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 2311069-PTS-AUG6407629
aug
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"
Processor,,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)
Chipset,,Intel Sky Lake-E DMI3 Registers,Intel Sky Lake-E DMI3 Registers
Memory,,32GB,32GB
Disk,,Samsung SSD 970 PRO 512GB,Samsung SSD 970 PRO 512GB
Graphics,,llvmpipe,llvmpipe
Audio,,Realtek ALC1220,Realtek ALC1220
Network,,Intel I219-V + Intel I211,Intel I219-V + Intel I211
OS,,Ubuntu 22.04,Ubuntu 22.04
Kernel,,6.2.0-33-generic (x86_64),6.2.0-33-generic (x86_64)
Desktop,,GNOME Shell 42.2,GNOME Shell 42.2
Display Server,,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)
Vulkan,,1.2.204,1.2.204
Compiler,,GCC 11.4.0,GCC 11.4.0
File-System,,ext4,ext4
Screen Resolution,,1024x768,1024x768
,,"a","b"
"OpenVKL - Benchmark: vklBenchmarkCPU Scalar (Items / Sec)",HIB,157,157
"OpenVKL - Benchmark: vklBenchmarkCPU ISPC (Items / Sec)",HIB,411,411
"Timed Gem5 Compilation - Time To Compile (sec)",LIB,413.862,413.585
"OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,257612,257164
"QMCPACK - Input: O_ae_pyscf_UHF (Execution Time - sec)",LIB,238,241.13
"OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,218906,218882
"OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,214480,214262
"QMCPACK - Input: Li2_STO_ae (Execution Time - sec)",LIB,219.65,222.42
"CloverLeaf - Input: clover_bm64_short (sec)",LIB,212.72,211.67
"easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 (sec)",LIB,207.533,207.714
"DuckDB - Benchmark: IMDB (sec)",LIB,,
"QMCPACK - Input: FeCO6_b3lyp_gms (Execution Time - sec)",LIB,183.42,183.17
"DuckDB - Benchmark: TPC-H Parquet (sec)",LIB,,
"OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,132846,132304
"OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,113740,114336
"OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,110942,110960
"QMCPACK - Input: LiH_ae_MSD (Execution Time - sec)",LIB,106.57,106.32
"CloverLeaf - Input: clover_bm (sec)",LIB,88.76,88.75
"OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,7813,7854
"OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,6625,6606
"OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,6468,6463
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1615.72,1625.41
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,1650.24,1632.03
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,1722.09,1677.89
"OSPRay Studio - Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,70355,70459
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,906.092,908.247
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,897.021,919.84
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,941.957,898.306
"QuantLib - Configuration: Multi-Threaded (MFLOPS)",HIB,44641,44888.6
"Intel Open Image Denoise - Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only (Images / Sec)",HIB,0.42,0.41
"OSPRay Studio - Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,60718,60600
"OSPRay Studio - Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,1636,1630
"OSPRay Studio - Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,59518,59525
"OSPRay Studio - Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,1667,1667
"OSPRay Studio - Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,1968,1972
"OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,1758.87,1768.54
"OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,6.77,6.74
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,444.06,444.29
"OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,26.96,26.97
"OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,453.11,457.7
"OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,26.48,26.21
"OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,452.46,457
"OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,26.51,26.25
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,151.95,152.93
"OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,78.93,78.36
"OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (ms)",LIB,51.6,52.23
"OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (FPS)",HIB,232.23,229.51
"OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (ms)",LIB,205.41,205.72
"OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (FPS)",HIB,58.37,58.28
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,37.23,37.14
"OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,322.01,322.81
"OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (ms)",LIB,86.37,119.54
"OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (FPS)",HIB,208.24,150.46
"OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (ms)",LIB,104.57,103.02
"OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (FPS)",HIB,171.99,174.6
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,15.82,15.77
"OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,756.48,758.98
"OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (ms)",LIB,5.59,5.59
"OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (FPS)",HIB,3190.1,3192.8
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,85.3,84.25
"OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,140.54,142.3
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,23.43,23.52
"OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,766.69,763.83
"OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (ms)",LIB,15.78,15.65
"OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (FPS)",HIB,759.1,765.16
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,0.48,0.48
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,35356.18,35584.44
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,6.58,6.57
"OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,2725.1,2734.29
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,0.97,0.97
"OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,18225.98,18196.6
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon Obj (FPS)",HIB,19.6108,19.6293
"OSPRay Studio - Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,38826,38857
"C-Blosc - Test: blosclz noshuffle - Buffer Size: 256MB (MB/s)",HIB,4239.4,4248.9
"Embree - Binary: Pathtracer - Model: Asian Dragon Obj (FPS)",HIB,20.7169,20.6897
"C-Blosc - Test: blosclz shuffle - Buffer Size: 256MB (MB/s)",HIB,4399.7,4429.6
"C-Blosc - Test: blosclz bitshuffle - Buffer Size: 256MB (MB/s)",HIB,4497.3,4516
"OSPRay Studio - Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,34183,34063
"OSPRay Studio - Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,33567,33453
"QMCPACK - Input: simple-H2O (Execution Time - sec)",LIB,42.511,42.48
"Embree - Binary: Pathtracer ISPC - Model: Crown (FPS)",HIB,17.7179,17.6515
"Embree - Binary: Pathtracer - Model: Crown (FPS)",HIB,20.2696,20.16
"C-Blosc - Test: blosclz shuffle - Buffer Size: 128MB (MB/s)",HIB,5468.8,5457.9
"C-Blosc - Test: blosclz noshuffle - Buffer Size: 128MB (MB/s)",HIB,5467.9,5490.8
"C-Blosc - Test: blosclz bitshuffle - Buffer Size: 128MB (MB/s)",HIB,5578.8,5636.2
"Intel Open Image Denoise - Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,0.88,0.88
"Intel Open Image Denoise - Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,0.88,0.88
"Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS)",HIB,22.8478,22.8438
"Embree - Binary: Pathtracer - Model: Asian Dragon (FPS)",HIB,22.9979,23.1394
"QuantLib - Configuration: Single-Threaded (MFLOPS)",HIB,2682,2684.2
"C-Blosc - Test: blosclz shuffle - Buffer Size: 64MB (MB/s)",HIB,6560.7,6563.5
"Cpuminer-Opt - Algorithm: scrypt (kH/s)",HIB,182.09,182.84
"Cpuminer-Opt - Algorithm: Magi (kH/s)",HIB,422.16,422.06
"Cpuminer-Opt - Algorithm: Triple SHA-256, Onecoin (kH/s)",HIB,53370,53490
"Cpuminer-Opt - Algorithm: Blake-2 S (kH/s)",HIB,103360,103360
"Cpuminer-Opt - Algorithm: Skeincoin (kH/s)",HIB,23470,23190
"C-Blosc - Test: blosclz bitshuffle - Buffer Size: 64MB (MB/s)",HIB,6752.2,6790.6
"C-Blosc - Test: blosclz noshuffle - Buffer Size: 64MB (MB/s)",HIB,6761.1,6779.6
"Cpuminer-Opt - Algorithm: Deepcoin (kH/s)",HIB,5431.94,5428.44
"Cpuminer-Opt - Algorithm: Ringcoin (kH/s)",HIB,2421.85,2421.09
"Cpuminer-Opt - Algorithm: LBC, LBRY Credits (kH/s)",HIB,9720.14,9722.17
"Cpuminer-Opt - Algorithm: Myriad-Groestl (kH/s)",HIB,7629.51,7651.61
"Cpuminer-Opt - Algorithm: Quad SHA-256, Pyrite (kH/s)",HIB,37850,37850
"Cpuminer-Opt - Algorithm: Garlicoin (kH/s)",HIB,1603.79,1596.74
"C-Blosc - Test: blosclz shuffle - Buffer Size: 8MB (MB/s)",HIB,7438.3,6824.9
"C-Blosc - Test: blosclz shuffle - Buffer Size: 32MB (MB/s)",HIB,7361.7,7424
"C-Blosc - Test: blosclz shuffle - Buffer Size: 16MB (MB/s)",HIB,7457.4,7424.4
"C-Blosc - Test: blosclz bitshuffle - Buffer Size: 32MB (MB/s)",HIB,7590,7651.2
"C-Blosc - Test: blosclz noshuffle - Buffer Size: 32MB (MB/s)",HIB,7828.9,7847.7
"C-Blosc - Test: blosclz bitshuffle - Buffer Size: 16MB (MB/s)",HIB,8107.4,8211.3
"C-Blosc - Test: blosclz bitshuffle - Buffer Size: 8MB (MB/s)",HIB,8267.5,8258.4
"HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 512 (GFLOP/s)",HIB,10.3095,10.2769
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.525652,0.525029
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,11.0649,11.0229
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,6.9011,6.86291
"C-Blosc - Test: blosclz noshuffle - Buffer Size: 16MB (MB/s)",HIB,9855.4,9737.2
"QMCPACK - Input: H4_ae (Execution Time - sec)",LIB,20.61,19.31
"C-Blosc - Test: blosclz noshuffle - Buffer Size: 8MB (MB/s)",HIB,10371.6,10336.6
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,2.49348,2.49628
"oneDNN - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,5.49542,5.54192
"oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.618773,0.578244
"HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 512 (GFLOP/s)",HIB,18.8937,18.7258
"HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 512 (GFLOP/s)",HIB,19.8916,20.059
"easyWave - Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 (sec)",LIB,8.422,8.418
"oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,2.91534,2.85512
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,5.38829,5.25114
"oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1.20555,1.24078
"HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 512 (GFLOP/s)",HIB,35.6982,36.1147
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,9.87746,9.88829
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,9.0344,9.05479
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,7.85872,7.86557
"HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 256 (GFLOP/s)",HIB,8.82564,8.9321
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,11.3386,11.1414
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.633996,0.643669
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,2.70456,2.69575
"HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 256 (GFLOP/s)",HIB,16.3164,15.8081
"HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 256 (GFLOP/s)",HIB,16.7333,16.863
"HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 256 (GFLOP/s)",HIB,31.0169,31.6018
"HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128 (GFLOP/s)",HIB,9.01432,9.1424
"HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128 (GFLOP/s)",HIB,20.9461,21.5749
"HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128 (GFLOP/s)",HIB,26.2733,25.6418
"HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128 (GFLOP/s)",HIB,55.0703,54.9198