tensorflow ryzen zen 4

AMD Ryzen 9 7950X3D 16-Core testing with a ASUS ROG CROSSHAIR X670E HERO (9927 BIOS) and AMD Radeon RX 7900 XTX on Ubuntu 23.04 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 2303296-PTS-TENSORFL70
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7600x a
March 29 2023
  1 Hour, 32 Minutes
7600x b
March 29 2023
  2 Hours, 22 Minutes
7950x3d a
March 29 2023
  48 Minutes
7950x3d b
March 29 2023
  48 Minutes
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tensorflow ryzen zen 4OpenBenchmarking.orgPhoronix Test SuiteAMD Ryzen 5 7600X 6-Core @ 4.70GHz (6 Cores / 12 Threads)AMD Ryzen 9 7950X3D 16-Core @ 4.20GHz (16 Cores / 32 Threads)ASUS ROG CROSSHAIR X670E HERO (9927 BIOS)AMD Device 14d832GBWestern Digital WD_BLACK SN850X 1000GB + 2000GBAMD Radeon RX 7900 XTX (2304/1249MHz)AMD Device ab30ASUS MG28UIntel I225-V + Intel Wi-Fi 6 AX210/AX211/AX411Ubuntu 23.046.2.8-060208-generic (x86_64)GNOME Shell 44.0X Server 1.21.1.7 + Wayland4.6 Mesa 23.1.0-devel (git-de8b14f 2023-03-24 lunar-oibaf-ppa) (LLVM 15.0.7 DRM 3.49)OpenCL 2.1 AMD-APP (3513.0)GCC 12.2.0ext43840x2160ProcessorsMotherboardChipsetMemoryDiskGraphicsAudioMonitorNetworkOSKernelDesktopDisplay ServerOpenGLOpenCLCompilerFile-SystemScreen ResolutionTensorflow Ryzen Zen 4 BenchmarksSystem Logs- Transparent Huge Pages: madvise- Scaling Governor: acpi-cpufreq performance (Boost: Enabled) - CPU Microcode: 0xa601203- Python 3.11.2- itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of usercopy/swapgs barriers and __user pointer sanitization + spectre_v2: Mitigation of Retpolines IBPB: conditional IBRS_FW STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected

7600x a7600x b7950x3d a7950x3d bResult OverviewPhoronix Test Suite100%138%175%213%250%BlenderBlenderBlenderBlenderBlenderTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowTensorFlowBarbershop - CPU-OnlyPabellon Barcelona - CPU-OnlyBMW27 - CPU-OnlyFishy Cat - CPU-OnlyClassroom - CPU-OnlyCPU - 512 - AlexNetCPU - 256 - AlexNetCPU - 64 - AlexNetCPU - 32 - GoogLeNetCPU - 64 - GoogLeNetCPU - 16 - GoogLeNetCPU - 32 - AlexNetCPU - 256 - GoogLeNetCPU - 512 - GoogLeNetCPU - 64 - ResNet-50CPU - 32 - ResNet-50CPU - 256 - ResNet-50CPU - 16 - ResNet-50CPU - 16 - AlexNet

tensorflow ryzen zen 4tensorflow: CPU - 16 - AlexNettensorflow: CPU - 32 - AlexNettensorflow: CPU - 64 - AlexNettensorflow: CPU - 256 - AlexNettensorflow: CPU - 512 - AlexNettensorflow: CPU - 16 - GoogLeNettensorflow: CPU - 16 - ResNet-50tensorflow: CPU - 32 - GoogLeNettensorflow: CPU - 32 - ResNet-50tensorflow: CPU - 64 - GoogLeNettensorflow: CPU - 64 - ResNet-50tensorflow: CPU - 256 - GoogLeNettensorflow: CPU - 256 - ResNet-50tensorflow: CPU - 512 - GoogLeNetblender: BMW27 - CPU-Onlyblender: Classroom - CPU-Onlyblender: Fishy Cat - CPU-Onlyblender: Barbershop - CPU-Onlyblender: Pabellon Barcelona - CPU-Only7600x a7600x b7950x3d a7950x3d b114.42145.54166.15186.23188.782.0827.8680.7327.8180.0527.6379.5427.5379.77127.87333.15163.191202.85411.84114.73145.45164.76186.31190.3081.9527.8580.7627.8079.9227.6679.6127.5479.77128.26333.68162.921202.67410.66176259.68340.13419.28430.57146.6943.14149.544.34145.144.16137.9543.85136.952.113666.56480.88167.38176.37258.45339.62418.85430.58146.4343.24149.6644.32145.1944.24137.7543.9136.9751.96135.866.16480.34166.53OpenBenchmarking.org

