2 x AMD EPYC 9654 96-Core testing with a AMD Titanite_4G (RTI1004D BIOS) and ASPEED on Clear Linux OS 38660 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 2303310-NE-AMDGENOAO60
amd-genoa-onednn-31
2 x AMD EPYC 9654 96-Core testing with a AMD Titanite_4G (RTI1004D BIOS) and ASPEED on Clear Linux OS 38660 via the Phoronix Test Suite.
,,"a","b","c"
Processor,,2 x AMD EPYC 9654 96-Core @ 2.40GHz (192 Cores / 384 Threads),2 x AMD EPYC 9654 96-Core @ 2.40GHz (192 Cores / 384 Threads),2 x AMD EPYC 9654 96-Core @ 2.40GHz (192 Cores / 384 Threads)
Motherboard,,AMD Titanite_4G (RTI1004D BIOS),AMD Titanite_4G (RTI1004D BIOS),AMD Titanite_4G (RTI1004D BIOS)
Chipset,,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4
Memory,,1520GB,1520GB,1520GB
Disk,,2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007,2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007,2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007
Graphics,,ASPEED,ASPEED,ASPEED
Network,,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe
OS,,Clear Linux OS 38660,Clear Linux OS 38660,Clear Linux OS 38660
Kernel,,6.2.8-1293.native (x86_64),6.2.8-1293.native (x86_64),6.2.8-1293.native (x86_64)
Display Server,,X Server,X Server,X Server
Compiler,,GCC 12.2.1 20230323 releases/gcc-12.2.0-616-g1b6b7f214c + Clang 15.0.7 + LLVM 15.0.7,GCC 12.2.1 20230323 releases/gcc-12.2.0-616-g1b6b7f214c + Clang 15.0.7 + LLVM 15.0.7,GCC 12.2.1 20230323 releases/gcc-12.2.0-616-g1b6b7f214c + Clang 15.0.7 + LLVM 15.0.7
File-System,,ext4,ext4,ext4
Screen Resolution,,800x600,800x600,800x600
,,"a","b","c"
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1302.83,1323.12,1357.36
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU (ms)",LIB,1297.60,1317.63,1424.56
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,999.384,1001.27,974.37
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,1007.475,1016.04,968.294
"oneDNN - Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,998.040,1022.78,985.498
"oneDNN - Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU (ms)",LIB,5.16295,5.56995,5.13421
"oneDNN - Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,3.80454,3.87903,4.61093
"oneDNN - Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,,1373.66,1347.87
"oneDNN - Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,3.81667,4.12976,3.98273
"oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.753564,0.816992,0.824101
"oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,1.54627,1.64919,1.66125
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,20.8426,20.6935,20.68
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,2.23356,2.22682,2.21262
"oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.923951,0.946937,0.911944
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,0.521813,0.547057,0.530342
"oneDNN - Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU (ms)",LIB,1.81517,1.75887,1.72273
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.362781,0.363114,0.360127
"oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,0.414999,0.408003,0.406869
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.282128,0.292579,0.277235
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,0.643195,0.640364,0.653813
"oneDNN - Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU (ms)",LIB,0.946786,0.952539,0.954284