kubuntu-2404-nvme

ARMv8 Cortex-A76 testing with a Raspberry Pi 5 Model B Rev 1.0 and V3D 7.1.7 8GB on Ubuntu 24.04 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 2411044-NE-KUBUNTU2446
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ARMv8 Cortex-A76
September 27
  1 Day, 20 Minutes
V3D 7.1.7
November 04
  9 Minutes
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kubuntu-2404-nvmeProcessorMotherboardChipsetMemoryDiskGraphicsMonitorNetworkOSKernelDesktopDisplay ServerOpenGLFile-SystemScreen ResolutionCompilerARMv8 Cortex-A76V3D 7.1.7ARMv8 Cortex-A76 @ 2.40GHz (4 Cores)Raspberry Pi 5 Model B Rev 1.0Broadcom BCM27128GB500GB KINGSTON SNV2S500GV3D 7.1.7 8GBPA247CVRaspberry Pi RP1 PCIe 2.0 South BridgeUbuntu 24.046.8.0-1012-raspi (aarch64)KDE Plasma 5.27.11X Server 1.21.1.113.1 Mesa 24.0.9-0ubuntu0.1ext41920x1080500GB KINGSTON SNV2S500G + 62GB DataTraveler 3.06.8.0-1013-raspi (aarch64)3.1 Mesa 24.0.9-0ubuntu0.2GCC 13.2.0OpenBenchmarking.orgKernel Details- Transparent Huge Pages: madviseProcessor Details- Scaling Governor: cpufreq-dt ondemandSecurity Details- gather_data_sampling: Not affected + itlb_multihit: Not affected + l1tf: Not affected + mds: Not affected + meltdown: Not affected + mmio_stale_data: Not affected + reg_file_data_sampling: Not affected + retbleed: Not affected + spec_rstack_overflow: Not affected + spec_store_bypass: Mitigation of SSB disabled via prctl + spectre_v1: Mitigation of __user pointer sanitization + spectre_v2: Mitigation of CSV2 BHB + srbds: Not affected + tsx_async_abort: Not affected Compiler Details- V3D 7.1.7: --build=aarch64-linux-gnu --disable-libquadmath --disable-libquadmath-support --disable-werror --enable-checking=release --enable-clocale=gnu --enable-default-pie --enable-fix-cortex-a53-843419 --enable-gnu-unique-object --enable-languages=c,ada,c++,go,d,fortran,objc,obj-c++,m2 --enable-libphobos-checking=release --enable-libstdcxx-backtrace --enable-libstdcxx-debug --enable-libstdcxx-time=yes --enable-multiarch --enable-nls --enable-objc-gc=auto --enable-offload-defaulted --enable-offload-targets=nvptx-none=/build/gcc-13-dIwDw0/gcc-13-13.2.0/debian/tmp-nvptx/usr --enable-plugin --enable-shared --enable-threads=posix --host=aarch64-linux-gnu --program-prefix=aarch64-linux-gnu- --target=aarch64-linux-gnu --with-default-libstdcxx-abi=new --with-gcc-major-version-only --with-target-system-zlib=auto --without-cuda-driver -v

