Intel Core i7-10700T testing with a Logic Supply RXM-181 (Z01-0002A026 BIOS) and Intel UHD 630 CML GT2 3GB on Ubuntu 21.10 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 2203303-NE-10700TCOM78
10700t comet weds
Intel Core i7-10700T testing with a Logic Supply RXM-181 (Z01-0002A026 BIOS) and Intel UHD 630 CML GT2 3GB on Ubuntu 21.10 via the Phoronix Test Suite.
,,"A","B","C"
Processor,,Intel Core i7-10700T @ 4.50GHz (8 Cores / 16 Threads),Intel Core i7-10700T @ 4.50GHz (8 Cores / 16 Threads),Intel Core i7-10700T @ 4.50GHz (8 Cores / 16 Threads)
Motherboard,,Logic Supply RXM-181 (Z01-0002A026 BIOS),Logic Supply RXM-181 (Z01-0002A026 BIOS),Logic Supply RXM-181 (Z01-0002A026 BIOS)
Chipset,,Intel Comet Lake PCH,Intel Comet Lake PCH,Intel Comet Lake PCH
Memory,,32GB,32GB,32GB
Disk,,256GB TS256GMTS800,256GB TS256GMTS800,256GB TS256GMTS800
Graphics,,Intel UHD 630 CML GT2 3GB (1200MHz),Intel UHD 630 CML GT2 3GB (1200MHz),Intel UHD 630 CML GT2 3GB (1200MHz)
Audio,,Realtek ALC233,Realtek ALC233,Realtek ALC233
Monitor,,DELL P2415Q,DELL P2415Q,DELL P2415Q
Network,,Intel I219-LM + Intel I210,Intel I219-LM + Intel I210,Intel I219-LM + Intel I210
OS,,Ubuntu 21.10,Ubuntu 21.10,Ubuntu 21.10
Kernel,,5.13.0-35-generic (x86_64),5.13.0-35-generic (x86_64),5.13.0-35-generic (x86_64)
Desktop,,GNOME Shell 40.5,GNOME Shell 40.5,GNOME Shell 40.5
Display Server,,X Server + Wayland,X Server + Wayland,X Server + Wayland
OpenGL,,4.6 Mesa 21.2.2,4.6 Mesa 21.2.2,4.6 Mesa 21.2.2
Vulkan,,1.2.182,1.2.182,1.2.182
Compiler,,GCC 11.2.0,GCC 11.2.0,GCC 11.2.0
File-System,,ext4,ext4,ext4
Screen Resolution,,1920x1080,1920x1080,1920x1080
,,"A","B","C"
"perf-bench - Benchmark: Epoll Wait (ops/sec)",HIB,109366,115261,112104
"perf-bench - Benchmark: Futex Hash (ops/sec)",HIB,3559455,3644833,3674250
"perf-bench - Benchmark: Memcpy 1MB (GB/sec)",HIB,26.836621,26.803861,25.616662
"perf-bench - Benchmark: Memset 1MB (GB/sec)",HIB,43.091819,43.234222,41.195661
"perf-bench - Benchmark: Sched Pipe (ops/sec)",HIB,163024,161604,161030
"perf-bench - Benchmark: Futex Lock-Pi (ops/sec)",HIB,843,845,848
"perf-bench - Benchmark: Syscall Basic (ops/sec)",HIB,14180008,14188609,14102641
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,6.31917,4.19472,4.18294
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,9.74806,9.64795,9.36624
"oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.80373,2.2005,2.26074
"oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.62391,2.48963,2.43947
"oneDNN - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,
"oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,17.0221,17.0692,17.017
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,14.0868,11.0421,12.9019
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,9.22489,8.17558,8.25954
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,15.5284,15.5771,15.4461
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,3.87824,3.76516,3.76013
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,5.46541,4.65868,4.60998
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,6791.09,6778.99,6787.52
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,3603.05,3588.14,3594.68
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,6792.71,6780.39,6786.74
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,3597.62,3575.32,3590.54
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU (ms)",LIB,3.98170,3.96065,3.94494
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,6801.99,6804,6790.86
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,3612.75,3619.68,3600.38
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,2.26038,2.30454,2.24351
"oneDNN - Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,,
"ONNX Runtime - Model: GPT-2 - Device: CPU (Inferences/min)",HIB,3644,3713,3711
"ONNX Runtime - Model: yolov4 - Device: CPU (Inferences/min)",HIB,203,203,204
"ONNX Runtime - Model: bertsquad-12 - Device: CPU (Inferences/min)",HIB,303,306,
"ONNX Runtime - Model: fcn-resnet101-11 - Device: CPU (Inferences/min)",HIB,39,39,
"ONNX Runtime - Model: ArcFace ResNet-100 - Device: CPU (Inferences/min)",HIB,694,703,
"ONNX Runtime - Model: super-resolution-10 - Device: CPU (Inferences/min)",HIB,2167,2186,