2 x INTEL XEON PLATINUM 8592+ testing with a Quanta Cloud QuantaGrid D54Q-2U S6Q-MB-MPS (3B05.TEL4P1 BIOS) and ASPEED on Ubuntu 23.10 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 2403172-NE-XEONEMR4990
{
"title": "xeon emr",
"last_modified": "2024-03-17 21:29:53",
"description": "2 x INTEL XEON PLATINUM 8592+ testing with a Quanta Cloud QuantaGrid D54Q-2U S6Q-MB-MPS (3B05.TEL4P1 BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite.",
"systems": {
"a": {
"identifier": "a",
"hardware": {
"Processor": "2 x INTEL XEON PLATINUM 8592+ @ 3.90GHz (128 Cores \/ 256 Threads)",
"Motherboard": "Quanta Cloud QuantaGrid D54Q-2U S6Q-MB-MPS (3B05.TEL4P1 BIOS)",
"Chipset": "Intel Device 1bce",
"Memory": "1008GB",
"Disk": "3201GB Micron_7450_MTFDKCC3T2TFS",
"Graphics": "ASPEED",
"Network": "2 x Intel X710 for 10GBASE-T"
},
"software": {
"OS": "Ubuntu 23.10",
"Kernel": "6.6.0-rc5-phx-patched (x86_64)",
"Desktop": "GNOME Shell 45.0",
"Display Server": "X Server 1.21.1.7",
"Compiler": "GCC 13.2.0",
"File-System": "ext4",
"Screen Resolution": "1920x1200"
},
"user": "phoronix",
"timestamp": "2024-03-17 17:32:44",
"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,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-defaulted --enable-offload-targets=nvptx-none=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/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": "intel_pstate performance (EPP: performance)",
"cpu-microcode": "0x21000161",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.11.6",
"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: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced \/ Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected"
}
},
"b": {
"identifier": "b",
"hardware": {
"Processor": "2 x INTEL XEON PLATINUM 8592+ @ 3.90GHz (128 Cores \/ 256 Threads)",
"Motherboard": "Quanta Cloud QuantaGrid D54Q-2U S6Q-MB-MPS (3B05.TEL4P1 BIOS)",
"Chipset": "Intel Device 1bce",
"Memory": "1008GB",
"Disk": "3201GB Micron_7450_MTFDKCC3T2TFS",
"Graphics": "ASPEED",
"Network": "2 x Intel X710 for 10GBASE-T"
},
"software": {
"OS": "Ubuntu 23.10",
"Kernel": "6.6.0-rc5-phx-patched (x86_64)",
"Desktop": "GNOME Shell 45.0",
"Display Server": "X Server 1.21.1.7",
"Compiler": "GCC 13.2.0",
"File-System": "ext4",
"Screen Resolution": "1920x1200"
},
"user": "phoronix",
"timestamp": "2024-03-17 19:20:25",
"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,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-defaulted --enable-offload-targets=nvptx-none=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/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": "intel_pstate performance (EPP: performance)",
"cpu-microcode": "0x21000161",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.11.6",
"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: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced \/ Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected"
}
},
"c": {
"identifier": "c",
"hardware": {
"Processor": "2 x INTEL XEON PLATINUM 8592+ @ 3.90GHz (128 Cores \/ 256 Threads)",
"Motherboard": "Quanta Cloud QuantaGrid D54Q-2U S6Q-MB-MPS (3B05.TEL4P1 BIOS)",
"Chipset": "Intel Device 1bce",
"Memory": "1008GB",
"Disk": "3201GB Micron_7450_MTFDKCC3T2TFS",
"Graphics": "ASPEED",
"Network": "2 x Intel X710 for 10GBASE-T"
},
"software": {
"OS": "Ubuntu 23.10",
"Kernel": "6.6.0-rc5-phx-patched (x86_64)",
"Desktop": "GNOME Shell 45.0",
"Display Server": "X Server 1.21.1.7",
"Compiler": "GCC 13.2.0",
"File-System": "ext4",
"Screen Resolution": "1920x1200"
},
"user": "phoronix",
"timestamp": "2024-03-17 20:26:22",
"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,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-defaulted --enable-offload-targets=nvptx-none=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/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": "intel_pstate performance (EPP: performance)",
"cpu-microcode": "0x21000161",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.11.6",
"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: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced \/ Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + srbds: Not affected + tsx_async_abort: Not affected"
}
},
"d": {
"identifier": "d",
"hardware": {
"Processor": "2 x INTEL XEON PLATINUM 8592+ @ 3.90GHz (128 Cores \/ 256 Threads)",
"Motherboard": "Quanta Cloud QuantaGrid D54Q-2U S6Q-MB-MPS (3B05.TEL4P1 BIOS)",
"Chipset": "Intel Device 1bce",
"Memory": "1008GB",
"Disk": "3201GB Micron_7450_MTFDKCC3T2TFS",
"Graphics": "ASPEED",
"Network": "2 x Intel X710 for 10GBASE-T"
},
"software": {
"OS": "Ubuntu 23.10",
"Kernel": "6.6.0-rc5-phx-patched (x86_64)",
"Desktop": "GNOME Shell 45.0",
"Display Server": "X Server 1.21.1.7",
"Compiler": "GCC 13.2.0",
"File-System": "ext4",
"Screen Resolution": "1920x1200"
},
"user": "phoronix",
"timestamp": "2024-03-17 20:58:03",
"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,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-defaulted --enable-offload-targets=nvptx-none=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/debian\/tmp-nvptx\/usr,amdgcn-amdhsa=\/build\/gcc-13-XYspKM\/gcc-13-13.2.0\/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": "intel_pstate performance (EPP: performance)",
"cpu-microcode": "0x21000161",
"kernel-extra-details": "Transparent Huge Pages: madvise",
"python": "Python 3.11.6",
"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: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy\/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Enhanced \/ Automatic IBRS IBPB: conditional RSB filling PBRSB-eIBRS: SW sequence + 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": 43297.4000000000014551915228366851806640625,
"test_run_times": [
12.2200000000000006394884621840901672840118408203125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -mavx512f -mavx512cd -mavx512bw -mavx512dq -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