kubuntu-2404-nvmebuild-apache: Time To Compilebuild-ffmpeg: Time To Compilemnn: nasnetmnn: mobilenetV3mnn: squeezenetv1.1mnn: resnet-v2-50mnn: SqueezeNetV1.0mnn: MobileNetV2_224mnn: mobilenet-v1-1.0mnn: inception-v3ncnn: CPU - mobilenetncnn: CPU-v2-v2 - mobilenet-v2ncnn: CPU-v3-v3 - mobilenet-v3ncnn: CPU - shufflenet-v2ncnn: CPU - mnasnetncnn: CPU - efficientnet-b0ncnn: CPU - blazefacencnn: CPU - googlenetncnn: CPU - vgg16ncnn: CPU - resnet18ncnn: CPU - alexnetncnn: CPU - resnet50ncnn: CPUv2-yolov3v2-yolov3 - mobilenetv2-yolov3ncnn: CPU - yolov4-tinyncnn: CPU - squeezenet_ssdncnn: CPU - regnety_400mncnn: CPU - vision_transformerncnn: CPU - FastestDetncnn: Vulkan GPU - mobilenetncnn: Vulkan GPU-v2-v2 - mobilenet-v2ncnn: Vulkan GPU-v3-v3 - mobilenet-v3ncnn: Vulkan GPU - shufflenet-v2ncnn: Vulkan GPU - mnasnetncnn: Vulkan GPU - efficientnet-b0ncnn: Vulkan GPU - blazefacencnn: Vulkan GPU - googlenetncnn: Vulkan GPU - vgg16ncnn: Vulkan GPU - resnet18ncnn: Vulkan GPU - alexnetncnn: Vulkan GPU - resnet50ncnn: Vulkan GPUv2-yolov3v2-yolov3 - mobilenetv2-yolov3ncnn: Vulkan GPU - yolov4-tinyncnn: Vulkan GPU - squeezenet_ssdncnn: Vulkan GPU - regnety_400mncnn: Vulkan GPU - vision_transformerncnn: Vulkan GPU - FastestDetopencv: DNN - Deep Neural Networkopencv: Features 2Dopencv: Object Detectionopencv: Coreopencv: Image Processingopencv: Stitchingopencv: Videorbenchmark: numpy: tensorflow-lite: Mobilenet Floattensorflow-lite: Mobilenet Quanttensorflow-lite: NASNet Mobiletensorflow-lite: SqueezeNettensorflow-lite: Inception ResNet V2tensorflow-lite: Inception V4onednn: Convolution Batch Shapes Auto - CPUonednn: Deconvolution Batch shapes_1d - CPUonednn: Deconvolution Batch shapes_3d - CPUonednn: IP Shapes 1D - CPUonednn: IP Shapes 3D - CPUonednn: Recurrent Neural Network Training - CPUonednn: Recurrent Neural Network Inference - CPUonnx: yolov4 - CPU - Parallelonnx: yolov4 - CPU - Parallelonnx: fcn-resnet101-11 - CPU - Parallelonnx: fcn-resnet101-11 - CPU - Parallelonnx: super-resolution-10 - CPU - Parallelonnx: super-resolution-10 - CPU - Parallelonnx: ResNet50 v1-12-int8 - CPU - Parallelonnx: ResNet50 v1-12-int8 - CPU - Parallelonnx: CaffeNet 12-int8 - CPU - Parallelonnx: CaffeNet 12-int8 - CPU - Parallelonnx: T5 Encoder - CPU - Parallelonnx: T5 Encoder - CPU - Parallelonnx: ZFNet-512 - CPU - Parallelonnx: ZFNet-512 - CPU - Parallelonnx: ResNet101_DUC_HDC-12 - CPU - Parallelonnx: ResNet101_DUC_HDC-12 - CPU - Parallelwhisper-cpp: ggml-base.en - 2016 State of the Unionwhisper-cpp: ggml-small.en - 2016 State of the Unionwhisper-cpp: ggml-medium.en - 2016 State of the Unionwhisperfile: Tinywhisperfile: Smallwhisperfile: Mediumllama-cpp: Meta-Llama-3-8B-Instruct-Q8_0.ggufllamafile: mistral-7b-instruct-v0.2.Q5_K_M - CPUllamafile: mistral-7b-instruct-v0.2.Q5_K_M - GPU AUTOllamafile: TinyLlama-1.1B-Chat-v1.0.BF16 - CPUllamafile: TinyLlama-1.1B-Chat-v1.0.BF16 - GPU AUTOllamafile: llava-v1.6-mistral-7b.Q8_0 - CPUllamafile: llava-v1.6-mistral-7b.Q8_0 - GPU AUTOxnnpack: FP32MobileNetV2xnnpack: FP32MobileNetV3Largexnnpack: FP32MobileNetV3Smallxnnpack: FP16MobileNetV2xnnpack: FP16MobileNetV3Largexnnpack: FP16MobileNetV3Smallxnnpack: QU8MobileNetV2xnnpack: QU8MobileNetV3Largexnnpack: QU8MobileNetV3Smallvkmark: 800 x 600 - Mailboxvkmark: 1024 x 768 - Mailboxvkmark: 1280 x 1024 - Mailboxvkmark: 1920 x 1080 - MailboxARMv8 Cortex-A76V3D 7.1.7104.932462.72528.9073.97514.305122.55730.06814.9621.55150.3848.6613.9410.083.839.1615.991.5734.79163.1424.9525.6957.9448.6657.2143.1112.82627.866.3248.8314.129.763.979.1316.061.934.49163.3225.0125.8958.3148.8357.0542.5112.86629.586.13472235240888614432814706282644394951618590.6038136.8518684.65774.2452846.626872.6215253246550264.111560.132103.12258.65262.980265557.735072.30.5335761874.140.1004199958.278.69434115.01112.497480.010945.173922.131916.90759.14199.59958104.1650.043207223144.3646.2341928.494125899.9365332.120881779.118625162.4460.121.891.88154.381.961.95205222035474921016610478404611904103383337467302192131OpenBenchmarking.org

Timed Apache Compilation

This test times how long it takes to build the Apache HTTPD web server. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed Apache Compilation 2.4.41Time To CompileARMv8 Cortex-A7620406080100104.93

Timed FFmpeg Compilation

This test times how long it takes to build the FFmpeg multimedia library. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterTimed FFmpeg Compilation 7.0Time To CompileARMv8 Cortex-A76100200300400500462.73

