Tests for a future article. 2 x AMD EPYC 7773X 64-Core testing with a AMD DAYTONA_X (RYM1009B BIOS) and ASPEED on Ubuntu 20.04 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 2212247-NE-EPYCMILAN08
epyc milan x xmas
Tests for a future article. 2 x AMD EPYC 7773X 64-Core testing with a AMD DAYTONA_X (RYM1009B BIOS) and ASPEED on Ubuntu 20.04 via the Phoronix Test Suite.
a:
Processor: 2 x AMD EPYC 7773X 64-Core @ 2.20GHz (128 Cores / 256 Threads), Motherboard: AMD DAYTONA_X (RYM1009B BIOS), Chipset: AMD Starship/Matisse, Memory: 512GB, Disk: 800GB INTEL SSDPF21Q800GB, Graphics: ASPEED, Monitor: VE228, Network: 2 x Mellanox MT27710
OS: Ubuntu 20.04, Kernel: 6.1.0-rc8-phx (x86_64), Display Server: X Server, Vulkan: 1.1.182, Compiler: GCC 9.4.0, File-System: ext4, Screen Resolution: 1920x1080
b:
Processor: 2 x AMD EPYC 7773X 64-Core @ 2.20GHz (128 Cores / 256 Threads), Motherboard: AMD DAYTONA_X (RYM1009B BIOS), Chipset: AMD Starship/Matisse, Memory: 512GB, Disk: 800GB INTEL SSDPF21Q800GB, Graphics: ASPEED, Monitor: VE228, Network: 2 x Mellanox MT27710
OS: Ubuntu 20.04, Kernel: 6.1.0-rc8-phx (x86_64), Display Server: X Server, Vulkan: 1.1.182, Compiler: GCC 9.4.0, File-System: ext4, Screen Resolution: 1920x1080
OpenVKL 1.3.1
Benchmark: vklBenchmark ISPC
Items / Sec > Higher Is Better
a . 622 |==================================================================
b . 664 |======================================================================
OpenVKL 1.3.1
Benchmark: vklBenchmark Scalar
Items / Sec > Higher Is Better
a . 456 |======================================================================
b . 440 |====================================================================
Timed Linux Kernel Compilation 6.1
Build: allmodconfig
Seconds < Lower Is Better
a . 177.98 |===================================================================
b . 177.40 |===================================================================
CockroachDB 22.2
Workload: KV, 10% Reads - Concurrency: 1024
ops/s > Higher Is Better
a . 47190.8 |===============================================================
b . 49337.7 |==================================================================
CockroachDB 22.2
Workload: KV, 50% Reads - Concurrency: 1024
ops/s > Higher Is Better
a . 64847.1 |==================================================================
b . 59441.5 |============================================================
CockroachDB 22.2
Workload: KV, 60% Reads - Concurrency: 1024
ops/s > Higher Is Better
a . 70580.2 |==================================================================
b . 70896.9 |==================================================================
CockroachDB 22.2
Workload: KV, 60% Reads - Concurrency: 512
ops/s > Higher Is Better
a . 72451.2 |=================================================================
b . 73171.5 |==================================================================
CockroachDB 22.2
Workload: KV, 95% Reads - Concurrency: 1024
ops/s > Higher Is Better
a . 88959.2 |==================================================================
b . 88708.4 |==================================================================
CockroachDB 22.2
Workload: KV, 10% Reads - Concurrency: 512
ops/s > Higher Is Better
a . 49998.2 |================================================================
b . 51201.0 |==================================================================
CockroachDB 22.2
Workload: KV, 50% Reads - Concurrency: 512
ops/s > Higher Is Better
a . 69331.1 |==================================================================
b . 69785.0 |==================================================================
CockroachDB 22.2
Workload: KV, 95% Reads - Concurrency: 512
ops/s > Higher Is Better
a . 72081.8 |=====================================================
b . 89654.1 |==================================================================
CockroachDB 22.2
Workload: KV, 10% Reads - Concurrency: 256
ops/s > Higher Is Better
a . 51117.2 |==================================================================
b . 49348.6 |================================================================
CockroachDB 22.2
Workload: KV, 60% Reads - Concurrency: 256
ops/s > Higher Is Better
a . 74632.2 |==================================================================
b . 73457.7 |=================================================================
CockroachDB 22.2
Workload: KV, 50% Reads - Concurrency: 256
ops/s > Higher Is Better
a . 68275.7 |=================================================================
b . 69421.4 |==================================================================
CockroachDB 22.2
Workload: KV, 95% Reads - Concurrency: 256
ops/s > Higher Is Better
a . 88931.9 |=================================================================
b . 90275.6 |==================================================================
CockroachDB 22.2
Workload: KV, 50% Reads - Concurrency: 128
ops/s > Higher Is Better
a . 64904.1 |===============================================================
b . 67808.6 |==================================================================
CockroachDB 22.2
Workload: KV, 10% Reads - Concurrency: 128
ops/s > Higher Is Better
a . 49496.0 |================================================================
b . 51045.1 |==================================================================
CockroachDB 22.2
Workload: KV, 60% Reads - Concurrency: 128
ops/s > Higher Is Better
a . 70821.7 |=================================================================
b . 71858.8 |==================================================================
CockroachDB 22.2
Workload: KV, 95% Reads - Concurrency: 128
ops/s > Higher Is Better
a . 87221.5 |==================================================================
b . 75051.9 |=========================================================
CockroachDB 22.2
Workload: MoVR - Concurrency: 1024
ops/s > Higher Is Better
a . 765.6 |====================================================================