},
"b": {
"value": 50572.0999999999985448084771633148193359375,
"test_run_times": [
12.1199999999999992184029906638897955417633056640625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -mavx512f -mavx512cd -mavx512bw -mavx512dq -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
},
"c": {
"value": 52220.4000000000014551915228366851806640625,
"test_run_times": [
12.089999999999999857891452847979962825775146484375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -mavx512f -mavx512cd -mavx512bw -mavx512dq -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
},
"d": {
"value": 49150.300000000002910383045673370361328125,
"test_run_times": [
12.1300000000000007815970093361102044582366943359375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -mavx512f -mavx512cd -mavx512bw -mavx512dq -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
}
}
},
"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": 3.102799999999999780442294650129042565822601318359375,
"test_run_times": [
99.2099999999999937472239253111183643341064453125
]
},
"b": {
"value": 2.96760000000000001563194018672220408916473388671875,
"test_run_times": [
100.849999999999994315658113919198513031005859375
]
},
"c": {
"value": 2.950600000000000111555209514335729181766510009765625,
"test_run_times": [
96.3900000000000005684341886080801486968994140625
]
},
"d": {
"value": 3.213699999999999779021209178608842194080352783203125,
"test_run_times": [
98.2600000000000051159076974727213382720947265625
]
}
}
},
"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": 16509.138200000001234002411365509033203125,
"test_run_times": [
99.2099999999999937472239253111183643341064453125
]
},
"b": {
"value": 17153.22569999999905121512711048126220703125,
"test_run_times": [
100.849999999999994315658113919198513031005859375
]
},
"c": {
"value": 17224.35840000000098370946943759918212890625,
"test_run_times": [
96.3900000000000005684341886080801486968994140625
]
},
"d": {
"value": 16021.351000000000567524693906307220458984375,
"test_run_times": [
98.2600000000000051159076974727213382720947265625
]
}
}
},
"f7bde6e6bd4dbb60d5b8b62e4dcb0d37bdd03163": {
"identifier": "pts\/stockfish-1.5.0",
"title": "Stockfish",
"app_version": "16.1",
"description": "Chess Benchmark",
"scale": "Nodes Per Second",
"proportion": "HIB",
"display_format": "BAR_GRAPH",
"results": {
"a": {
"value": 212133268,
"test_run_times": [
89.4800000000000039790393202565610408782958984375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-lgcov -m64 -lpthread -fno-exceptions -std=c++17 -fno-peel-loops -fno-tracer -pedantic -O3 -funroll-loops -msse -msse3 -mpopcnt -mavx2 -mbmi -mavx512f -mavx512bw -mavx512vnni -mavx512dq -mavx512vl -msse4.1 -mssse3 -msse2 -mbmi2 -flto -flto-partition=one -flto=jobserver"
}
}
},
"b": {
"value": 207635904,
"test_run_times": [
108.06999999999999317878973670303821563720703125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-lgcov -m64 -lpthread -fno-exceptions -std=c++17 -fno-peel-loops -fno-tracer -pedantic -O3 -funroll-loops -msse -msse3 -mpopcnt -mavx2 -mbmi -mavx512f -mavx512bw -mavx512vnni -mavx512dq -mavx512vl -msse4.1 -mssse3 -msse2 -mbmi2 -flto -flto-partition=one -flto=jobserver"
}
}
},
"c": {
"value": 221316167,
"test_run_times": [
113.68999999999999772626324556767940521240234375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-lgcov -m64 -lpthread -fno-exceptions -std=c++17 -fno-peel-loops -fno-tracer -pedantic -O3 -funroll-loops -msse -msse3 -mpopcnt -mavx2 -mbmi -mavx512f -mavx512bw -mavx512vnni -mavx512dq -mavx512vl -msse4.1 -mssse3 -msse2 -mbmi2 -flto -flto-partition=one -flto=jobserver"
}
}
},
"d": {
"value": 214224198,
"test_run_times": [
136.25
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-lgcov -m64 -lpthread -fno-exceptions -std=c++17 -fno-peel-loops -fno-tracer -pedantic -O3 -funroll-loops -msse -msse3 -mpopcnt -mavx2 -mbmi -mavx512f -mavx512bw -mavx512vnni -mavx512dq -mavx512vl -msse4.1 -mssse3 -msse2 -mbmi2 -flto -flto-partition=one -flto=jobserver"
}
}
}
}
},
"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": 457.740999999999985448084771633148193359375,
"test_run_times": [
1.979999999999999982236431605997495353221893310546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 439.1190000000000281943357549607753753662109375,
"test_run_times": [
2.020000000000000017763568394002504646778106689453125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 441.4189999999999827196006663143634796142578125,
"test_run_times": [
2.04000000000000003552713678800500929355621337890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"d": {
"value": 442.336000000000012732925824820995330810546875,
"test_run_times": [
2
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"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": 755.6000000000000227373675443232059478759765625,
"test_run_times": [
3.95000000000000017763568394002504646778106689453125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -mavx512f -mavx512cd -mavx512bw -mavx512dq -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
},
"b": {
"value": 728.700000000000045474735088646411895751953125,
"test_run_times": [
3.850000000000000088817841970012523233890533447265625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -mavx512f -mavx512cd -mavx512bw -mavx512dq -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
},
"c": {
"value": 755.299999999999954525264911353588104248046875,
"test_run_times": [
3.899999999999999911182158029987476766109466552734375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -mavx512f -mavx512cd -mavx512bw -mavx512dq -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
},
"d": {
"value": 756,
"test_run_times": [
3.95000000000000017763568394002504646778106689453125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mavx2 -mavx -msse4.1 -mfma -mavx512f -mavx512cd -mavx512bw -mavx512dq -O3 -fno-trapping-math -fno-math-errno -ldl"
}
}
}
}
},
