --scenario sync",
"description": "Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 21.126400000000000289901436190120875835418701171875,
"raw_values": [
21.11489999999999866986399865709245204925537109375,
21.10439999999999827196006663143634796142578125,
21.15990000000000037516656448133289813995361328125
],
"test_run_times": [
41.38000000000000255795384873636066913604736328125,
41.3599999999999994315658113919198513031005859375,
46.32000000000000028421709430404007434844970703125
]
},
"b": {
"value": 21.43410000000000081854523159563541412353515625,
"test_run_times": [
41.219999999999998863131622783839702606201171875
]
},
"c": {
"value": 21.420500000000000540012479177676141262054443359375,
"test_run_times": [
41.21000000000000085265128291212022304534912109375
]
}
}
},
"4c1cc90e3ea0d3504b4076fbf87308d1ee648506": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:cv\/segmentation\/yolact-darknet53\/pytorch\/dbolya\/coco\/pruned90-none --scenario sync",
"description": "Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Synchronous Single-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 47.3192999999999983629095368087291717529296875,
"raw_values": [
47.34559999999999746478351880796253681182861328125,
47.36829999999999785131876706145703792572021484375,
47.2441000000000030922819860279560089111328125
],
"test_run_times": [
41.38000000000000255795384873636066913604736328125,
41.3599999999999994315658113919198513031005859375,
46.32000000000000028421709430404007434844970703125
]
},
"b": {
"value": 46.6398999999999972487785271368920803070068359375,
"test_run_times": [
41.219999999999998863131622783839702606201171875
]
},
"c": {
"value": 46.67020000000000123918653116561472415924072265625,
"test_run_times": [
41.21000000000000085265128291212022304534912109375
]
}
}
},
"83ca1e360507a59226001525682d066a1eee5e84": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/question_answering\/obert-large\/pytorch\/huggingface\/squad\/pruned97_quant-none --input_shapes='[1,128]' --scenario async",
"description": "Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 344.2857000000000198269844986498355865478515625,
"raw_values": [
344.603299999999990177457220852375030517578125,
344.16960000000000263753463514149188995361328125,
344.084200000000009822542779147624969482421875
],
"test_run_times": [
45.49000000000000198951966012828052043914794921875,
45.4200000000000017053025658242404460906982421875,
45.31000000000000227373675443232059478759765625
]
},
"b": {
"value": 344.92270000000002028173184953629970550537109375,
"test_run_times": [
45.4200000000000017053025658242404460906982421875
]
},
"c": {
"value": 344.66030000000000654836185276508331298828125,
"test_run_times": [
45.3900000000000005684341886080801486968994140625
]
}
}
},
"356fd68833e3222975779732b39790139f819b22": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/question_answering\/obert-large\/pytorch\/huggingface\/squad\/pruned97_quant-none --input_shapes='[1,128]' --scenario async",
"description": "Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 46.41689999999999827196006663143634796142578125,
"raw_values": [
46.380099999999998772182152606546878814697265625,
46.4275999999999982037479639984667301177978515625,
46.4431000000000011596057447604835033416748046875
],
"test_run_times": [
45.49000000000000198951966012828052043914794921875,
45.4200000000000017053025658242404460906982421875,
45.31000000000000227373675443232059478759765625
]
},
"b": {
"value": 46.3528000000000020008883439004421234130859375,
"test_run_times": [
45.4200000000000017053025658242404460906982421875
]
},
"c": {
"value": 46.364699999999999135980033315718173980712890625,
"test_run_times": [
45.3900000000000005684341886080801486968994140625
]
}
}
},
"56185e1b61cd8aa824fb78f1d7d102710de33b94": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/question_answering\/obert-large\/pytorch\/huggingface\/squad\/pruned97_quant-none --input_shapes='[1,128]' --scenario sync",
"description": "Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 86.390500000000002955857780762016773223876953125,
"raw_values": [
86.095699999999993679011822678148746490478515625,
86.3134000000000014551915228366851806640625,
86.7623999999999995225152815692126750946044921875
],
"test_run_times": [
77.4800000000000039790393202565610408782958984375,
77.150000000000005684341886080801486968994140625,
82.18999999999999772626324556767940521240234375
]
},
"b": {
"value": 86.50360000000000582076609134674072265625,
"test_run_times": [
77.43999999999999772626324556767940521240234375
]
},
"c": {
"value": 85.99660000000000081854523159563541412353515625,
"test_run_times": [
77.4800000000000039790393202565610408782958984375
]
}
}
},
"d4b9f05f0f69b018a9d07117bd621c6a7f7953e4": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/question_answering\/obert-large\/pytorch\/huggingface\/squad\/pruned97_quant-none --input_shapes='[1,128]' --scenario sync",
"description": "Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Synchronous Single-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 11.568799999999999528199623455293476581573486328125,
"raw_values": [
11.608000000000000540012479177676141262054443359375,
11.579599999999999226929503493010997772216796875,
11.5188000000000005940137270954437553882598876953125
],
"test_run_times": [
77.4800000000000039790393202565610408782958984375,
77.150000000000005684341886080801486968994140625,
82.18999999999999772626324556767940521240234375
]
},
"b": {
"value": 11.553200000000000358113538823090493679046630859375,
"test_run_times": [
77.43999999999999772626324556767940521240234375
]
},
"c": {
"value": 11.6213999999999995083044268540106713771820068359375,