Mobile Neural Network

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.9.b11b7037dModel: nasnetARMv8 Cortex-A7671421283528.91MIN: 26.83 / MAX: 75.521. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.9.b11b7037dModel: mobilenetV3ARMv8 Cortex-A760.89441.78882.68323.57764.4723.975MIN: 3.66 / MAX: 12.571. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.9.b11b7037dModel: squeezenetv1.1ARMv8 Cortex-A764812162014.31MIN: 13.36 / MAX: 34.421. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.9.b11b7037dModel: resnet-v2-50ARMv8 Cortex-A76306090120150122.56MIN: 112.59 / MAX: 278.691. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.9.b11b7037dModel: SqueezeNetV1.0ARMv8 Cortex-A7671421283530.07MIN: 28.25 / MAX: 64.531. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.9.b11b7037dModel: MobileNetV2_224ARMv8 Cortex-A764812162014.96MIN: 13.95 / MAX: 32.711. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.9.b11b7037dModel: mobilenet-v1-1.0ARMv8 Cortex-A7651015202521.55MIN: 20.1 / MAX: 44.011. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -pthread -ldl

OpenBenchmarking.orgms, Fewer Is BetterMobile Neural Network 2.9.b11b7037dModel: inception-v3ARMv8 Cortex-A76306090120150150.38MIN: 141.2 / MAX: 217.081. (CXX) g++ options: -std=c++11 -O3 -fvisibility=hidden -fomit-frame-pointer -fstrict-aliasing -ffunction-sections -fdata-sections -ffast-math -fno-rtti -fno-exceptions -pthread -ldl

NCNN

NCNN is a high performance neural network inference framework optimized for mobile and other platforms developed by Tencent. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: mobilenetARMv8 Cortex-A76112233445548.66MIN: 45.43 / MAX: 106.551. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU-v2-v2 - Model: mobilenet-v2ARMv8 Cortex-A764812162013.94MIN: 12.76 / MAX: 75.481. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU-v3-v3 - Model: mobilenet-v3ARMv8 Cortex-A76369121510.08MIN: 9.01 / MAX: 81.441. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: shufflenet-v2ARMv8 Cortex-A760.86181.72362.58543.44724.3093.83MIN: 3.41 / MAX: 68.921. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: mnasnetARMv8 Cortex-A7636912159.16MIN: 8.33 / MAX: 41.871. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: efficientnet-b0ARMv8 Cortex-A764812162015.99MIN: 14.54 / MAX: 78.11. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: blazefaceARMv8 Cortex-A760.35330.70661.05991.41321.76651.57MIN: 1.5 / MAX: 8.761. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: googlenetARMv8 Cortex-A7681624324034.79MIN: 32.19 / MAX: 113.231. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: vgg16ARMv8 Cortex-A764080120160200163.14MIN: 155.59 / MAX: 207.561. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: resnet18ARMv8 Cortex-A7661218243024.95MIN: 23.29 / MAX: 74.281. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: alexnetARMv8 Cortex-A7661218243025.69MIN: 24.31 / MAX: 55.131. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: resnet50ARMv8 Cortex-A76132639526557.94MIN: 53.77 / MAX: 1151. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPUv2-yolov3v2-yolov3 - Model: mobilenetv2-yolov3ARMv8 Cortex-A76112233445548.66MIN: 45.43 / MAX: 106.551. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: yolov4-tinyARMv8 Cortex-A76132639526557.21MIN: 54.26 / MAX: 106.971. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: squeezenet_ssdARMv8 Cortex-A76102030405043.11MIN: 39.81 / MAX: 109.111. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: regnety_400mARMv8 Cortex-A76369121512.82MIN: 11.59 / MAX: 75.681. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: vision_transformerARMv8 Cortex-A76140280420560700627.86MIN: 594.98 / MAX: 660.351. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: CPU - Model: FastestDetARMv8 Cortex-A762468106.32MIN: 5.61 / MAX: 67.671. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: mobilenetARMv8 Cortex-A76112233445548.83MIN: 45.66 / MAX: 115.751. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2ARMv8 Cortex-A764812162014.12MIN: 12.74 / MAX: 76.441. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3ARMv8 Cortex-A7636912159.76MIN: 8.95 / MAX: 77.11. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: shufflenet-v2ARMv8 Cortex-A760.89331.78662.67993.57324.46653.97MIN: 3.46 / MAX: 65.741. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: mnasnetARMv8 Cortex-A7636912159.13MIN: 8.28 / MAX: 66.071. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: efficientnet-b0ARMv8 Cortex-A764812162016.06MIN: 14.54 / MAX: 81.051. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: blazefaceARMv8 Cortex-A760.42750.8551.28251.712.13751.9MIN: 1.52 / MAX: 40.051. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: googlenetARMv8 Cortex-A7681624324034.49MIN: 32.05 / MAX: 115.751. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: vgg16ARMv8 Cortex-A764080120160200163.32MIN: 155.28 / MAX: 202.591. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: resnet18ARMv8 Cortex-A7661218243025.01MIN: 23.31 / MAX: 70.281. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: alexnetARMv8 Cortex-A7661218243025.89MIN: 24.36 / MAX: 55.561. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: resnet50ARMv8 Cortex-A76132639526558.31MIN: 53.92 / MAX: 113.751. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPUv2-yolov3v2-yolov3 - Model: mobilenetv2-yolov3ARMv8 Cortex-A76112233445548.83MIN: 45.66 / MAX: 115.751. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: yolov4-tinyARMv8 Cortex-A76132639526557.05MIN: 54.01 / MAX: 101.261. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: squeezenet_ssdARMv8 Cortex-A76102030405042.51MIN: 39.68 / MAX: 110.681. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: regnety_400mARMv8 Cortex-A76369121512.86MIN: 11.6 / MAX: 77.321. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: vision_transformerARMv8 Cortex-A76140280420560700629.58MIN: 585.91 / MAX: 719.321. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenBenchmarking.orgms, Fewer Is BetterNCNN 20230517Target: Vulkan GPU - Model: FastestDetARMv8 Cortex-A762468106.13MIN: 5.6 / MAX: 44.411. (CXX) g++ options: -O3 -rdynamic -lgomp -lpthread