"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": 643.5249999999999772626324556767940521240234375,
"test_run_times": [
1.5700000000000000621724893790087662637233734130859375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 640.892000000000052750692702829837799072265625,
"test_run_times": [
1.5500000000000000444089209850062616169452667236328125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 620.865000000000009094947017729282379150390625,
"test_run_times": [
1.600000000000000088817841970012523233890533447265625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"d": {
"value": 627.5900000000000318323145620524883270263671875,
"test_run_times": [
1.5800000000000000710542735760100185871124267578125
],
"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": 72.8599999999999994315658113919198513031005859375,
"test_run_times": [
11.7400000000000002131628207280300557613372802734375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 73.712999999999993860910763032734394073486328125,
"test_run_times": [
11.7599999999999997868371792719699442386627197265625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 72.826999999999998181010596454143524169921875,
"test_run_times": [
11.0099999999999997868371792719699442386627197265625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"d": {
"value": 71.510999999999995679900166578590869903564453125,
"test_run_times": [
11.5
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"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": 7.75,
"test_run_times": [
23.719999999999998863131622783839702606201171875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 7.53099999999999969446662362315692007541656494140625,
"test_run_times": [
26.030000000000001136868377216160297393798828125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 7.541000000000000369482222595252096652984619140625,
"test_run_times": [
25.8299999999999982946974341757595539093017578125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"d": {
"value": 7.5860000000000002984279490192420780658721923828125,
"test_run_times": [
25.8900000000000005684341886080801486968994140625
],
"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": 172.717999999999989313437254168093204498291015625,
"test_run_times": [
5.480000000000000426325641456060111522674560546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 168.298000000000001818989403545856475830078125,
"test_run_times": [
5.730000000000000426325641456060111522674560546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 169.909999999999996589394868351519107818603515625,
"test_run_times": [
5.62999999999999989341858963598497211933135986328125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"d": {
"value": 169.38700000000000045474735088646411895751953125,
"test_run_times": [
5.44000000000000039079850466805510222911834716796875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"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": 2.21300000000000007815970093361102044582366943359375,
"test_run_times": [
2.229999999999999982236431605997495353221893310546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"b": {
"value": 2.162999999999999811706175023573450744152069091796875,
"test_run_times": [
2.180000000000000159872115546022541821002960205078125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"c": {
"value": 2.15899999999999980815346134477294981479644775390625,
"test_run_times": [
2.1699999999999999289457264239899814128875732421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"d": {
"value": 2.162999999999999811706175023573450744152069091796875,
"test_run_times": [
2.180000000000000159872115546022541821002960205078125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
}
}
},
"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": 0.93940000000000001278976924368180334568023681640625,
"test_run_times": [
37.7000000000000028421709430404007434844970703125
]
},
"b": {
"value": 0.923200000000000020605739337042905390262603759765625,
"test_run_times": [
37.56000000000000227373675443232059478759765625
]
},
"c": {
"value": 0.93559999999999998721023075631819665431976318359375,
"test_run_times": [
37.46000000000000085265128291212022304534912109375
]
},
"d": {
"value": 0.94489999999999996216359932077466510236263275146484375,
"test_run_times": [
37.52000000000000312638803734444081783294677734375
]
}
}
},
"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": 1060.952199999999947976903058588504791259765625,
"test_run_times": [
37.7000000000000028421709430404007434844970703125
]
},
"b": {
"value": 1079.5718999999999141437001526355743408203125,
"test_run_times": [
37.56000000000000227373675443232059478759765625
]
},
"c": {
"value": 1065.96649999999999636202119290828704833984375,
"test_run_times": [
37.46000000000000085265128291212022304534912109375
]
},
"d": {
"value": 1055.182199999999966166797094047069549560546875,
"test_run_times": [
37.52000000000000312638803734444081783294677734375
]
}
}
},
"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": 9.9739000000000004320099833421409130096435546875,
"test_run_times": [
43.3299999999999982946974341757595539093017578125
]
},
"b": {
"value": 10.0233000000000007645439836778677999973297119140625,
"test_run_times": [
43.3900000000000005684341886080801486968994140625
]
},
"c": {
"value": 9.899699999999999278088580467738211154937744140625,
"test_run_times": [
43.7999999999999971578290569595992565155029296875
]
},
"d": {
"value": 10.12160000000000081854523159563541412353515625,
"test_run_times": [
43.53999999999999914734871708787977695465087890625
]
}
}
},
"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": 100.2083999999999974761522025801241397857666015625,
"test_run_times": [
43.3299999999999982946974341757595539093017578125
]
},
"b": {
"value": 99.709599999999994679455994628369808197021484375,
"test_run_times": [
43.3900000000000005684341886080801486968994140625
]
},
"c": {
"value": 100.95359999999999445208231918513774871826171875,
"test_run_times": [