b . 768.3 |====================================================================
CockroachDB 22.2
Workload: MoVR - Concurrency: 256
ops/s > Higher Is Better
a . 764.1 |====================================================================
b . 758.9 |====================================================================
CockroachDB 22.2
Workload: MoVR - Concurrency: 128
ops/s > Higher Is Better
a . 767 |======================================================================
b . 763 |======================================================================
CockroachDB 22.2
Workload: MoVR - Concurrency: 512
ops/s > Higher Is Better
a . 772.7 |====================================================================
b . 765.3 |===================================================================
Numenta Anomaly Benchmark 1.1
Detector: KNN CAD
Seconds < Lower Is Better
a . 88.69 |===================================================================
b . 89.54 |====================================================================
oneDNN 3.0
Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 1579.22 |=============================================================
b . 1700.59 |==================================================================
oneDNN 3.0
Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 1685.58 |==================================================================
b . 1680.10 |==================================================================
oneDNN 3.0
Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 1920.66 |==================================================================
b . 1863.81 |================================================================
oneDNN 3.0
Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 1473.67 |==================================================================
b . 1176.84 |=====================================================
oneDNN 3.0
Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 1372.40 |==============================================================
b . 1471.68 |==================================================================
oneDNN 3.0
Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU
ms < Lower Is Better
a . 1448.33 |==================================================================
b . 1298.93 |===========================================================
Numenta Anomaly Benchmark 1.1
Detector: Earthgecko Skyline
Seconds < Lower Is Better
a . 73.63 |====================================================================
b . 73.31 |====================================================================
OpenVINO 2022.3
Model: Person Detection FP16 - Device: CPU
ms < Lower Is Better
a . 2028.30 |=================================================================
b . 2051.22 |==================================================================
OpenVINO 2022.3
Model: Person Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 15.55 |====================================================================
b . 15.43 |===================================================================
OpenVINO 2022.3
Model: Face Detection FP16 - Device: CPU
ms < Lower Is Better
a . 1414.79 |================================================================
b . 1448.08 |==================================================================
OpenVINO 2022.3
Model: Face Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 22.35 |====================================================================
b . 21.95 |===================================================================
OpenVINO 2022.3
Model: Person Detection FP32 - Device: CPU
ms < Lower Is Better
a . 2047.78 |==================================================================
b . 2040.99 |==================================================================
OpenVINO 2022.3
Model: Person Detection FP32 - Device: CPU
FPS > Higher Is Better
a . 15.46 |====================================================================
b . 15.51 |====================================================================
OpenVINO 2022.3
Model: Face Detection FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 571.16 |===================================================================
b . 570.36 |===================================================================
OpenVINO 2022.3
Model: Face Detection FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 55.77 |====================================================================
b . 55.87 |====================================================================
OpenVINO 2022.3
Model: Machine Translation EN To DE FP16 - Device: CPU
ms < Lower Is Better
a . 114.89 |===================================================================
b . 115.44 |===================================================================
OpenVINO 2022.3
Model: Machine Translation EN To DE FP16 - Device: CPU
FPS > Higher Is Better
a . 278.21 |===================================================================
b . 276.86 |===================================================================
OpenVINO 2022.3
Model: Person Vehicle Bike Detection FP16 - Device: CPU
ms < Lower Is Better
a . 9.89 |=====================================================================
b . 9.90 |=====================================================================
OpenVINO 2022.3
Model: Person Vehicle Bike Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 3231.85 |==================================================================
b . 3229.45 |==================================================================
OpenVINO 2022.3
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 1.52 |=====================================================================
b . 1.52 |=====================================================================
OpenVINO 2022.3
Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 83051.23 |=================================================================