OpenCV

This is a benchmark of the OpenCV (Computer Vision) library's built-in performance tests. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetterOpenCV 4.7Test: DNN - Deep Neural NetworkARMv8 Cortex-A76100K200K300K400K500K4722351. (CXX) g++ options: -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -fvisibility=hidden -O3 -ldl -lm -lpthread -lrt

OpenBenchmarking.orgms, Fewer Is BetterOpenCV 4.7Test: Features 2DARMv8 Cortex-A7650K100K150K200K250K2408881. (CXX) g++ options: -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -fvisibility=hidden -O3 -ldl -lm -lpthread -lrt

OpenBenchmarking.orgms, Fewer Is BetterOpenCV 4.7Test: Object DetectionARMv8 Cortex-A7613K26K39K52K65K614431. (CXX) g++ options: -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -fvisibility=hidden -O3 -ldl -lm -lpthread -lrt

OpenBenchmarking.orgms, Fewer Is BetterOpenCV 4.7Test: CoreARMv8 Cortex-A7660K120K180K240K300K2814701. (CXX) g++ options: -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -fvisibility=hidden -O3 -ldl -lm -lpthread -lrt

Test: Graph API

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: AbsExact error: G-API output and reference output matrixes are not bitexact equal.

OpenBenchmarking.orgms, Fewer Is BetterOpenCV 4.7Test: Image ProcessingARMv8 Cortex-A76130K260K390K520K650K6282641. (CXX) g++ options: -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -fvisibility=hidden -O3 -ldl -lm -lpthread -lrt

OpenBenchmarking.orgms, Fewer Is BetterOpenCV 4.7Test: StitchingARMv8 Cortex-A7690K180K270K360K450K4394951. (CXX) g++ options: -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -fvisibility=hidden -O3 -ldl -lm -lpthread -lrt

OpenBenchmarking.orgms, Fewer Is BetterOpenCV 4.7Test: VideoARMv8 Cortex-A7630K60K90K120K150K1618591. (CXX) g++ options: -fsigned-char -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -fvisibility=hidden -O3 -ldl -lm -lpthread -lrt

R Benchmark

This test is a quick-running survey of general R performance Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgSeconds, Fewer Is BetterR BenchmarkARMv8 Cortex-A760.13590.27180.40770.54360.67950.6038

Numpy Benchmark

This is a test to obtain the general Numpy performance. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgScore, More Is BetterNumpy BenchmarkARMv8 Cortex-A76306090120150136.85

AI Benchmark Alpha

AI Benchmark Alpha is a Python library for evaluating artificial intelligence (AI) performance on diverse hardware platforms and relies upon the TensorFlow machine learning library. Learn more via the OpenBenchmarking.org test page.

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'tensorflow'

Mlpack Benchmark

Mlpack benchmark scripts for machine learning libraries Learn more via the OpenBenchmarking.org test page.

Benchmark: scikit_svm

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'imp'

Benchmark: scikit_linearridgeregression

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'imp'

Benchmark: scikit_qda

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'imp'

Benchmark: scikit_ica

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'imp'

Numenta Anomaly Benchmark

Numenta Anomaly Benchmark (NAB) is a benchmark for evaluating algorithms for anomaly detection in streaming, real-time applications. It is comprised of over 50 labeled real-world and artificial time-series data files plus a novel scoring mechanism designed for real-time applications. This test profile currently measures the time to run various detectors. Learn more via the OpenBenchmarking.org test page.

Detector: Bayesian Changepoint

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'

Detector: Windowed Gaussian

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'

Detector: Relative Entropy

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'

Detector: Earthgecko Skyline

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'

Detector: KNN CAD

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'

Detector: Contextual Anomaly Detector OSE

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: ModuleNotFoundError: No module named 'pandas'

TensorFlow Lite

This is a benchmark of the TensorFlow Lite implementation focused on TensorFlow machine learning for mobile, IoT, edge, and other cases. The current Linux support is limited to running on CPUs. This test profile is measuring the average inference time. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2022-05-18Model: Mobilenet FloatARMv8 Cortex-A764K8K12K16K20K18684.6

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2022-05-18Model: Mobilenet QuantARMv8 Cortex-A76120024003600480060005774.24

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2022-05-18Model: NASNet MobileARMv8 Cortex-A7611K22K33K44K55K52846.6

