epyc-75f3-new 2 x AMD EPYC 75F3 32-Core testing with a ASRockRack ROME2D16-2T (P3.30 BIOS) and ASPEED on Ubuntu 21.10 via the Phoronix Test Suite. A: Processor: 2 x AMD EPYC 75F3 32-Core @ 2.95GHz (64 Cores / 128 Threads), Motherboard: ASRockRack ROME2D16-2T (P3.30 BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: 1000GB Western Digital WD_BLACK SN850 1TB, Graphics: ASPEED, Audio: AMD Starship/Matisse, Network: 2 x Intel 10G X550T OS: Ubuntu 21.10, Kernel: 5.17.0-051700rc4daily20220219-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server, Vulkan: 1.1.182, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1024x768 AA: Processor: 2 x AMD EPYC 75F3 32-Core @ 2.95GHz (64 Cores / 128 Threads), Motherboard: ASRockRack ROME2D16-2T (P3.30 BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: 1000GB Western Digital WD_BLACK SN850 1TB, Graphics: ASPEED, Audio: AMD Starship/Matisse, Network: 2 x Intel 10G X550T OS: Ubuntu 21.10, Kernel: 5.17.0-051700rc4daily20220219-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server, Vulkan: 1.1.182, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1024x768 B: Processor: 2 x AMD EPYC 75F3 32-Core @ 2.95GHz (64 Cores / 128 Threads), Motherboard: ASRockRack ROME2D16-2T (P3.30 BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: 1000GB Western Digital WD_BLACK SN850 1TB, Graphics: ASPEED, Audio: AMD Starship/Matisse, Network: 2 x Intel 10G X550T OS: Ubuntu 21.10, Kernel: 5.17.0-051700rc4daily20220219-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server, Vulkan: 1.1.182, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1024x768 C: Processor: 2 x AMD EPYC 75F3 32-Core @ 2.95GHz (64 Cores / 128 Threads), Motherboard: ASRockRack ROME2D16-2T (P3.30 BIOS), Chipset: AMD Starship/Matisse, Memory: 128GB, Disk: 1000GB Western Digital WD_BLACK SN850 1TB, Graphics: ASPEED, Audio: AMD Starship/Matisse, Network: 2 x Intel 10G X550T OS: Ubuntu 21.10, Kernel: 5.17.0-051700rc4daily20220219-generic (x86_64), Desktop: GNOME Shell 40.5, Display Server: X Server, Vulkan: 1.1.182, Compiler: GCC 11.2.0, File-System: ext4, Screen Resolution: 1024x768 perf-bench Benchmark: Epoll Wait ops/sec > Higher Is Better A .. 2352 |============================================================== AA . 2299 |============================================================= B .. 2572 |==================================================================== C .. 2062 |======================================================= perf-bench Benchmark: Futex Hash ops/sec > Higher Is Better A .. 2976792 |================================================================= AA . 2976712 |================================================================= B .. 2979134 |================================================================= C .. 2945494 |================================================================ perf-bench Benchmark: Memcpy 1MB GB/sec > Higher Is Better A .. 42.87 |================================================================= AA . 42.83 |================================================================= B .. 44.15 |=================================================================== C .. 42.93 |================================================================= perf-bench Benchmark: Memset 1MB GB/sec > Higher Is Better A .. 62.46 |================================================================== AA . 63.42 |=================================================================== B .. 63.79 |=================================================================== C .. 63.19 |================================================================== perf-bench Benchmark: Sched Pipe ops/sec > Higher Is Better A .. 345990 |================================================================= AA . 351368 |================================================================== B .. 346133 |================================================================= C .. 339461 |================================================================ perf-bench Benchmark: Futex Lock-Pi ops/sec > Higher Is Better A .. 77 |=================================================================== AA . 77 |=================================================================== B .. 80 |====================================================================== C .. 77 |=================================================================== perf-bench Benchmark: Syscall Basic ops/sec > Higher Is Better A .. 17051621 |================================================================ AA . 17052202 |================================================================ B .. 16941879 |================================================================ C .. 16924594 |================================================================ libavif avifenc 0.10 Encoder Speed: 0 Seconds < Lower Is Better A .. 69.46 |================================================================== AA . 69.41 |================================================================== B .. 70.33 |=================================================================== C .. 70.65 |=================================================================== libavif avifenc 0.10 Encoder Speed: 2 Seconds < Lower Is Better A .. 38.78 |================================================================== AA . 38.73 |================================================================== B .. 37.57 |================================================================ C .. 39.57 |=================================================================== libavif avifenc 0.10 Encoder Speed: 6 Seconds < Lower Is Better A .. 4.278 |=================================================================== AA . 4.093 |================================================================ B .. 3.986 |============================================================== C .. 4.215 |================================================================== libavif avifenc 0.10 Encoder Speed: 6, Lossless Seconds < Lower Is Better A .. 7.215 |================================================================ AA . 7.389 |================================================================== B .. 7.514 |=================================================================== C .. 7.185 |================================================================ libavif avifenc 0.10 Encoder Speed: 10, Lossless Seconds < Lower Is Better A .. 5.010 |================================================================ AA . 5.229 |=================================================================== B .. 5.197 |=================================================================== C .. 4.971 |================================================================ oneDNN 2.6 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better A .. 2.94158 |================================================== AA . 3.77920 |================================================================ B .. 3.18091 |====================================================== C .. 3.85444 |================================================================= oneDNN 2.6 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better A .. 2.63912 |================================================================= AA . 2.54811 |=============================================================== B .. 2.56643 |=============================================================== C .. 2.54404 |=============================================================== oneDNN 2.6 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A .. 4.05569 |======================================================= AA . 4.25865 |========================================================== B .. 4.77292 |================================================================= C .. 2.55861 |=================================== oneDNN 2.6 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A .. 0.747084 |=========================================================== AA . 0.815632 |================================================================ B .. 0.757826 |=========================================================== C .. 0.743010 |========================================================== oneDNN 2.6 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 2.6 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 2.6 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better A .. 0.705380 |================================================================ AA . 0.708812 |================================================================ B .. 0.684799 |============================================================== C .. 0.689583 |============================================================== oneDNN 2.6 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better A .. 11.24 |=================================================================== AA . 