b . 82943.37 |=================================================================
OpenVINO 2022.3
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 22.23 |====================================================================
b . 22.24 |====================================================================
OpenVINO 2022.3
Model: Weld Porosity Detection FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 5753.13 |==================================================================
b . 5750.27 |==================================================================
OpenVINO 2022.3
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
ms < Lower Is Better
a . 1.64 |=====================================================================
b . 1.64 |=====================================================================
OpenVINO 2022.3
Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU
FPS > Higher Is Better
a . 76694.48 |=================================================================
b . 77006.49 |=================================================================
OpenVINO 2022.3
Model: Vehicle Detection FP16-INT8 - Device: CPU
ms < Lower Is Better
a . 8.51 |=====================================================================
b . 8.51 |=====================================================================
OpenVINO 2022.3
Model: Vehicle Detection FP16-INT8 - Device: CPU
FPS > Higher Is Better
a . 3755.03 |==================================================================
b . 3756.88 |==================================================================
OpenVINO 2022.3
Model: Vehicle Detection FP16 - Device: CPU
ms < Lower Is Better
a . 13.72 |====================================================================
b . 13.68 |====================================================================
OpenVINO 2022.3
Model: Vehicle Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 2329.23 |==================================================================
b . 2337.11 |==================================================================
OpenVINO 2022.3
Model: Weld Porosity Detection FP16 - Device: CPU
ms < Lower Is Better
a . 13.09 |====================================================================
b . 13.09 |====================================================================
OpenVINO 2022.3
Model: Weld Porosity Detection FP16 - Device: CPU
FPS > Higher Is Better
a . 2442.86 |==================================================================
b . 2442.72 |==================================================================
Numenta Anomaly Benchmark 1.1
Detector: Contextual Anomaly Detector OSE
Seconds < Lower Is Better
a . 44.56 |====================================================================
b . 44.29 |====================================================================
Timed Linux Kernel Compilation 6.1
Build: defconfig
Seconds < Lower Is Better
a . 24.03 |====================================================================
b . 23.96 |====================================================================
oneDNN 3.0
Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 27.48 |====================================================================
b . 27.24 |===================================================================
oneDNN 3.0
Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 1.03703 |==================================================================
b . 1.04002 |==================================================================
oneDNN 3.0
Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 2.29566 |==================================================================
b . 2.24618 |=================================================================
oneDNN 3.0
Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 1.57840 |==================================================================
b . 1.57114 |==================================================================
oneDNN 3.0
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 2.68287 |==================================================================
b . 2.66346 |==================================================================
oneDNN 3.0
Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 2.56092 |================================================================
b . 2.63047 |==================================================================
oneDNN 3.0
Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 1.83730 |==================================================================
b . 1.83852 |==================================================================
oneDNN 3.0
Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 0.967326 |=================================================================
b . 0.937745 |===============================================================
oneDNN 3.0
Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 0.589938 |=================================================================
b . 0.576758 |================================================================
oneDNN 3.0
Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 0.583512 |===================================================
b . 0.746936 |=================================================================
Numenta Anomaly Benchmark 1.1
Detector: Windowed Gaussian
Seconds < Lower Is Better
a . 5.491 |====================================================================
b . 5.493 |====================================================================
oneDNN 3.0
Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU
ms < Lower Is Better
a . 3.49280 |=================================================================
b . 3.54446 |==================================================================
oneDNN 3.0
Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU
ms < Lower Is Better
a . 0.717443 |=================================================================
b . 0.696358 |===============================================================