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2022-05-18Model: SqueezeNetARMv8 Cortex-A766K12K18K24K30K26872.6

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2022-05-18Model: Inception ResNet V2ARMv8 Cortex-A7650K100K150K200K250K215253

OpenBenchmarking.orgMicroseconds, Fewer Is BetterTensorFlow Lite 2022-05-18Model: Inception V4ARMv8 Cortex-A7650K100K150K200K250K246550

oneDNN

This is a test of the Intel oneDNN as an Intel-optimized library for Deep Neural Networks and making use of its built-in benchdnn functionality. The result is the total perf time reported. Intel oneDNN was formerly known as DNNL (Deep Neural Network Library) and MKL-DNN before being rebranded as part of the Intel oneAPI toolkit. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Convolution Batch Shapes Auto - Engine: CPUARMv8 Cortex-A7660120180240300264.11MIN: 254.721. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Deconvolution Batch shapes_1d - Engine: CPUARMv8 Cortex-A76120240360480600560.13MIN: 541.241. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Deconvolution Batch shapes_3d - Engine: CPUARMv8 Cortex-A7620406080100103.12MIN: 95.691. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: IP Shapes 1D - Engine: CPUARMv8 Cortex-A76132639526558.65MIN: 54.791. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: IP Shapes 3D - Engine: CPUARMv8 Cortex-A76142842567062.98MIN: 60.871. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Recurrent Neural Network Training - Engine: CPUARMv8 Cortex-A7614K28K42K56K70K65557.7MIN: 65037.41. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

OpenBenchmarking.orgms, Fewer Is BetteroneDNN 3.4Harness: Recurrent Neural Network Inference - Engine: CPUARMv8 Cortex-A768K16K24K32K40K35072.3MIN: 34622.41. (CXX) g++ options: -O3 -march=native -fopenmp -mcpu=generic -fPIC -pie -ldl

ONNX Runtime

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.19Model: yolov4 - Device: CPU - Executor: ParallelARMv8 Cortex-A760.12010.24020.36030.48040.60050.5335761. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.19Model: fcn-resnet101-11 - Device: CPU - Executor: ParallelARMv8 Cortex-A760.02260.04520.06780.09040.1130.1004191. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.19Model: super-resolution-10 - Device: CPU - Executor: ParallelARMv8 Cortex-A762468108.694341. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

Model: bertsquad-12 - Device: CPU - Executor: Parallel

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: onnxruntime/onnxruntime/test/onnx/onnx_model_info.cc:45 void OnnxModelInfo::InitOnnxModelInfo(const std::filesystem::__cxx11::path&) open file "bertsquad-12/bertsquad-12.onnx" failed: No such file or directory

Model: GPT-2 - Device: CPU - Executor: Parallel

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: onnxruntime/onnxruntime/test/onnx/onnx_model_info.cc:45 void OnnxModelInfo::InitOnnxModelInfo(const std::filesystem::__cxx11::path&) open file "GPT2/model.onnx" failed: No such file or directory

Model: ArcFace ResNet-100 - Device: CPU - Executor: Parallel

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: onnxruntime/onnxruntime/test/onnx/onnx_model_info.cc:45 void OnnxModelInfo::InitOnnxModelInfo(const std::filesystem::__cxx11::path&) open file "resnet100/resnet100.onnx" failed: No such file or directory

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.19Model: ResNet50 v1-12-int8 - Device: CPU - Executor: ParallelARMv8 Cortex-A76369121512.501. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.19Model: CaffeNet 12-int8 - Device: CPU - Executor: ParallelARMv8 Cortex-A76102030405045.171. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

Model: Faster R-CNN R-50-FPN-int8 - Device: CPU - Executor: Parallel

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: onnxruntime/onnxruntime/test/onnx/onnx_model_info.cc:45 void OnnxModelInfo::InitOnnxModelInfo(const std::filesystem::__cxx11::path&) open file "FasterRCNN-12-int8/FasterRCNN-12-int8.onnx" failed: No such file or directory

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.19Model: T5 Encoder - Device: CPU - Executor: ParallelARMv8 Cortex-A764812162016.911. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.19Model: ZFNet-512 - Device: CPU - Executor: ParallelARMv8 Cortex-A7636912159.599581. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

OpenBenchmarking.orgInferences Per Second, More Is BetterONNX Runtime 1.19Model: ResNet101_DUC_HDC-12 - Device: CPU - Executor: ParallelARMv8 Cortex-A760.00970.01940.02910.03880.04850.04320721. (CXX) g++ options: -O3 -march=native -ffunction-sections -fdata-sections -mtune=native -flto=auto -fno-fat-lto-objects -ldl -lrt

LeelaChessZero

Backend: BLAS

ARMv8 Cortex-A76: The test run did not produce a result.

Backend: Eigen

ARMv8 Cortex-A76: The test run did not produce a result.