43.7999999999999971578290569595992565155029296875
]
},
"d": {
"value": 98.746700000000004138200893066823482513427734375,
"test_run_times": [
43.53999999999999914734871708787977695465087890625
]
}
}
},
"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": 35.8292000000000001591615728102624416351318359375,
"test_run_times": [
40
]
},
"b": {
"value": 35.8509999999999990905052982270717620849609375,
"test_run_times": [
39.97999999999999687361196265555918216705322265625
]
},
"c": {
"value": 35.1942999999999983629095368087291717529296875,
"test_run_times": [
39.85000000000000142108547152020037174224853515625
]
},
"d": {
"value": 35.765399999999999636202119290828704833984375,
"test_run_times": [
39.93999999999999772626324556767940521240234375
]
}
}
},
"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": 27.8836000000000012732925824820995330810546875,
"test_run_times": [
40
]
},
"b": {
"value": 27.86659999999999826059138285927474498748779296875,
"test_run_times": [
39.97999999999999687361196265555918216705322265625
]
},
"c": {
"value": 28.385200000000001097077984013594686985015869140625,
"test_run_times": [
39.85000000000000142108547152020037174224853515625
]
},
"d": {
"value": 27.93090000000000117097442853264510631561279296875,
"test_run_times": [
39.93999999999999772626324556767940521240234375
]
}
}
},
"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": 22.0330000000000012505552149377763271331787109375,
"test_run_times": [
9.1300000000000007815970093361102044582366943359375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 22.16100000000000136424205265939235687255859375,
"test_run_times": [
10.0999999999999996447286321199499070644378662109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 22.391999999999999459987520822323858737945556640625,
"test_run_times": [
9.480000000000000426325641456060111522674560546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"d": {
"value": 22.239999999999998436805981327779591083526611328125,
"test_run_times": [
9.9199999999999999289457264239899814128875732421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"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": 68.8873999999999995225152815692126750946044921875,
"test_run_times": [
45.60000000000000142108547152020037174224853515625
]
},
"b": {
"value": 69.8790999999999939973349682986736297607421875,
"test_run_times": [
45.52000000000000312638803734444081783294677734375
]
},
"c": {
"value": 69.6415999999999968395059113390743732452392578125,
"test_run_times": [
45.7000000000000028421709430404007434844970703125
]
},
"d": {
"value": 69.94499999999999317878973670303821563720703125,
"test_run_times": [
45.64999999999999857891452847979962825775146484375
]
}
}
},
"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": 14.500099999999999766941982670687139034271240234375,
"test_run_times": [
45.60000000000000142108547152020037174224853515625
]
},
"b": {
"value": 14.2936999999999994059862729045562446117401123046875,
"test_run_times": [
45.52000000000000312638803734444081783294677734375
]
},
"c": {
"value": 14.3407999999999997697841536137275397777557373046875,
"test_run_times": [
45.7000000000000028421709430404007434844970703125
]
},
"d": {
"value": 14.2809000000000008157030606525950133800506591796875,
"test_run_times": [
45.64999999999999857891452847979962825775146484375
]
}
}
},
"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": 4837,
"test_run_times": [
5.79999999999999982236431605997495353221893310546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"b": {
"value": 4793,
"test_run_times": [
5.7599999999999997868371792719699442386627197265625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"c": {
"value": 4765,
"test_run_times": [
5.7400000000000002131628207280300557613372802734375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"d": {
"value": 4820,
"test_run_times": [
5.78000000000000024868995751603506505489349365234375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
}
}
},
"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": 1.249184000000000072105876824934966862201690673828125,
"test_run_times": [
1.2800000000000000266453525910037569701671600341796875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O2 -pthread -lbz2 -lpthread"
}
}
},
"b": {
"value": 1.235155999999999920646587270312011241912841796875,
"test_run_times": [
1.2600000000000000088817841970012523233890533447265625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O2 -pthread -lbz2 -lpthread"
}
}
},
"c": {
"value": 1.235287000000000023902657630969770252704620361328125,
"test_run_times": [
1.2600000000000000088817841970012523233890533447265625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O2 -pthread -lbz2 -lpthread"
}
}
},
"d": {
"value": 1.252094000000000040273562262882478535175323486328125,
"test_run_times": [
1.2800000000000000266453525910037569701671600341796875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O2 -pthread -lbz2 -lpthread"
}
}
}
}
},
"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": 152.479999999999989768184605054557323455810546875,
"test_run_times": [
6.29999999999999982236431605997495353221893310546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 152.78800000000001091393642127513885498046875,
"test_run_times": [
5.5800000000000000710542735760100185871124267578125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 153.09800000000001318767317570745944976806640625,
"test_run_times": [
5.6699999999999999289457264239899814128875732421875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"d": {
"value": 154.5,
"test_run_times": [
5.54999999999999982236431605997495353221893310546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"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": 4060,
"test_run_times": [
5.04000000000000003552713678800500929355621337890625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"b": {
"value": 4041,
"test_run_times": [
5.0099999999999997868371792719699442386627197265625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"c": {
