tests Tests for a future article. AMD Ryzen 5 5500U testing with a NB01 TUXEDO Aura 15 Gen2 NL5xNU (1.07.11RTR1 BIOS) and AMD Lucienne 512MB on Tuxedo 22.04 via the Phoronix Test Suite.
HTML result view exported from: https://openbenchmarking.org/result/2403274-NE-TESTS040635&sor&grs .
tests Processor Motherboard Chipset Memory Disk Graphics Audio Network OS Kernel Desktop Display Server OpenGL Vulkan Compiler File-System Screen Resolution a b AMD Ryzen 5 5500U @ 4.06GHz (6 Cores / 12 Threads) NB01 TUXEDO Aura 15 Gen2 NL5xNU (1.07.11RTR1 BIOS) AMD Renoir/Cezanne 2 x 8GB DDR4-3200MT/s Samsung M471A1K43DB1-CWE Samsung SSD 970 EVO Plus 500GB AMD Lucienne 512MB (1800/1333MHz) AMD Renoir Radeon HD Audio Realtek RTL8111/8168/8211/8411 + Intel Wi-Fi 6 AX200 Tuxedo 22.04 6.5.0-10027-tuxedo (x86_64) KDE Plasma 5.27.10 X Server 1.21.1.4 4.6 Mesa 24.0.3-0tux2 (LLVM 15.0.7 DRM 3.54) 1.3.274 GCC 11.4.0 ext4 1920x1080 OpenBenchmarking.org Kernel Details - Transparent Huge Pages: madvise Compiler Details - --build=x86_64-linux-gnu --disable-vtable-verify --disable-werror --enable-bootstrap --enable-cet --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-gnu-unique-object --enable-languages=c,ada,c++,go,brig,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-link-serialization=2 --enable-multiarch --enable-multilib --enable-nls --enable-objc-gc=auto --enable-offload-targets=nvptx-none=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-nvptx/usr,amdgcn-amdhsa=/build/gcc-11-XeT9lY/gcc-11-11.4.0/debian/tmp-gcn/usr --enable-plugin --enable-shared --enable-threads=posix --host=x86_64-linux-gnu --program-prefix=x86_64-linux-gnu- --target=x86_64-linux-gnu --with-abi=m64 --with-arch-32=i686 --with-build-config=bootstrap-lto-lean --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-multilib-list=m32,m64,mx32 --with-target-system-zlib=auto --with-tune=generic --without-cuda-driver -v Processor Details - Scaling Governor: amd-pstate-epp powersave (EPP: balance_performance) - CPU Microcode: 0x8608103 Python Details - Python 3.10.12 Security Details - gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + retbleed: Mitigation of untrained return thunk; SMT enabled with STIBP protection + spec_rstack_overflow: Mitigation of Safe RET + 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 STIBP: always-on RSB filling PBRSB-eIBRS: Not affected + srbds: Not affected + tsx_async_abort: Not affected
tests pytorch: CPU - 1 - Efficientnet_v2_l pytorch: CPU - 256 - Efficientnet_v2_l blender: Pabellon Barcelona - CPU-Only tensorflow: CPU - 32 - VGG-16 pytorch: CPU - 512 - ResNet-152 pytorch: CPU - 16 - Efficientnet_v2_l blender: Barbershop - CPU-Only pytorch: CPU - 32 - Efficientnet_v2_l pytorch: CPU - 64 - Efficientnet_v2_l build-mesa: Time To Compile pytorch: CPU - 512 - Efficientnet_v2_l pytorch: CPU - 256 - ResNet-152 pytorch: CPU - 512 - ResNet-50 blender: Fishy Cat - CPU-Only tensorflow: CPU - 16 - VGG-16 pytorch: CPU - 16 - ResNet-152 pytorch: CPU - 1 - ResNet-152 tensorflow: CPU - 32 - GoogLeNet blender: Classroom - CPU-Only tensorflow: CPU - 16 - GoogLeNet pytorch: CPU - 1 - ResNet-50 tensorflow: CPU - 64 - ResNet-50 tensorflow: CPU - 16 - ResNet-50 pytorch: CPU - 32 - ResNet-50 tensorflow: CPU - 32 - AlexNet pytorch: CPU - 64 - ResNet-50 pytorch: CPU - 16 - ResNet-50 pytorch: CPU - 32 - ResNet-152 tensorflow: CPU - 16 - AlexNet tensorflow: CPU - 1 - AlexNet pytorch: CPU - 64 - ResNet-152 tensorflow: CPU - 1 - VGG-16 blender: BMW27 - CPU-Only tensorflow: CPU - 64 - AlexNet pytorch: CPU - 256 - ResNet-50 tensorflow: CPU - 1 - ResNet-50 tensorflow: CPU - 64 - GoogLeNet tensorflow: CPU - 256 - GoogLeNet tensorflow: CPU - 512 - AlexNet