Whisper.cpp

OpenBenchmarking.orgSeconds, Fewer Is BetterWhisper.cpp 1.6.2Model: ggml-base.en - Input: 2016 State of the UnionARMv8 Cortex-A76140280420560700646.231. (CXX) g++ options: -O3 -std=c++11 -fPIC -pthread -mcpu=native

OpenBenchmarking.orgSeconds, Fewer Is BetterWhisper.cpp 1.6.2Model: ggml-small.en - Input: 2016 State of the UnionARMv8 Cortex-A764008001200160020001928.491. (CXX) g++ options: -O3 -std=c++11 -fPIC -pthread -mcpu=native

OpenBenchmarking.orgSeconds, Fewer Is BetterWhisper.cpp 1.6.2Model: ggml-medium.en - Input: 2016 State of the UnionARMv8 Cortex-A76130026003900520065005899.941. (CXX) g++ options: -O3 -std=c++11 -fPIC -pthread -mcpu=native

Whisperfile

OpenBenchmarking.orgSeconds, Fewer Is BetterWhisperfile 20Aug24Model Size: TinyARMv8 Cortex-A7670140210280350332.12

OpenBenchmarking.orgSeconds, Fewer Is BetterWhisperfile 20Aug24Model Size: SmallARMv8 Cortex-A764008001200160020001779.12

OpenBenchmarking.orgSeconds, Fewer Is BetterWhisperfile 20Aug24Model Size: MediumARMv8 Cortex-A76110022003300440055005162.45

PyTorch

This is a benchmark of PyTorch making use of pytorch-benchmark [https://github.com/LukasHedegaard/pytorch-benchmark]. Learn more via the OpenBenchmarking.org test page.

Device: CPU - Batch Size: 1 - Model: ResNet-50

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 1 - Model: ResNet-152

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 16 - Model: ResNet-50

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 16 - Model: ResNet-152

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 32 - Model: ResNet-50

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 32 - Model: ResNet-152

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 32 - Model: Efficientnet_v2_l

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 64 - Model: ResNet-50

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 64 - Model: ResNet-152

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 64 - Model: Efficientnet_v2_l

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 256 - Model: ResNet-50

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 256 - Model: ResNet-152

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 256 - Model: Efficientnet_v2_l

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

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

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 512 - Model: ResNet-152

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Device: CPU - Batch Size: 512 - Model: Efficientnet_v2_l

ARMv8 Cortex-A76: The test quit with a non-zero exit status. E: KeyError: 'brand_raw'

Llama.cpp

OpenBenchmarking.orgTokens Per Second, More Is BetterLlama.cpp b3067Model: Meta-Llama-3-8B-Instruct-Q8_0.ggufARMv8 Cortex-A760.0270.0540.0810.1080.1350.121. (CXX) g++ options: -std=c++11 -fPIC -O3 -pthread -mcpu=native -lopenblas

Llamafile

OpenBenchmarking.orgTokens Per Second, More Is BetterLlamafile 0.8.6Test: mistral-7b-instruct-v0.2.Q5_K_M - Acceleration: CPUARMv8 Cortex-A760.42530.85061.27591.70122.12651.89

OpenBenchmarking.orgTokens Per Second, More Is BetterLlamafile 0.8.6Test: mistral-7b-instruct-v0.2.Q5_K_M - Acceleration: GPU AUTOARMv8 Cortex-A760.4230.8461.2691.6922.1151.88

Test: Meta-Llama-3-8B-Instruct.F16 - Acceleration: CPU

ARMv8 Cortex-A76: The test quit with a non-zero exit status.

Test: Meta-Llama-3-8B-Instruct.F16 - Acceleration: GPU AUTO

ARMv8 Cortex-A76: The test quit with a non-zero exit status.

OpenBenchmarking.orgTokens Per Second, More Is BetterLlamafile 0.8.6Test: TinyLlama-1.1B-Chat-v1.0.BF16 - Acceleration: CPUARMv8 Cortex-A764812162015

OpenBenchmarking.orgTokens Per Second, More Is BetterLlamafile 0.8.6Test: TinyLlama-1.1B-Chat-v1.0.BF16 - Acceleration: GPU AUTOARMv8 Cortex-A760.98551.9712.95653.9424.92754.38

OpenBenchmarking.orgTokens Per Second, More Is BetterLlamafile 0.8.6Test: llava-v1.6-mistral-7b.Q8_0 - Acceleration: CPUARMv8 Cortex-A760.4410.8821.3231.7642.2051.96

OpenBenchmarking.orgTokens Per Second, More Is BetterLlamafile 0.8.6Test: llava-v1.6-mistral-7b.Q8_0 - Acceleration: GPU AUTOARMv8 Cortex-A760.43880.87761.31641.75522.1941.95

Test: wizardcoder-python-34b-v1.0.Q6_K - Acceleration: CPU

ARMv8 Cortex-A76: The test quit with a non-zero exit status.

Test: wizardcoder-python-34b-v1.0.Q6_K - Acceleration: GPU AUTO

ARMv8 Cortex-A76: The test quit with a non-zero exit status.