TensorFlow

This is a benchmark of the TensorFlow deep learning framework using the TensorFlow reference benchmarks (tensorflow/benchmarks with tf_cnn_benchmarks.py). Note with the Phoronix Test Suite there is also pts/tensorflow-lite for benchmarking the TensorFlow Lite binaries if desired for complementary metrics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: AlexNet7950x3d b7950x3d a7600x b7600x a4080120160200SE +/- 0.04, N = 3176.37176.00114.73114.42

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: AlexNet7950x3d a7950x3d b7600x a7600x b60120180240300SE +/- 0.21, N = 3259.68258.45145.54145.45

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: AlexNet7950x3d a7950x3d b7600x a7600x b70140210280350SE +/- 0.14, N = 3340.13339.62166.15164.76

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: AlexNet7950x3d a7950x3d b7600x b7600x a90180270360450SE +/- 0.42, N = 3419.28418.85186.31186.23

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: AlexNet7950x3d b7950x3d a7600x b7600x a90180270360450SE +/- 1.32, N = 3430.58430.57190.30188.70

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: GoogLeNet7950x3d a7950x3d b7600x a7600x b306090120150SE +/- 0.08, N = 3146.69146.4382.0881.95

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 16 - Model: ResNet-507950x3d b7950x3d a7600x a7600x b1020304050SE +/- 0.01, N = 343.2443.1427.8627.85

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: GoogLeNet7950x3d b7950x3d a7600x b7600x a306090120150SE +/- 0.02, N = 3149.66149.5080.7680.73

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 32 - Model: ResNet-507950x3d a7950x3d b7600x a7600x b1020304050SE +/- 0.01, N = 344.3444.3227.8127.80

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: GoogLeNet7950x3d b7950x3d a7600x a7600x b306090120150SE +/- 0.04, N = 3145.19145.1080.0579.92

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 64 - Model: ResNet-507950x3d b7950x3d a7600x b7600x a1020304050SE +/- 0.00, N = 344.2444.1627.6627.63

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: GoogLeNet7950x3d a7950x3d b7600x b7600x a306090120150SE +/- 0.05, N = 3137.95137.7579.6179.54

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 256 - Model: ResNet-507950x3d b7950x3d a7600x b7600x a102030405043.9043.8527.5427.53

OpenBenchmarking.orgimages/sec, More Is BetterTensorFlow 2.12Device: CPU - Batch Size: 512 - Model: GoogLeNet7950x3d b7950x3d a7600x b7600x a306090120150136.97136.9079.7779.77

Device: CPU - Batch Size: 512 - Model: ResNet-50

7600x a: The test quit with a non-zero exit status.

7600x b: The test quit with a non-zero exit status.

7950x3d a: The test quit with a non-zero exit status. E: Fatal Python error: Segmentation fault

7950x3d b: The test quit with a non-zero exit status. E: Fatal Python error: Segmentation fault

Blender

Blender is an open-source 3D creation and modeling software project. This test is of Blender's Cycles performance with various sample files. GPU computing via NVIDIA OptiX and NVIDIA CUDA is currently supported as well as HIP for AMD Radeon GPUs and Intel oneAPI for Intel Graphics. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.5Blend File: BMW27 - Compute: CPU-Only7950x3d b7950x3d a7600x a7600x b30609012015051.9652.10127.87128.26

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.5Blend File: Classroom - Compute: CPU-Only7950x3d b7950x3d a7600x a7600x b70140210280350135.80136.00333.15333.68

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.5Blend File: Fishy Cat - Compute: CPU-Only7950x3d b7950x3d a7600x b7600x a408012016020066.1666.56162.92163.19

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.5Blend File: Barbershop - Compute: CPU-Only7950x3d b7950x3d a7600x b7600x a30060090012001500480.34480.881202.671202.85

OpenBenchmarking.orgSeconds, Fewer Is BetterBlender 3.5Blend File: Pabellon Barcelona - Compute: CPU-Only7950x3d b7950x3d a7600x b7600x a90180270360450166.53167.38410.66411.84