EPYC 7502 AMD EPYC 7502 32-Core testing with a ASRockRack EPYCD8 (P2.10 BIOS) and llvmpipe on Ubuntu 20.10 via the Phoronix Test Suite. 1: Processor: AMD EPYC 7502 32-Core @ 2.50GHz (32 Cores / 64 Threads), Motherboard: ASRockRack EPYCD8 (P2.10 BIOS), Chipset: AMD Starship/Matisse, Memory: 126GB, Disk: 280GB INTEL SSDPED1D280GA, Graphics: llvmpipe, Audio: AMD Starship/Matisse, Monitor: VE228, Network: 2 x Intel I350 OS: Ubuntu 20.10, Kernel: 5.8.0-31-generic (x86_64), Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, Display Driver: modesetting 1.20.9, OpenGL: 4.5 Mesa 20.2.1 (LLVM 11.0.0 256 bits), Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1024x768 2: Processor: AMD EPYC 7502 32-Core @ 2.50GHz (32 Cores / 64 Threads), Motherboard: ASRockRack EPYCD8 (P2.10 BIOS), Chipset: AMD Starship/Matisse, Memory: 126GB, Disk: 280GB INTEL SSDPED1D280GA, Graphics: llvmpipe, Audio: AMD Starship/Matisse, Monitor: VE228, Network: 2 x Intel I350 OS: Ubuntu 20.10, Kernel: 5.8.0-31-generic (x86_64), Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, Display Driver: modesetting 1.20.9, OpenGL: 4.5 Mesa 20.2.1 (LLVM 11.0.0 256 bits), Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1080 3: Processor: AMD EPYC 7502 32-Core @ 2.50GHz (32 Cores / 64 Threads), Motherboard: ASRockRack EPYCD8 (P2.10 BIOS), Chipset: AMD Starship/Matisse, Memory: 126GB, Disk: 280GB INTEL SSDPED1D280GA, Graphics: llvmpipe, Audio: AMD Starship/Matisse, Monitor: VE228, Network: 2 x Intel I350 OS: Ubuntu 20.10, Kernel: 5.8.0-31-generic (x86_64), Desktop: GNOME Shell 3.38.1, Display Server: X Server 1.20.9, Display Driver: modesetting 1.20.9, OpenGL: 4.5 Mesa 20.2.1 (LLVM 11.0.0 256 bits), Compiler: GCC 10.2.0, File-System: ext4, Screen Resolution: 1920x1080 Compile Bench 0.6 Test: Compile MB/s > Higher Is Better 1 . 1826.99 |================================================================== 2 . 1840.71 |================================================================== 3 . 1831.66 |================================================================== Compile Bench 0.6 Test: Initial Create MB/s > Higher Is Better 1 . 529.46 |================================================================= 2 . 543.80 |=================================================================== 3 . 544.25 |=================================================================== Compile Bench 0.6 Test: Read Compiled Tree MB/s > Higher Is Better 1 . 2774.39 |================================================================== 2 . 2757.12 |================================================================= 3 . 2783.90 |================================================================== Timed HMMer Search 3.3.1 Pfam Database Search Seconds < Lower Is Better 1 . 176.77 |=================================================================== 2 . 176.86 |=================================================================== 3 . 176.75 |=================================================================== Timed MAFFT Alignment 7.471 Multiple Sequence Alignment - LSU RNA Seconds < Lower Is Better 1 . 10.41 |==================================================================== 2 . 10.32 |=================================================================== 3 . 10.26 |=================================================================== GraphicsMagick 1.3.33 Operation: Swirl Iterations Per Minute > Higher Is Better 1 . 1198 |===================================================================== 2 . 1194 |===================================================================== 3 . 1200 |===================================================================== GraphicsMagick 1.3.33 Operation: Rotate Iterations Per Minute > Higher Is Better 1 . 520 |===================================================================== 2 . 508 |==================================================================== 3 . 524 |====================================================================== GraphicsMagick 1.3.33 Operation: Sharpen Iterations Per Minute > Higher Is Better 1 . 372 |===================================================================== 2 . 372 |===================================================================== 3 . 375 |====================================================================== GraphicsMagick 1.3.33 Operation: Enhanced Iterations Per Minute > Higher Is Better 1 . 567 |====================================================================== 2 . 564 |====================================================================== 3 . 567 |====================================================================== GraphicsMagick 1.3.33 Operation: Resizing Iterations Per Minute > Higher Is Better 1 . 1767 |===================================================================== 2 . 1759 |===================================================================== 3 . 1769 |===================================================================== GraphicsMagick 1.3.33 Operation: Noise-Gaussian Iterations Per Minute > Higher Is Better 1 . 514 |====================================================================== 2 . 506 |===================================================================== 3 . 513 |====================================================================== GraphicsMagick 1.3.33 Operation: HWB Color Space Iterations Per Minute > Higher Is Better 1 . 1124 |==================================================================== 2 . 1101 |=================================================================== 3 . 1133 |===================================================================== oneDNN 2.0 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 1.59488 |================================================================== 2 . 1.60043 |================================================================== 3 . 1.59918 |================================================================== oneDNN 2.0 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 2.99323 |================================================================== 2 . 2.99882 |================================================================== 3 . 2.99084 |================================================================== oneDNN 2.0 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 1.18770 |================================================================== 2 . 1.18465 |================================================================== 3 . 1.18670 |================================================================== oneDNN 2.0 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 1.022320 |================================================================= 2 . 