"value": 4092,
"test_run_times": [
5.089999999999999857891452847979962825775146484375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"d": {
"value": 4059,
"test_run_times": [
5.04999999999999982236431605997495353221893310546875
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
}
}
},
"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": 26.074000000000001620037437533028423786163330078125,
"test_run_times": [
26.07000000000000028421709430404007434844970703125
]
},
"b": {
"value": 26.364000000000000767386154620908200740814208984375,
"test_run_times": [
26.3599999999999994315658113919198513031005859375
]
},
"c": {
"value": 26.042000000000001591615728102624416351318359375,
"test_run_times": [
26.03999999999999914734871708787977695465087890625
]
},
"d": {
"value": 26.131000000000000227373675443232059478759765625,
"test_run_times": [
26.129999999999999005240169935859739780426025390625
]
}
}
},
"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": 168.799000000000006593836587853729724884033203125,
"test_run_times": [
5.4900000000000002131628207280300557613372802734375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"b": {
"value": 167.051999999999992496668710373342037200927734375,
"test_run_times": [
5.75
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"c": {
"value": 168.19999999999998863131622783839702606201171875,
"test_run_times": [
5.45000000000000017763568394002504646778106689453125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
},
"d": {
"value": 168.292000000000001591615728102624416351318359375,
"test_run_times": [
5.5999999999999996447286321199499070644378662109375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-march=native -mno-avx -mavx2 -mavx512f -mavx512bw -mavx512dq"
}
}
}
}
},
"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": 181.563999999999992951416061259806156158447265625,
"test_run_times": [
181.56000000000000227373675443232059478759765625
]
},
"b": {
"value": 183.152999999999991587174008600413799285888671875,
"test_run_times": [
183.150000000000005684341886080801486968994140625
]
},
"c": {
"value": 182.433999999999997498889570124447345733642578125,
"test_run_times": [
182.43000000000000682121026329696178436279296875
]
},
"d": {
"value": 181.2839999999999918145476840436458587646484375,
"test_run_times": [
181.280000000000001136868377216160297393798828125
]
}
}
},
"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": 137.94859999999999899955582804977893829345703125,
"test_run_times": [
44.719999999999998863131622783839702606201171875
]
},
"b": {
"value": 137.2758000000000038198777474462985992431640625,
"test_run_times": [
44.74000000000000198951966012828052043914794921875
]
},
"c": {
"value": 136.558999999999997498889570124447345733642578125,
"test_run_times": [
44.7999999999999971578290569595992565155029296875
]
},
"d": {
"value": 137.823000000000007503331289626657962799072265625,
"test_run_times": [
44.82000000000000028421709430404007434844970703125
]
}
}
},
"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": 461.3827999999999747160472907125949859619140625,
"test_run_times": [
44.719999999999998863131622783839702606201171875
]
},
"b": {
"value": 462.51780000000002246451913379132747650146484375,
"test_run_times": [
44.74000000000000198951966012828052043914794921875
]
},
"c": {
"value": 465.4569999999999936335370875895023345947265625,
"test_run_times": [
44.7999999999999971578290569595992565155029296875
]
},
"d": {
"value": 460.90870000000001027729013003408908843994140625,
"test_run_times": [
44.82000000000000028421709430404007434844970703125
]
}
}
},
"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": 199.06680000000000063664629124104976654052734375,
"test_run_times": [
39.4500000000000028421709430404007434844970703125
]
},
"b": {
"value": 198.344799999999992223820299841463565826416015625,
"test_run_times": [
39.280000000000001136868377216160297393798828125
]
},
"c": {
"value": 200.281800000000004047251422889530658721923828125,
"test_run_times": [
39.2999999999999971578290569595992565155029296875
]
},
"d": {
"value": 198.37889999999998735802364535629749298095703125,
"test_run_times": [
39.28999999999999914734871708787977695465087890625
]
}
}
},
"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": 5.01989999999999980673237587325274944305419921875,
"test_run_times": [
39.4500000000000028421709430404007434844970703125
]
},
"b": {
"value": 5.03779999999999983373299983213655650615692138671875,
"test_run_times": [
39.280000000000001136868377216160297393798828125
]
},
"c": {
"value": 4.98960000000000025721647034515626728534698486328125,
"test_run_times": [
39.2999999999999971578290569595992565155029296875
]
},
"d": {
"value": 5.03709999999999968878228173707611858844757080078125,
"test_run_times": [
39.28999999999999914734871708787977695465087890625
]
}
}
},
"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": 197.613300000000009504219633527100086212158203125,
"test_run_times": [
37.780000000000001136868377216160297393798828125
]
},
"b": {
"value": 195.871700000000004138200893066823482513427734375,
"test_run_times": [
37.78999999999999914734871708787977695465087890625
]
},
"c": {
"value": 195.832500000000010231815394945442676544189453125,
"test_run_times": [
37.85000000000000142108547152020037174224853515625
]
},
"d": {
"value": 197.0081000000000130967237055301666259765625,
"test_run_times": [
37.75
]
}
}
},
"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": 5.05799999999999982946974341757595539093017578125,
"test_run_times": [
37.780000000000001136868377216160297393798828125
]
},
"b": {
"value": 5.1029999999999997584154698415659368038177490234375,
"test_run_times": [
37.78999999999999914734871708787977695465087890625
]
},
"c": {
"value": 5.103699999999999903366187936626374721527099609375,
"test_run_times": [
37.85000000000000142108547152020037174224853515625
]
},
"d": {
"value": 5.07340000000000035385028240852989256381988525390625,
"test_run_times": [