tensorflow: CPU - 32 - ResNet-50 tensorflow: CPU - 1 - GoogLeNet tensorflow: CPU - 256 - AlexNet a b 5.16 3.33 1067.46 3.27 5.23 3.43 3327.01 3.40 3.42 58.728 3.43 5.25 12.68 385.47 3.2 5.67 9.35 20.12 841.77 19.85 21.00 6.41 6.41 12.84 45.55 12.91 13.03 5.55 36.39 5.15 5.46 1.39 321.21 51.53 12.84 4.56 19.73 19.48 57.39 6.41 10.84 56.5 5.55 3.58 994.19 3.05 5.60 3.65 3128.57 3.60 3.62 62.049 3.60 5.50 12.21 372.08 3.09 5.50 9.15 20.52 827.48 20.19 21.31 6.32 6.5 13.01 44.96 12.75 13.19 5.49 36.02 5.1 5.51 1.38 319.31 51.25 12.90 4.54 19.8 19.53 57.5 6.42 10.83 56.55 OpenBenchmarking.org
PyTorch Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l b a 1.2488 2.4976 3.7464 4.9952 6.244 5.55 5.16 MIN: 5.16 / MAX: 5.76 MIN: 4.63 / MAX: 5.38
PyTorch Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l b a 0.8055 1.611 2.4165 3.222 4.0275 3.58 3.33 MIN: 3.45 / MAX: 3.76 MIN: 3.07 / MAX: 3.54
Blender Blend File: Pabellon Barcelona - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.1 Blend File: Pabellon Barcelona - Compute: CPU-Only b a 200 400 600 800 1000 994.19 1067.46
TensorFlow Device: CPU - Batch Size: 32 - Model: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: VGG-16 a b 0.7358 1.4716 2.2074 2.9432 3.679 3.27 3.05
PyTorch Device: CPU - Batch Size: 512 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 512 - Model: ResNet-152 b a 1.26 2.52 3.78 5.04 6.3 5.60 5.23 MIN: 4.7 / MAX: 5.82 MIN: 4.63 / MAX: 5.55
PyTorch Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l b a 0.8213 1.6426 2.4639 3.2852 4.1065 3.65 3.43 MIN: 3.29 / MAX: 3.78 MIN: 3.22 / MAX: 3.62
Blender Blend File: Barbershop - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.1 Blend File: Barbershop - Compute: CPU-Only b a 700 1400 2100 2800 3500 3128.57 3327.01
PyTorch Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l b a 0.81 1.62 2.43 3.24 4.05 3.60 3.40 MIN: 3.43 / MAX: 3.75 MIN: 3.17 / MAX: 3.52
PyTorch Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l b a 0.8145 1.629 2.4435 3.258 4.0725 3.62 3.42 MIN: 3.48 / MAX: 3.74 MIN: 3.31 / MAX: 3.62
Timed Mesa Compilation Time To Compile OpenBenchmarking.org Seconds, Fewer Is Better Timed Mesa Compilation 24.0 Time To Compile a b 14 28 42 56 70 58.73 62.05
PyTorch Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l b a 0.81 1.62 2.43 3.24 4.05 3.60 3.43 MIN: 3.45 / MAX: 3.74 MIN: 3.08 / MAX: 3.65
PyTorch Device: CPU - Batch Size: 256 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 256 - Model: ResNet-152 b a 1.2375 2.475 3.7125 4.95 6.1875 5.50 5.25 MIN: 5.23 / MAX: 5.75 MIN: 4.56 / MAX: 5.61
PyTorch Device: CPU - Batch Size: 512 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 512 - Model: ResNet-50 a b 3 6 9 12 15 12.68 12.21 MIN: 11.1 / MAX: 13.05 MIN: 11.73 / MAX: 12.93
Blender Blend File: Fishy Cat - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.1 Blend File: Fishy Cat - Compute: CPU-Only b a 80 160 240 320 400 372.08 385.47
TensorFlow Device: CPU - Batch Size: 16 - Model: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: VGG-16 a b 0.72 1.44 2.16 2.88 3.6 3.20 3.09
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-152 a b 1.2758 2.5516 3.8274 5.1032 6.379 5.67 5.50 MIN: 4.92 / MAX: 5.85 MIN: 4.52 / MAX: 5.67
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-152 a b 3 6 9 12 15 9.35 9.15 MIN: 8.95 / MAX: 9.56 MIN: 7.71 / MAX: 9.45
TensorFlow Device: CPU - Batch Size: 32 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: GoogLeNet b a 5 10 15 20 25 20.52 20.12
Blender Blend File: Classroom - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.1 Blend File: Classroom - Compute: CPU-Only b a 200 400 600 800 1000 827.48 841.77