XNNPACK

OpenBenchmarking.orgus, Fewer Is BetterXNNPACK 2cd86bModel: FP32MobileNetV2ARMv8 Cortex-A764K8K12K16K20K205221. (CXX) g++ options: -O3 -lrt -lm

OpenBenchmarking.orgus, Fewer Is BetterXNNPACK 2cd86bModel: FP32MobileNetV3LargeARMv8 Cortex-A764K8K12K16K20K203541. (CXX) g++ options: -O3 -lrt -lm

OpenBenchmarking.orgus, Fewer Is BetterXNNPACK 2cd86bModel: FP32MobileNetV3SmallARMv8 Cortex-A761600320048006400800074921. (CXX) g++ options: -O3 -lrt -lm

OpenBenchmarking.orgus, Fewer Is BetterXNNPACK 2cd86bModel: FP16MobileNetV2ARMv8 Cortex-A762K4K6K8K10K101661. (CXX) g++ options: -O3 -lrt -lm

OpenBenchmarking.orgus, Fewer Is BetterXNNPACK 2cd86bModel: FP16MobileNetV3LargeARMv8 Cortex-A762K4K6K8K10K104781. (CXX) g++ options: -O3 -lrt -lm

OpenBenchmarking.orgus, Fewer Is BetterXNNPACK 2cd86bModel: FP16MobileNetV3SmallARMv8 Cortex-A76900180027003600450040461. (CXX) g++ options: -O3 -lrt -lm

OpenBenchmarking.orgus, Fewer Is BetterXNNPACK 2cd86bModel: QU8MobileNetV2ARMv8 Cortex-A763K6K9K12K15K119041. (CXX) g++ options: -O3 -lrt -lm

OpenBenchmarking.orgus, Fewer Is BetterXNNPACK 2cd86bModel: QU8MobileNetV3LargeARMv8 Cortex-A762K4K6K8K10K103381. (CXX) g++ options: -O3 -lrt -lm

OpenBenchmarking.orgus, Fewer Is BetterXNNPACK 2cd86bModel: QU8MobileNetV3SmallARMv8 Cortex-A76700140021002800350033371. (CXX) g++ options: -O3 -lrt -lm

CPU Fan Speed Monitor

OpenBenchmarking.orgRPMCPU Fan Speed MonitorPhoronix Test Suite System MonitoringARMv8 Cortex-A76V3D 7.1.714002800420056007000Min: 11 / Avg: 4822.05 / Max: 8294Min: 1730 / Avg: 3391.02 / Max: 3465

CPU Peak Freq (Highest CPU Core Frequency) Monitor

OpenBenchmarking.orgMegahertzCPU Peak Freq (Highest CPU Core Frequency) MonitorPhoronix Test Suite System MonitoringARMv8 Cortex-A76V3D 7.1.7400800120016002000Min: 1500 / Avg: 2086.36 / Max: 2400Min: 1500 / Avg: 1569.55 / Max: 2400

CPU Temperature Monitor

OpenBenchmarking.orgCelsiusCPU Temperature MonitorPhoronix Test Suite System MonitoringARMv8 Cortex-A76V3D 7.1.71428425670Min: 44.65 / Avg: 55.93 / Max: 74.35Min: 43.55 / Avg: 47.16 / Max: 50.15

CPU Usage (Summary) Monitor

OpenBenchmarking.orgPercentCPU Usage (Summary) MonitorPhoronix Test Suite System MonitoringARMv8 Cortex-A76V3D 7.1.720406080100Min: 0 / Avg: 87.88 / Max: 100Min: 0 / Avg: 4.58 / Max: 47.45

Memory Usage Monitor

OpenBenchmarking.orgMegabytesMemory Usage MonitorPhoronix Test Suite System MonitoringARMv8 Cortex-A76V3D 7.1.76001200180024003000Min: 247 / Avg: 1954.03 / Max: 3664Min: 915 / Avg: 975.04 / Max: 1075

System Fan Speed Monitor

OpenBenchmarking.orgRPMSystem Fan Speed MonitorPhoronix Test Suite System MonitoringARMv8 Cortex-A76V3D 7.1.714002800420056007000Min: 11 / Avg: 4822.03 / Max: 8294Min: 1730 / Avg: 3391.03 / Max: 3465

System Temperature Monitor

OpenBenchmarking.orgCelsiusSystem Temperature MonitorPhoronix Test Suite System MonitoringARMv8 Cortex-A76V3D 7.1.71428425670Min: 44.7 / Avg: 55.89 / Max: 73.8Min: 44.1 / Avg: 47.2 / Max: 50.7

VKMark

VKMark is a collection of open-source Vulkan tests / rendering benchmarks. Learn more via the OpenBenchmarking.org test page.