37.75
]
}
}
},
"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": 1800.714600000000018553691916167736053466796875,
"test_run_times": [
38.17999999999999971578290569595992565155029296875
]
},
"b": {
"value": 1788.797800000000052023096941411495208740234375,
"test_run_times": [
38.25
]
},
"c": {
"value": 1803.23219999999992069206200540065765380859375,
"test_run_times": [
38.159999999999996589394868351519107818603515625
]
},
"d": {
"value": 1794.84619999999995343387126922607421875,
"test_run_times": [
38.11999999999999744204615126363933086395263671875
]
}
}
},
"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": 35.49980000000000046611603465862572193145751953125,
"test_run_times": [
38.17999999999999971578290569595992565155029296875
]
},
"b": {
"value": 35.73029999999999972715158946812152862548828125,
"test_run_times": [
38.25
]
},
"c": {
"value": 35.4543000000000034788172342814505100250244140625,
"test_run_times": [
38.159999999999996589394868351519107818603515625
]
},
"d": {
"value": 35.61370000000000146656020660884678363800048828125,
"test_run_times": [
38.11999999999999744204615126363933086395263671875
]
}
}
},
"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": 34.0568999999999988403942552395164966583251953125,
"test_run_times": [
43.4200000000000017053025658242404460906982421875
]
},
"b": {
"value": 34.123300000000000409272615797817707061767578125,
"test_run_times": [
48.52000000000000312638803734444081783294677734375
]
},
"c": {
"value": 33.98960000000000292175172944553196430206298828125,
"test_run_times": [
43.53999999999999914734871708787977695465087890625
]
},
"d": {
"value": 33.891300000000001091393642127513885498046875,
"test_run_times": [
43.63000000000000255795384873636066913604736328125
]
}
}
},
"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": 29.354500000000001591615728102624416351318359375,
"test_run_times": [
43.4200000000000017053025658242404460906982421875
]
},
"b": {
"value": 29.294799999999998618704921682365238666534423828125,
"test_run_times": [
48.52000000000000312638803734444081783294677734375
]
},
"c": {
"value": 29.411500000000000198951966012828052043914794921875,
"test_run_times": [
43.53999999999999914734871708787977695465087890625
]
},
"d": {
"value": 29.495000000000000994759830064140260219573974609375,
"test_run_times": [
43.63000000000000255795384873636066913604736328125
]
}
}
},
"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": 51.6595999999999975216269376687705516815185546875,
"test_run_times": [
39.71000000000000085265128291212022304534912109375
]
},
"b": {
"value": 51.51310000000000144382283906452357769012451171875,
"test_run_times": [
39.8299999999999982946974341757595539093017578125
]
},
"c": {
"value": 51.84219999999999828332875040359795093536376953125,
"test_run_times": [
39.85000000000000142108547152020037174224853515625
]
},
"d": {
"value": 51.70720000000000027284841053187847137451171875,
"test_run_times": [
39.840000000000003410605131648480892181396484375
]
}
}
},
"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": 1238.056100000000014915713109076023101806640625,
"test_run_times": [
39.71000000000000085265128291212022304534912109375
]
},
"b": {
"value": 1241.54880000000002837623469531536102294921875,
"test_run_times": [
39.8299999999999982946974341757595539093017578125
]
},
"c": {
"value": 1233.704999999999927240423858165740966796875,
"test_run_times": [
39.85000000000000142108547152020037174224853515625
]
},
"d": {
"value": 1236.947799999999915598891675472259521484375,
"test_run_times": [
39.840000000000003410605131648480892181396484375
]
}
}
},
"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": 342.28140000000001919033820740878582000732421875,
"test_run_times": [
37.72999999999999687361196265555918216705322265625
]
},
"b": {
"value": 342.9008000000000038198777474462985992431640625,
"test_run_times": [
37.56000000000000227373675443232059478759765625
]
},
"c": {
"value": 341.44409999999999172359821386635303497314453125,
"test_run_times": [
37.6099999999999994315658113919198513031005859375
]
},
"d": {
"value": 343.5348999999999932697392068803310394287109375,
"test_run_times": [
37.590000000000003410605131648480892181396484375
]
}
}
},
"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": 25.0330000000000012505552149377763271331787109375,
"test_run_times": [
25.050000000000000710542735760100185871124267578125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"b": {
"value": 24.97500000000000142108547152020037174224853515625,
"test_run_times": [
24.989999999999998436805981327779591083526611328125
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"c": {
"value": 25.077000000000001733724275254644453525543212890625,
"test_run_times": [
25.089999999999999857891452847979962825775146484375
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
},
"d": {
"value": 24.925000000000000710542735760100185871124267578125,
"test_run_times": [
24.940000000000001278976924368180334568023681640625
],
"details": {
"compiler-options": {
"compiler-type": "CXX",
"compiler": "g++",
"compiler-options": "-O3"
}
}
}
}
},
"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": 2.91880000000000006110667527536861598491668701171875,
"test_run_times": [
37.72999999999999687361196265555918216705322265625
]
},
"b": {
"value": 2.91349999999999997868371792719699442386627197265625,
"test_run_times": [
37.56000000000000227373675443232059478759765625
]
},
"c": {
"value": 2.92569999999999996731503415503539144992828369140625,
"test_run_times": [
37.6099999999999994315658113919198513031005859375
]
},
"d": {
"value": 2.907999999999999918287585387588478624820709228515625,
"test_run_times": [
37.590000000000003410605131648480892181396484375
]
}
}
},
"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": 1789.69579999999996289261616766452789306640625,
"test_run_times": [
38.36999999999999744204615126363933086395263671875
]
},
"b": {
"value": 1792.693899999999985084286890923976898193359375,