1.004974 |================================================================ 3 . 1.008960 |================================================================ oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 3.50587 |================================================================== 2 . 3.50799 |================================================================== 3 . 3.50153 |================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 2.13223 |================================================================== 2 . 2.12522 |================================================================== 3 . 2.13462 |================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 3.69957 |================================================================== 2 . 3.69580 |================================================================== 3 . 3.68999 |================================================================== oneDNN 2.0 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 4.02660 |================================================================== 2 . 3.99404 |================================================================= 3 . 4.00453 |================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2.21053 |================================================================== 2 . 2.20864 |================================================================== 3 . 2.21550 |================================================================== oneDNN 2.0 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 1.95466 |================================================================== 2 . 1.95672 |================================================================== 3 . 1.96404 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 2780.11 |================================================================== 2 . 2782.40 |================================================================== 3 . 2764.71 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 1006.15 |================================================================= 2 . 1014.80 |================================================================== 3 . 1011.41 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 2958.90 |================================================================== 2 . 2787.42 |============================================================== 3 . 2772.04 |============================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 1002.24 |================================================================ 2 . 996.48 |================================================================ 3 . 1026.04 |================================================================== oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU ms < Lower Is Better 1 . 0.538154 |================================================================= 2 . 0.541569 |================================================================= 3 . 0.541623 |================================================================= oneDNN 2.0 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 2782.71 |================================================================== 2 . 2790.87 |================================================================== 3 . 2772.14 |================================================================== oneDNN 2.0 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better 1 . 1023.25 |================================================================== 2 . 1012.52 |================================================================= 3 . 1022.60 |================================================================== oneDNN 2.0 Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better 1 . 1.17432 |================================================================== 2 . 1.17368 |================================================================== 3 . 1.17332 |================================================================== Coremark 1.0 CoreMark Size 666 - Iterations Per Second Iterations/Sec > Higher Is Better 1 . 1128026.26 |=============================================================== 2 . 1129442.35 |=============================================================== 3 . 1128056.11 |=============================================================== Timed FFmpeg Compilation 4.2.2 Time To Compile Seconds < Lower Is Better 1 . 26.17 |==================================================================== 2 . 26.26 |==================================================================== 3 . 26.23 |==================================================================== SQLite Speedtest 3.30 Timed Time - Size 1,000 Seconds < Lower Is Better 1 . 82.97 |================================================================== 2 . 84.92 |==================================================================== 3 . 83.41 |=================================================================== Apache Siege 2.4.29 Concurrent Users: 10 Transactions Per Second > Higher Is Better 1 . 19503.99 |=============================================================== 2 . 20108.13 |================================================================= Apache Siege 2.4.29 Concurrent Users: 50 Transactions Per Second > Higher Is Better 1 . 29285.90 |================================================================= 2 . 29257.88 |================================================================= Apache Siege 2.4.29 Concurrent Users: 100 Transactions Per Second > Higher Is Better 1 . 30541.45 |================================================================= 2 . 30529.88 |================================================================= Apache Siege 2.4.29 Concurrent Users: 200 Transactions Per Second > Higher Is Better 1 . 33062.47 |================================================================= 2 . 32895.05 |================================================================= Apache Siege 2.4.29 Concurrent Users: 250 Transactions Per Second > Higher Is Better 1 . 37395.23 |================================================================= 2 . 34655.33 |============================================================ Apache Siege 2.4.29 Concurrent Users: 500 Transactions Per Second > Higher Is Better 1 . 46298.75 |================================================================= BRL-CAD 7.30.8 VGR Performance Metric VGR Performance Metric > Higher Is Better 1 . 362291 |===================================================================