"test_run_times": [
77.4800000000000039790393202565610408782958984375
]
}
}
},
"93d0edcc5ea127a7ae76411e7c930bccd559b10d": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/token_classification\/bert-base\/pytorch\/huggingface\/conll2003\/base-none --scenario async",
"description": "Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 30.074000000000001620037437533028423786163330078125,
"raw_values": [
30.4318999999999988403942552395164966583251953125,
30.131099999999999994315658113919198513031005859375,
29.659099999999998686917024315334856510162353515625
],
"test_run_times": [
44.85000000000000142108547152020037174224853515625,
44.3900000000000005684341886080801486968994140625,
44.46000000000000085265128291212022304534912109375
]
},
"b": {
"value": 30.2195999999999997953636921010911464691162109375,
"test_run_times": [
44.36999999999999744204615126363933086395263671875
]
},
"c": {
"value": 30.074200000000001153921402874402701854705810546875,
"test_run_times": [
49.60000000000000142108547152020037174224853515625
]
}
}
},
"1ef7bb431fa28fd7b9e986fd0cb9552c75643fd9": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/token_classification\/bert-base\/pytorch\/huggingface\/conll2003\/base-none --scenario async",
"description": "Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 529.0850000000000363797880709171295166015625,
"raw_values": [
523.959399999999959618435241281986236572265625,
527.5394000000000005456968210637569427490234375,
535.7563000000000101863406598567962646484375
],
"test_run_times": [
44.85000000000000142108547152020037174224853515625,
44.3900000000000005684341886080801486968994140625,
44.46000000000000085265128291212022304534912109375
]
},
"b": {
"value": 525.919599999999945794115774333477020263671875,
"test_run_times": [
44.36999999999999744204615126363933086395263671875
]
},
"c": {
"value": 530.651200000000017098500393331050872802734375,
"test_run_times": [
49.60000000000000142108547152020037174224853515625
]
}
}
},
"8810fe9271cfde46003041442cc253185eb44e1c": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/token_classification\/bert-base\/pytorch\/huggingface\/conll2003\/base-none --scenario sync",
"description": "Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream",
"scale": "items\/sec",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 17.626999999999998891553332214243710041046142578125,
"raw_values": [
17.515100000000000335376171278767287731170654296875,
17.717600000000000903810359886847436428070068359375,
17.648399999999998755129126948304474353790283203125
],
"test_run_times": [
44.35000000000000142108547152020037174224853515625,
44.25,
44.27000000000000312638803734444081783294677734375
]
},
"b": {
"value": 17.6287999999999982492226990871131420135498046875,
"test_run_times": [
44.159999999999996589394868351519107818603515625
]
},
"c": {
"value": 17.54129999999999967030817060731351375579833984375,
"test_run_times": [
44.1099999999999994315658113919198513031005859375
]
}
}
},
"78aa5fcf7f9028bdaf1287fd59d1b0d907e4aca2": {
"identifier": "pts\/deepsparse-1.7.0",
"title": "Neural Magic DeepSparse",
"app_version": "1.7",
"arguments": "zoo:nlp\/token_classification\/bert-base\/pytorch\/huggingface\/conll2003\/base-none --scenario sync",
"description": "Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream",
"scale": "ms\/batch",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 56.72460000000000235331754083745181560516357421875,
"raw_values": [
57.0861000000000018417267710901796817779541015625,
56.43310000000000314912540488876402378082275390625,
56.65469999999999828332875040359795093536376953125
],
"test_run_times": [
44.35000000000000142108547152020037174224853515625,
44.25,
44.27000000000000312638803734444081783294677734375
]
},
"b": {
"value": 56.7171000000000020691004465334117412567138671875,
"test_run_times": [
44.159999999999996589394868351519107818603515625
]
},
"c": {
"value": 57.00019999999999953388396534137427806854248046875,
"test_run_times": [
44.1099999999999994315658113919198513031005859375
]
}
}
},
"f6124ad8f9966a9fca6124ac8f3ce8e74420f735": {
"identifier": "pts\/draco-1.6.1",
"title": "Google Draco",
"app_version": "1.5.6",
"arguments": "-i lion.ply",
"description": "Model: Lion",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 5258,
"raw_values": [
5271,
5243,
5261
],
"test_run_times": [
7.0099999999999997868371792719699442386627197265625,
6.95000000000000017763568394002504646778106689453125,
6.95999999999999996447286321199499070644378662109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"b": {
"value": 5275,
"test_run_times": [
7.019999999999999573674358543939888477325439453125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"c": {
"value": 5199,
"test_run_times": [
6.95000000000000017763568394002504646778106689453125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
}
}
},
"c2182c1656777f7fc05206b18918c42e97f0d45b": {
"identifier": "pts\/draco-1.6.1",
"title": "Google Draco",
"app_version": "1.5.6",
"arguments": "-i church.ply",
"description": "Model: Church Facade",
"scale": "ms",
"proportion": "LIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 7989,
"raw_values": [
7964,
7969,
8034
],
"test_run_times": [
9.67999999999999971578290569595992565155029296875,
9.6400000000000005684341886080801486968994140625,
9.71000000000000085265128291212022304534912109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"b": {
"value": 8191,
"test_run_times": [
9.9199999999999999289457264239899814128875732421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"c": {
"value": 8165,
"test_run_times": [
9.92999999999999971578290569595992565155029296875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
}
}
}
}
}