"test_run_times": [
43.27000000000000312638803734444081783294677734375
]
},
"c": {
"value": 1781.89069999999992433004081249237060546875,
"test_run_times": [
38.219999999999998863131622783839702606201171875
]
},
"d": {
"value": 1789.8074999999998908606357872486114501953125,
"test_run_times": [
38.3299999999999982946974341757595539093017578125
]
}
}
},
"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": 351.8686999999999898136593401432037353515625,
"test_run_times": [
41.52000000000000312638803734444081783294677734375
]
},
"b": {
"value": 350.377799999999979263520799577236175537109375,
"test_run_times": [
41.67999999999999971578290569595992565155029296875
]
},
"c": {
"value": 349.80320000000000391082721762359142303466796875,
"test_run_times": [
41.53999999999999914734871708787977695465087890625
]
},
"d": {
"value": 350.442999999999983629095368087291717529296875,
"test_run_times": [
41.39999999999999857891452847979962825775146484375
]
}
}
},
"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": 35.71509999999999962483343551866710186004638671875,
"test_run_times": [
38.36999999999999744204615126363933086395263671875
]
},
"b": {
"value": 35.666100000000000136424205265939235687255859375,
"test_run_times": [
43.27000000000000312638803734444081783294677734375
]
},
"c": {
"value": 35.8738000000000027966962079517543315887451171875,
"test_run_times": [
38.219999999999998863131622783839702606201171875
]
},
"d": {
"value": 35.710700000000002773958840407431125640869140625,
"test_run_times": [
38.3299999999999982946974341757595539093017578125
]
}
}
},
"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": 181.78530000000000654836185276508331298828125,
"test_run_times": [
41.52000000000000312638803734444081783294677734375
]
},
"b": {
"value": 182.109600000000000363797880709171295166015625,
"test_run_times": [
41.67999999999999971578290569595992565155029296875
]
},
"c": {
"value": 182.808999999999997498889570124447345733642578125,
"test_run_times": [
41.53999999999999914734871708787977695465087890625
]
},
"d": {
"value": 182.552400000000005775291356258094310760498046875,
"test_run_times": [
41.39999999999999857891452847979962825775146484375
]
}
}
},
"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": 2.908500000000000085265128291212022304534912109375,
"test_run_times": [
37.5499999999999971578290569595992565155029296875
]
},
"b": {
"value": 2.919200000000000017053025658242404460906982421875,
"test_run_times": [
37.52000000000000312638803734444081783294677734375
]
},
"c": {
"value": 2.91730000000000000426325641456060111522674560546875,
"test_run_times": [
37.590000000000003410605131648480892181396484375
]
},
"d": {
"value": 2.90350000000000019184653865522705018520355224609375,
"test_run_times": [
42.81000000000000227373675443232059478759765625
]
}
}
},
"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": 343.4587000000000216459739021956920623779296875,
"test_run_times": [
37.5499999999999971578290569595992565155029296875
]
},
"b": {
"value": 342.20839999999998326529748737812042236328125,
"test_run_times": [
37.52000000000000312638803734444081783294677734375
]
},
"c": {
"value": 342.442099999999982173903845250606536865234375,
"test_run_times": [
37.590000000000003410605131648480892181396484375
]
},
"d": {
"value": 344.04689999999999372448655776679515838623046875,
"test_run_times": [
42.81000000000000227373675443232059478759765625
]
}
}
},
"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": 5.44629999999999991899812812334857881069183349609375,
"test_run_times": [
38.67999999999999971578290569595992565155029296875
]
},
"b": {
"value": 5.4444999999999996731503415503539144992828369140625,
"test_run_times": [
38.75999999999999801048033987171947956085205078125
]
},
"c": {
"value": 5.45439999999999969304553815163671970367431640625,
"test_run_times": [
38.659999999999996589394868351519107818603515625
]
},
"d": {
"value": 5.46750000000000024868995751603506505489349365234375,
"test_run_times": [
38.81000000000000227373675443232059478759765625
]
}
}
},
"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": 11719.007100000000718864612281322479248046875,
"test_run_times": [
38.67999999999999971578290569595992565155029296875
]
},
"b": {
"value": 11722.586300000000846921466290950775146484375,
"test_run_times": [
38.75999999999999801048033987171947956085205078125
]
},
"c": {
"value": 11702.1756999999997788108885288238525390625,
"test_run_times": [
38.659999999999996589394868351519107818603515625
]
},
"d": {
"value": 11674.246199999999589635990560054779052734375,
"test_run_times": [
38.81000000000000227373675443232059478759765625
]
}
}
},
"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": 138.30500000000000682121026329696178436279296875,
"test_run_times": [
44.46000000000000085265128291212022304534912109375
]
},
"b": {
"value": 137.790899999999993497112882323563098907470703125,
"test_run_times": [
44.56000000000000227373675443232059478759765625
]
},
"c": {
"value": 137.970499999999987039700499735772609710693359375,
"test_run_times": [
44.6099999999999994315658113919198513031005859375
]
},
"d": {
"value": 137.965699999999998226485331542789936065673828125,
"test_run_times": [
44.56000000000000227373675443232059478759765625
]
}
}
},
"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": 13.9186999999999994059862729045562446117401123046875,
"test_run_times": [
47.159999999999996589394868351519107818603515625
]
},
"b": {
"value": 13.8924000000000003041122909053228795528411865234375,
"test_run_times": [
47.2000000000000028421709430404007434844970703125
]
},
"c": {
"value": 13.8712999999999997413624441833235323429107666015625,
"test_run_times": [
47.21000000000000085265128291212022304534912109375
]
},
"d": {
"value": 13.92229999999999989768184605054557323455810546875,
"test_run_times": [
47.24000000000000198951966012828052043914794921875
]
}
}
},
"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": 4590.2272999999995590769685804843902587890625,