OpenBenchmarking.orgVKMark Score, More Is BetterVKMark 2022-05-16Resolution: 800 x 600 - Present Mode: MailboxV3D 7.1.71002003004005004671. (CXX) g++ options: -pthread -ldl -std=c++14 -O0 -MD -MQ -MF

OpenBenchmarking.orgVKMark Score, More Is BetterVKMark 2022-05-16Resolution: 1024 x 768 - Present Mode: MailboxV3D 7.1.7701402102803503021. (CXX) g++ options: -pthread -ldl -std=c++14 -O0 -MD -MQ -MF

OpenBenchmarking.orgVKMark Score, More Is BetterVKMark 2022-05-16Resolution: 1280 x 1024 - Present Mode: MailboxV3D 7.1.740801201602001921. (CXX) g++ options: -pthread -ldl -std=c++14 -O0 -MD -MQ -MF

OpenBenchmarking.orgVKMark Score, More Is BetterVKMark 2022-05-16Resolution: 1920 x 1080 - Present Mode: MailboxV3D 7.1.73060901201501311. (CXX) g++ options: -pthread -ldl -std=c++14 -O0 -MD -MQ -MF

109 Results Shown

Timed Apache Compilation
Timed FFmpeg Compilation
Mobile Neural Network:
  nasnet
  mobilenetV3
  squeezenetv1.1
  resnet-v2-50
  SqueezeNetV1.0
  MobileNetV2_224
  mobilenet-v1-1.0
  inception-v3
NCNN:
  CPU - mobilenet
  CPU-v2-v2 - mobilenet-v2
  CPU-v3-v3 - mobilenet-v3
  CPU - shufflenet-v2
  CPU - mnasnet
  CPU - efficientnet-b0
  CPU - blazeface
  CPU - googlenet
  CPU - vgg16
  CPU - resnet18
  CPU - alexnet
  CPU - resnet50
  CPUv2-yolov3v2-yolov3 - mobilenetv2-yolov3
  CPU - yolov4-tiny
  CPU - squeezenet_ssd
  CPU - regnety_400m
  CPU - vision_transformer
  CPU - FastestDet
  Vulkan GPU - mobilenet
  Vulkan GPU-v2-v2 - mobilenet-v2
  Vulkan GPU-v3-v3 - mobilenet-v3
  Vulkan GPU - shufflenet-v2
  Vulkan GPU - mnasnet
  Vulkan GPU - efficientnet-b0
  Vulkan GPU - blazeface
  Vulkan GPU - googlenet
  Vulkan GPU - vgg16
  Vulkan GPU - resnet18
  Vulkan GPU - alexnet
  Vulkan GPU - resnet50
  Vulkan GPUv2-yolov3v2-yolov3 - mobilenetv2-yolov3
  Vulkan GPU - yolov4-tiny
  Vulkan GPU - squeezenet_ssd
  Vulkan GPU - regnety_400m
  Vulkan GPU - vision_transformer
  Vulkan GPU - FastestDet
OpenCV:
  DNN - Deep Neural Network
  Features 2D
  Object Detection
  Core
  Image Processing
  Stitching
  Video
R Benchmark
Numpy Benchmark
TensorFlow Lite:
  Mobilenet Float
  Mobilenet Quant
  NASNet Mobile
  SqueezeNet
  Inception ResNet V2
  Inception V4
oneDNN:
  Convolution Batch Shapes Auto - CPU
  Deconvolution Batch shapes_1d - CPU
  Deconvolution Batch shapes_3d - CPU
  IP Shapes 1D - CPU
  IP Shapes 3D - CPU
  Recurrent Neural Network Training - CPU
  Recurrent Neural Network Inference - CPU
ONNX Runtime:
  yolov4 - CPU - Parallel
  fcn-resnet101-11 - CPU - Parallel
  super-resolution-10 - CPU - Parallel
  ResNet50 v1-12-int8 - CPU - Parallel
  CaffeNet 12-int8 - CPU - Parallel
  T5 Encoder - CPU - Parallel
  ZFNet-512 - CPU - Parallel
  ResNet101_DUC_HDC-12 - CPU - Parallel
Whisper.cpp:
  ggml-base.en - 2016 State of the Union
  ggml-small.en - 2016 State of the Union
  ggml-medium.en - 2016 State of the Union
Whisperfile:
  Tiny
  Small
  Medium
Llama.cpp
Llamafile:
  mistral-7b-instruct-v0.2.Q5_K_M - CPU
  mistral-7b-instruct-v0.2.Q5_K_M - GPU AUTO
  TinyLlama-1.1B-Chat-v1.0.BF16 - CPU
  TinyLlama-1.1B-Chat-v1.0.BF16 - GPU AUTO
  llava-v1.6-mistral-7b.Q8_0 - CPU
  llava-v1.6-mistral-7b.Q8_0 - GPU AUTO
XNNPACK:
  FP32MobileNetV2
  FP32MobileNetV3Large
  FP32MobileNetV3Small
  FP16MobileNetV2
  FP16MobileNetV3Large
  FP16MobileNetV3Small
  QU8MobileNetV2
  QU8MobileNetV3Large
  QU8MobileNetV3Small
CPU Fan Speed Monitor:
  Phoronix Test Suite System Monitoring:
    RPM
    Megahertz
    Celsius
    Percent
    Megabytes
    RPM
    Celsius
VKMark:
  800 x 600 - Mailbox
  1024 x 768 - Mailbox
  1280 x 1024 - Mailbox
  1920 x 1080 - Mailbox