11.14 |================================================================== B .. 11.22 |=================================================================== C .. 11.19 |=================================================================== oneDNN 2.6 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better A .. 2.12767 |================================================================= AA . 2.10407 |================================================================ B .. 1.94632 |=========================================================== C .. 1.99639 |============================================================= oneDNN 2.6 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A .. 0.897288 |============================================== AA . 1.247010 |================================================================ B .. 0.928893 |================================================ C .. 0.784430 |======================================== oneDNN 2.6 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A .. 1.68391 |=========================================================== AA . 1.07515 |====================================== B .. 1.85300 |================================================================= C .. 1.23753 |=========================================== oneDNN 2.6 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A .. 0.878553 |============================================================== AA . 0.904662 |================================================================ B .. 0.803426 |========================================================= C .. 0.829217 |=========================================================== oneDNN 2.6 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better A .. 3874.18 |======================================================== AA . 4530.24 |================================================================= B .. 4336.25 |============================================================== C .. 4224.87 |============================================================= oneDNN 2.6 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better A .. 1693.03 |============================================================= AA . 1803.51 |================================================================= B .. 1810.37 |================================================================= C .. 1713.39 |============================================================== oneDNN 2.6 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A .. 3819.45 |====================================================== AA . 4416.22 |============================================================== B .. 4623.03 |================================================================= C .. 4390.23 |============================================================== oneDNN 2.6 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 2.6 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 2.6 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better oneDNN 2.6 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better A .. 1624.25 |==================================================== AA . 2016.94 |================================================================= B .. 1801.29 |========================================================== C .. 1696.60 |======================================================= oneDNN 2.6 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better A .. 11.51 |==================================== AA . 17.55 |====================================================== B .. 12.50 |======================================= C .. 21.67 |=================================================================== oneDNN 2.6 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better AA . 4276.70 |============================================================== B .. 4464.12 |================================================================= C .. 3862.48 |======================================================== oneDNN 2.6 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better AA . 1711.61 |================================================================ B .. 1734.92 |================================================================= C .. 1721.12 |================================================================ oneDNN 2.6 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better AA . 22.91 |===================================================== B .. 27.34 |=============================================================== C .. 29.10 |=================================================================== oneDNN 2.6 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better ONNX Runtime 1.11 Model: GPT-2 - Device: CPU - Executor: Parallel Inferences Per Minute > Higher Is Better AA . 1308 |==================================================================== B .. 1225 |================================================================ C .. 1242 |================================================================= ONNX Runtime 1.11 Model: GPT-2 - Device: CPU - Executor: Standard Inferences Per Minute > Higher Is Better AA . 13234 |=================================================================== B .. 13106 |================================================================== C .. 9094 |============================================== ONNX Runtime 1.11 Model: yolov4 - Device: CPU - Executor: Parallel Inferences Per Minute > Higher Is Better AA . 434 |===================================================================== B .. 436 |===================================================================== C .. 436 |===================================================================== ONNX Runtime 1.11 Model: yolov4 - Device: CPU - Executor: Standard Inferences Per Minute > Higher Is Better AA . 355 |===================================================================== B .. 291 |========================================================= C .. 316 |============================================================= ONNX Runtime 1.11 Model: bertsquad-12 - Device: CPU - Executor: Parallel Inferences Per Minute > Higher Is Better AA . 594 |===================================================================== B .. 592 |===================================================================== C .. 592 |===================================================================== ONNX Runtime 1.11 Model: bertsquad-12 - Device: CPU - Executor: Standard Inferences Per Minute > Higher Is Better AA . 540 |========================================================== B .. 643 |===================================================================== C .. 539 |========================================================== ONNX Runtime 1.11 Model: fcn-resnet101-11 - Device: CPU - Executor: Parallel Inferences Per Minute > Higher Is Better AA . 123 |==================================================================== B .. 123 |==================================================================== C .. 124 |===================================================================== ONNX Runtime 1.11 Model: fcn-resnet101-11 - Device: CPU - Executor: Standard Inferences Per Minute > Higher Is Better AA . 170 |===================================================================== B .. 158 |================================================================ C .. 152 |============================================================== ONNX Runtime 1.11 Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel Inferences Per Minute > Higher Is Better AA . 1225 |=================================================================== B .. 1235 |==================================================================== C .. 1229 |==================================================================== ONNX Runtime 1.11 Model: ArcFace ResNet-100 - Device: CPU - Executor: Standard Inferences Per Minute > Higher Is Better AA . 1194 |=============================================================== B .. 1244 |================================================================== C .. 1279 |==================================================================== ONNX Runtime 1.11 Model: super-resolution-10 - Device: CPU - Executor: Parallel Inferences Per Minute > Higher Is Better AA . 4320 |==================================================================== B .. 4242 |=================================================================== C .. 4233 |=================================================================== ONNX Runtime 1.11 Model: super-resolution-10 - Device: CPU - Executor: Standard Inferences Per Minute > Higher Is Better AA . 4626 |========================================= B .. 7762 |==================================================================== C .. 4488 |=======================================