"test_run_times": [
47.159999999999996589394868351519107818603515625
]
},
"b": {
"value": 4598.8810000000003128661774098873138427734375,
"test_run_times": [
47.2000000000000028421709430404007434844970703125
]
},
"c": {
"value": 4605.9916000000002895831130445003509521484375,
"test_run_times": [
47.21000000000000085265128291212022304534912109375
]
},
"d": {
"value": 4589.1482999999998355633579194545745849609375,
"test_run_times": [
47.24000000000000198951966012828052043914794921875
]
}
}
},
"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": 3.27780000000000004689582056016661226749420166015625,
"test_run_times": [
45.64999999999999857891452847979962825775146484375
]
},
"b": {
"value": 3.27740000000000009094947017729282379150390625,
"test_run_times": [
45.68999999999999772626324556767940521240234375
]
},
"c": {
"value": 3.276100000000000012079226507921703159809112548828125,
"test_run_times": [
45.590000000000003410605131648480892181396484375
]
},
"d": {
"value": 3.28770000000000006679101716144941747188568115234375,
"test_run_times": [
45.6400000000000005684341886080801486968994140625
]
}
}
},
"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": 304.7581000000000130967237055301666259765625,
"test_run_times": [
45.64999999999999857891452847979962825775146484375
]
},
"b": {
"value": 304.795299999999997453414835035800933837890625,
"test_run_times": [
45.68999999999999772626324556767940521240234375
]
},
"c": {
"value": 304.8962999999999965439201332628726959228515625,
"test_run_times": [
45.590000000000003410605131648480892181396484375
]
},
"d": {
"value": 303.84219999999999117790139280259609222412109375,
"test_run_times": [
45.6400000000000005684341886080801486968994140625
]
}
}
},
"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": 460.7323000000000092768459580838680267333984375,
"test_run_times": [
44.46000000000000085265128291212022304534912109375
]
},
"b": {
"value": 461.21670000000000300133251585066318511962890625,
"test_run_times": [
44.56000000000000227373675443232059478759765625
]
},
"c": {
"value": 461.9932000000000016370904631912708282470703125,
"test_run_times": [
44.6099999999999994315658113919198513031005859375
]
},
"d": {
"value": 462.02839999999997644408722408115863800048828125,
"test_run_times": [
44.56000000000000227373675443232059478759765625
]
}
}
},
"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": 29.248599999999999710098563809879124164581298828125,
"test_run_times": [
43.38000000000000255795384873636066913604736328125
]
},
"b": {
"value": 29.208400000000001028865881380625069141387939453125,
"test_run_times": [
43.2000000000000028421709430404007434844970703125
]
},
"c": {
"value": 29.27680000000000148929757415316998958587646484375,
"test_run_times": [
43.43999999999999772626324556767940521240234375
]
},
"d": {
"value": 29.236399999999999721467247582040727138519287109375,
"test_run_times": [
43.38000000000000255795384873636066913604736328125
]
}
}
},
"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": 34.183300000000002683009370230138301849365234375,
"test_run_times": [
43.38000000000000255795384873636066913604736328125
]
},
"b": {
"value": 34.22970000000000112549969344399869441986083984375,
"test_run_times": [
43.2000000000000028421709430404007434844970703125
]
},
"c": {
"value": 34.1503000000000014324541552923619747161865234375,
"test_run_times": [
43.43999999999999772626324556767940521240234375
]
},
"d": {
"value": 34.19680000000000319460013997741043567657470703125,
"test_run_times": [
43.38000000000000255795384873636066913604736328125
]
}
}
},
"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": 1904.078299999999899227987043559551239013671875,
"test_run_times": [
46.090000000000003410605131648480892181396484375
]
},
"b": {
"value": 1902.914500000000089130480773746967315673828125,
"test_run_times": [
46.219999999999998863131622783839702606201171875
]
},
"c": {
"value": 1902.1757999999999810825102031230926513671875,
"test_run_times": [
46.159999999999996589394868351519107818603515625
]
},
"d": {
"value": 1902.9281000000000858562998473644256591796875,
"test_run_times": [
45.93999999999999772626324556767940521240234375
]
}
}
},
"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": 73.9698000000000064346750150434672832489013671875,
"test_run_times": [
38.3299999999999982946974341757595539093017578125
]
},
"b": {
"value": 73.9960999999999984311216394416987895965576171875,
"test_run_times": [
38.280000000000001136868377216160297393798828125
]
},
"c": {
"value": 74.0382000000000033423930290155112743377685546875,
"test_run_times": [
38.38000000000000255795384873636066913604736328125
]
},
"d": {
"value": 74.0260999999999995679900166578590869903564453125,
"test_run_times": [
38.219999999999998863131622783839702606201171875
]
}
}
},
"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": 864.3473999999999932697392068803310394287109375,
"test_run_times": [
38.3299999999999982946974341757595539093017578125
]
},
"b": {
"value": 863.669200000000046202330850064754486083984375,
"test_run_times": [
38.280000000000001136868377216160297393798828125
]
},
"c": {
"value": 863.8537999999999783540260978043079376220703125,
"test_run_times": [
38.38000000000000255795384873636066913604736328125
]
},
"d": {
"value": 863.925700000000006184563972055912017822265625,
"test_run_times": [
38.219999999999998863131622783839702606201171875
]
}
}
},
"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": 33.57180000000000319460013997741043567657470703125,
"test_run_times": [
46.090000000000003410605131648480892181396484375
]
},
"b": {
"value": 33.59420000000000072759576141834259033203125,
"test_run_times": [
46.219999999999998863131622783839702606201171875
]
},
"c": {
"value": 33.59129999999999682813722756691277027130126953125,
"test_run_times": [
46.159999999999996589394868351519107818603515625
]
},
"d": {
"value": 33.59669999999999845385900698602199554443359375,
"test_run_times": [
45.93999999999999772626324556767940521240234375
]
}
}
}
}
}