cxle sep 2022

Intel Core i9-10980XE testing with a ASRock X299 Steel Legend (P1.30 BIOS) and llvmpipe 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 2209028-PTS-CXLESEP292
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Timed Code Compilation 5 Tests
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HPC - High Performance Computing 2 Tests
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Multi-Core 9 Tests
Programmer / Developer System Benchmarks 5 Tests
Python Tests 2 Tests
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A
September 02 2022
  1 Hour, 7 Minutes
B
September 02 2022
  1 Hour, 6 Minutes
C
September 02 2022
  9 Minutes
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cxle sep 2022 Intel Core i9-10980XE testing with a ASRock X299 Steel Legend (P1.30 BIOS) and llvmpipe on Ubuntu 22.04 via the Phoronix Test Suite. ,,"A","B","C" Processor,,Intel Core i9-10980XE @ 4.80GHz (18 Cores / 36 Threads),Intel Core i9-10980XE @ 4.80GHz (18 Cores / 36 Threads),Intel Core i9-10980XE @ 4.80GHz (18 Cores / 36 Threads) Motherboard,,ASRock X299 Steel Legend (P1.30 BIOS),ASRock X299 Steel Legend (P1.30 BIOS),ASRock X299 Steel Legend (P1.30 BIOS) Chipset,,Intel Sky Lake-E DMI3 Registers,Intel Sky Lake-E DMI3 Registers,Intel Sky Lake-E DMI3 Registers Memory,,32GB,32GB,32GB Disk,,Samsung SSD 970 PRO 512GB,Samsung SSD 970 PRO 512GB,Samsung SSD 970 PRO 512GB Graphics,,llvmpipe,llvmpipe,llvmpipe Audio,,Realtek ALC1220,Realtek ALC1220,Realtek ALC1220 Network,,Intel I219-V + Intel I211,Intel I219-V + Intel I211,Intel I219-V + Intel I211 OS,,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04 Kernel,,5.19.0-051900rc7-generic (x86_64),5.19.0-051900rc7-generic (x86_64),5.19.0-051900rc7-generic (x86_64) Desktop,,GNOME Shell 42.2,GNOME Shell 42.2,GNOME Shell 42.2 Display Server,,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3 OpenGL,,4.5 Mesa 22.0.1 (LLVM 13.0.1 256 bits),4.5 Mesa 22.0.1 (LLVM 13.0.1 256 bits),4.5 Mesa 22.0.1 (LLVM 13.0.1 256 bits) Vulkan,,1.2.204,1.2.204,1.2.204 Compiler,,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0 File-System,,ext4,ext4,ext4 Screen Resolution,,1024x768,1024x768,1024x768 ,,"A","B","C" "Mobile Neural Network - Model: squeezenetv1.1 (ms)",LIB,2.671,2.388, "Mobile Neural Network - Model: SqueezeNetV1.0 (ms)",LIB,5.127,4.606, "Mobile Neural Network - Model: mobilenet-v1-1.0 (ms)",LIB,2.792,2.585, "Natron - Input: Spaceship (FPS)",HIB,3.8,4.1, "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,16.86,18.06, "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,532.75,497.47, "Mobile Neural Network - Model: MobileNetV2_224 (ms)",LIB,3.849,3.688, "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,0.5,0.52, "OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,6.18,6.41, "OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,1443.73,1400.04, "GraphicsMagick - Operation: Rotate (Iterations/min)",HIB,771,795,794 "Mobile Neural Network - Model: resnet-v2-50 (ms)",LIB,9.821,9.525, "Mobile Neural Network - Model: nasnet (ms)",LIB,14.957,14.512, "GraphicsMagick - Operation: HWB Color Space (Iterations/min)",HIB,891,866,878 "OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,2626.86,2555.32, "OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,3.39,3.48, "GraphicsMagick - Operation: Noise-Gaussian (Iterations/min)",HIB,386,383,378 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,8.8,8.64, "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,1020.4,1039.07, "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,32619.64,32100.57, "7-Zip Compression - Test: Compression Rating (MIPS)",HIB,116952,118795,117179 "Unpacking The Linux Kernel - linux-5.19.tar.xz (sec)",LIB,7.475,7.527,7.426 "Mobile Neural Network - Model: mobilenetV3 (ms)",LIB,1.984,2.01, "7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,102464,101358,101803 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,0.99,1, "GraphicsMagick - Operation: Swirl (Iterations/min)",HIB,677,672,672 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,17825.32,17723.69, "Timed Erlang/OTP Compilation - Time To Compile (sec)",LIB,103.484,102.901, "GraphicsMagick - Operation: Resizing (Iterations/min)",HIB,1480,1472,1479 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,23.84,23.72, "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,753.52,757.32, "Timed PHP Compilation - Time To Compile (sec)",LIB,57.561,57.32, "Mobile Neural Network - Model: inception-v3 (ms)",LIB,22.495,22.42, "Timed Wasmer Compilation - Time To Compile (sec)",LIB,55.762,55.598, "GraphicsMagick - Operation: Enhanced (Iterations/min)",HIB,350,349,349 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,57.78,57.91, "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,155.6,155.26, "Timed CPython Compilation - Build Configuration: Default (sec)",LIB,17.664,17.699, "Timed Node.js Compilation - Time To Compile (sec)",LIB,376.628,377.2, "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,7.26,7.25, "OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,2542.39,2545.61, "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,2474.62,2476.8, "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,385.68,385.95, "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,139.31,139.34, "Timed CPython Compilation - Build Configuration: Released Build, PGO + LTO Optimized (sec)",LIB,276.266,276.312, "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,64.55,64.54, "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,23.29,23.29, "OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,3.49,3.49, "GraphicsMagick - Operation: Sharpen (Iterations/min)",HIB,212,212,212