TensorFlow Device: CPU - Batch Size: 16 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: GoogLeNet b a 5 10 15 20 25 20.19 19.85
PyTorch Device: CPU - Batch Size: 1 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 b a 5 10 15 20 25 21.31 21.00 MIN: 19.02 / MAX: 22.37 MIN: 18.97 / MAX: 22.06
TensorFlow Device: CPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 a b 2 4 6 8 10 6.41 6.32
TensorFlow Device: CPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 b a 2 4 6 8 10 6.50 6.41
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 b a 3 6 9 12 15 13.01 12.84 MIN: 10.31 / MAX: 13.63 MIN: 11.98 / MAX: 13.14
TensorFlow Device: CPU - Batch Size: 32 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: AlexNet a b 10 20 30 40 50 45.55 44.96
PyTorch Device: CPU - Batch Size: 64 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-50 a b 3 6 9 12 15 12.91 12.75 MIN: 12.22 / MAX: 13.13 MIN: 11.96 / MAX: 13.06
PyTorch Device: CPU - Batch Size: 16 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 16 - Model: ResNet-50 b a 3 6 9 12 15 13.19 13.03 MIN: 12.63 / MAX: 13.62 MIN: 10.67 / MAX: 13.24
PyTorch Device: CPU - Batch Size: 32 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 32 - Model: ResNet-152 a b 1.2488 2.4976 3.7464 4.9952 6.244 5.55 5.49 MIN: 5.27 / MAX: 5.69 MIN: 4.9 / MAX: 5.65
TensorFlow Device: CPU - Batch Size: 16 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 16 - Model: AlexNet a b 8 16 24 32 40 36.39 36.02
TensorFlow Device: CPU - Batch Size: 1 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: AlexNet a b 1.1588 2.3176 3.4764 4.6352 5.794 5.15 5.10
PyTorch Device: CPU - Batch Size: 64 - Model: ResNet-152 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 64 - Model: ResNet-152 b a 1.2398 2.4796 3.7194 4.9592 6.199 5.51 5.46 MIN: 4.73 / MAX: 5.69 MIN: 5.13 / MAX: 5.76
TensorFlow Device: CPU - Batch Size: 1 - Model: VGG-16 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: VGG-16 a b 0.3128 0.6256 0.9384 1.2512 1.564 1.39 1.38
Blender Blend File: BMW27 - Compute: CPU-Only OpenBenchmarking.org Seconds, Fewer Is Better Blender 4.1 Blend File: BMW27 - Compute: CPU-Only b a 70 140 210 280 350 319.31 321.21
TensorFlow Device: CPU - Batch Size: 64 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: AlexNet a b 12 24 36 48 60 51.53 51.25
PyTorch Device: CPU - Batch Size: 256 - Model: ResNet-50 OpenBenchmarking.org batches/sec, More Is Better PyTorch 2.2.1 Device: CPU - Batch Size: 256 - Model: ResNet-50 b a 3 6 9 12 15 12.90 12.84 MIN: 11.21 / MAX: 13.23 MIN: 11.4 / MAX: 13.12
TensorFlow Device: CPU - Batch Size: 1 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: ResNet-50 a b 1.026 2.052 3.078 4.104 5.13 4.56 4.54
TensorFlow Device: CPU - Batch Size: 64 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 64 - Model: GoogLeNet b a 5 10 15 20 25 19.80 19.73
TensorFlow Device: CPU - Batch Size: 256 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 256 - Model: GoogLeNet b a 5 10 15 20 25 19.53 19.48
TensorFlow Device: CPU - Batch Size: 512 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 512 - Model: AlexNet b a 13 26 39 52 65 57.50 57.39
TensorFlow Device: CPU - Batch Size: 32 - Model: ResNet-50 OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 32 - Model: ResNet-50 b a 2 4 6 8 10 6.42 6.41
TensorFlow Device: CPU - Batch Size: 1 - Model: GoogLeNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 1 - Model: GoogLeNet a b 3 6 9 12 15 10.84 10.83
TensorFlow Device: CPU - Batch Size: 256 - Model: AlexNet OpenBenchmarking.org images/sec, More Is Better TensorFlow 2.16.1 Device: CPU - Batch Size: 256 - Model: AlexNet b a 13 26 39 52 65 56.55 56.50
Phoronix Test Suite v10.8.5