Tests for a future article. Intel Core i9-10980XE testing with a ASRock X299 Steel Legend (P1.50 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 2401111-PTS-FG69231050
fg
Tests for a future article. Intel Core i9-10980XE testing with a ASRock X299 Steel Legend (P1.50 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 (P1.50 BIOS),ASRock X299 Steel Legend (P1.50 BIOS)
Chipset,,Intel Sky Lake-E DMI3 Registers,Intel Sky Lake-E DMI3 Registers
Memory,,4 x 8 GB 3600MT/s,4 x 8 GB 3600MT/s
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,,6.2.0-39-generic (x86_64),6.2.0-39-generic (x86_64)
Desktop,,GNOME Shell 42.2,GNOME Shell 42.2
Display Server,,X Server 1.21.1.4,X Server 1.21.1.4
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"
"Quicksilver - Input: CORAL2 P2 (Figure Of Merit)",HIB,10310000,10700000
"Quicksilver - Input: CTS2 (Figure Of Merit)",HIB,12400000,12420000
"TensorFlow - Device: CPU - Batch Size: 16 - Model: VGG-16 (images/sec)",HIB,13.92,13.68
"CacheBench - Test: Read / Modify / Write (MB/s)",HIB,102291.247696,104862.243767
"CacheBench - Test: Write (MB/s)",HIB,34706.645719,34716.737299
"CacheBench - Test: Read (MB/s)",HIB,9086.408264,9090.522649
"Quicksilver - Input: CORAL2 P1 (Figure Of Merit)",HIB,13720000,13460000
"Speedb - Test: Random Fill Sync (Op/s)",HIB,5791,5755
"TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,31.31,30.91
"Speedb - Test: Update Random (Op/s)",HIB,518065,518444
"Speedb - Test: Random Fill (Op/s)",HIB,700951,697334
"Speedb - Test: Read While Writing (Op/s)",HIB,4762697,4899297
"Speedb - Test: Read Random Write Random (Op/s)",HIB,2159010,2156356
"Speedb - Test: Random Read (Op/s)",HIB,77800094,78077376
"Llama.cpp - Model: llama-2-13b.Q4_0.gguf (Tokens/sec)",HIB,9.68,9.9
"Speedb - Test: Sequential Fill (Op/s)",HIB,749586,735121
"Y-Cruncher - Pi Digits To Calculate: 1B (sec)",LIB,24.082,25.382
"TensorFlow - Device: CPU - Batch Size: 1 - Model: VGG-16 (images/sec)",HIB,4.87,4.67
"TensorFlow - Device: CPU - Batch Size: 1 - Model: ResNet-50 (images/sec)",HIB,7.68,7.8
"TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,117.54,115.71
"Llama.cpp - Model: llama-2-7b.Q4_0.gguf (Tokens/sec)",HIB,18.35,17.79
"TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,150.54,142.73
"Y-Cruncher - Pi Digits To Calculate: 500M (sec)",LIB,10.62,11.284
"TensorFlow - Device: CPU - Batch Size: 1 - Model: AlexNet (images/sec)",HIB,14.42,13.74
"TensorFlow - Device: CPU - Batch Size: 1 - Model: GoogLeNet (images/sec)",HIB,37.63,36.97
"PyTorch - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l (batches/sec)",HIB,,
"PyTorch - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l (batches/sec)",HIB,,
"PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-50 (batches/sec)",HIB,,
"PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-152 (batches/sec)",HIB,,
"PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-152 (batches/sec)",HIB,,
"PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-50 (batches/sec)",HIB,,