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KVM testing 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 2402237-NE-20860178071
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BLAS (Basic Linear Algebra Sub-Routine) Tests 3 Tests
C++ Boost Tests 2 Tests
CPU Massive 4 Tests
Creator Workloads 3 Tests
HPC - High Performance Computing 8 Tests
Machine Learning 5 Tests
Multi-Core 6 Tests
NVIDIA GPU Compute 20 Tests
OpenCL 6 Tests
OpenMPI Tests 2 Tests
Python Tests 2 Tests
Renderers 2 Tests
Scientific Computing 2 Tests
Server CPU Tests 2 Tests
Common Workstation Benchmarks 2 Tests

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NVIDIA A100 80GB PCIe
February 23
  8 Hours, 52 Minutes
14 x Intel Xeon Gold 6342 - NVIDIA A100 80GB PCIe -
February 23
  6 Hours, 6 Minutes
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  7 Hours, 29 Minutes
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2 Suite 1.0.0 System Test suite extracted from 2. pts/shoc-1.2.0 -opencl -benchmark MaxFlops Target: OpenCL - Benchmark: Max SP Flops pts/ncnn-1.5.0 Target: Vulkan GPU - Model: mnasnet pts/ncnn-1.5.0 Target: Vulkan GPU - Model: FastestDet pts/ncnn-1.5.0 Target: Vulkan GPU - Model: vision_transformer pts/ncnn-1.5.0 Target: Vulkan GPU - Model: regnety_400m pts/ncnn-1.5.0 Target: Vulkan GPU - Model: squeezenet_ssd pts/ncnn-1.5.0 Target: Vulkan GPU - Model: yolov4-tiny pts/ncnn-1.5.0 Target: Vulkan GPU - Model: resnet50 pts/ncnn-1.5.0 Target: Vulkan GPU - Model: alexnet pts/ncnn-1.5.0 Target: Vulkan GPU - Model: resnet18 pts/ncnn-1.5.0 Target: Vulkan GPU - Model: vgg16 pts/ncnn-1.5.0 Target: Vulkan GPU - Model: googlenet pts/ncnn-1.5.0 Target: Vulkan GPU - Model: blazeface pts/ncnn-1.5.0 Target: Vulkan GPU - Model: efficientnet-b0 pts/ncnn-1.5.0 Target: Vulkan GPU - Model: shufflenet-v2 pts/ncnn-1.5.0 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 pts/ncnn-1.5.0 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 pts/ncnn-1.5.0 Target: Vulkan GPU - Model: mobilenet pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-TT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-TN pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-NT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMM-NN pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMV-T pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dGEMV-N pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dDOT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dAXPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - dCOPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - sDOT pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - sAXPY pts/viennacl-1.1.0 dense_blas-bench-cpu Test: CPU BLAS - sCOPY pts/blender-4.0.0 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device OPTIX Blend File: BMW27 - Compute: NVIDIA OptiX pts/fahbench-1.0.2 pts/blender-4.0.0 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device OPTIX Blend File: Barbershop - Compute: NVIDIA OptiX pts/blender-4.0.0 -b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device OPTIX Blend File: Fishy Cat - Compute: NVIDIA OptiX pts/blender-4.0.0 -b ../pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device OPTIX Blend File: Pabellon Barcelona - Compute: NVIDIA OptiX pts/gromacs-1.9.0 cuda-build water-cut1.0_GMX50_bare/1536 Implementation: NVIDIA CUDA GPU - Input: water_GMX50_bare pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -gpu all -iterations 1000 Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 1000 pts/blender-4.0.0 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device OPTIX Blend File: Classroom - Compute: NVIDIA OptiX pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMM-TT pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMM-TN pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMM-NT pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMM-NN pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMV-T pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dGEMV-N pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dDOT pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dAXPY pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - dCOPY pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - sDOT pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - sAXPY pts/viennacl-1.1.0 dense_blas-bench-opencl Test: OpenCL BLAS - sCOPY pts/luxcorerender-1.4.0 LuxCore2.1Benchmark/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: LuxCore Benchmark - Acceleration: GPU pts/luxcorerender-1.4.0 DanishMood/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: Danish Mood - Acceleration: GPU pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -gpu all -iterations 1000 Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 1000 pts/plaidml-1.0.4 --no-fp16 --no-train densenet201 OPENCL FP16: No - Mode: Inference - Network: DenseNet 201 - Device: OpenCL pts/shoc-1.2.0 -opencl -benchmark DeviceMemory Target: OpenCL - Benchmark: Texture Read Bandwidth pts/plaidml-1.0.4 --no-fp16 --train mobilenet OPENCL FP16: No - Mode: Training - Network: Mobilenet - Device: OpenCL pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -gpu all -iterations 200 Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 200 pts/luxcorerender-1.4.0 DLSC/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: DLSC - Acceleration: GPU pts/luxcorerender-1.4.0 OrangeJuice/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: Orange Juice - Acceleration: GPU pts/arrayfire-1.2.0 cg_opencl Test: Conjugate Gradient OpenCL pts/hashcat-1.1.1 -m 0 Benchmark: MD5 pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -gpu all -iterations 100 Model: GoogleNet - Acceleration: NVIDIA CUDA - Iterations: 100 pts/mixbench-1.1.1 mixbench-ocl-ro GIOPS Backend: OpenCL - Benchmark: Integer pts/hashcat-1.1.1 -m 1700 Benchmark: SHA-512 pts/hashcat-1.1.1 -m 100 Benchmark: SHA1 pts/hashcat-1.1.1 -m 11600 Benchmark: 7-Zip pts/cl-mem-1.0.1 WRITE Benchmark: Write pts/cl-mem-1.0.1 COPY Benchmark: Copy pts/cl-mem-1.0.1 READ Benchmark: Read pts/hashcat-1.1.1 -m 6211 Benchmark: TrueCrypt RIPEMD160 + XTS pts/plaidml-1.0.4 --fp16 --no-train mobilenet OPENCL FP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCL pts/shoc-1.2.0 -opencl -benchmark Triad Target: OpenCL - Benchmark: Triad pts/plaidml-1.0.4 --no-fp16 --no-train mobilenet OPENCL FP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCL pts/plaidml-1.0.4 --no-fp16 --no-train imdb_lstm OPENCL FP16: No - Mode: Inference - Network: IMDB LSTM - Device: OpenCL pts/financebench-1.1.1 Black-Scholes/OpenCL/blackScholesAnalyticEngine.exe Benchmark: Black-Scholes OpenCL pts/clpeak-1.1.0 --global-bandwidth OpenCL Test: Global Memory Bandwidth pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -gpu all -iterations 200 Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 200 pts/clpeak-1.1.0 --compute-sp OpenCL Test: Single-Precision Float pts/shoc-1.2.0 -opencl -benchmark Reduction Target: OpenCL - Benchmark: Reduction pts/shoc-1.2.0 -opencl -benchmark FFT Target: OpenCL - Benchmark: FFT SP pts/shoc-1.2.0 -opencl -benchmark S3D Target: OpenCL - Benchmark: S3D pts/shoc-1.2.0 -opencl -benchmark BusSpeedReadback Target: OpenCL - Benchmark: Bus Speed Readback pts/shoc-1.2.0 -opencl -benchmark GEMM Target: OpenCL - Benchmark: GEMM SGEMM_N pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -gpu all -iterations 100 Model: AlexNet - Acceleration: NVIDIA CUDA - Iterations: 100 pts/neatbench-1.0.4 gpu Acceleration: GPU pts/rodinia-1.3.2 OCL_PARTICLEFILTER Test: OpenCL Particle Filter pts/shoc-1.2.0 -opencl -benchmark BusSpeedDownload Target: OpenCL - Benchmark: Bus Speed Download pts/clpeak-1.1.0 --compute-dp OpenCL Test: Double-Precision Double pts/clpeak-1.1.0 --compute-integer OpenCL Test: Integer Compute INT pts/mixbench-1.1.1 mixbench-ocl-ro SPGFLOPS Backend: OpenCL - Benchmark: Single Precision pts/mixbench-1.1.1 mixbench-ocl-ro DPGFLOPS Backend: OpenCL - Benchmark: Double Precision pts/shoc-1.2.0 -opencl -benchmark MD5Hash Target: OpenCL - Benchmark: MD5 Hash pts/luxcorerender-1.4.0 RainbowColorsAndPrism/LuxCoreScene/render.cfg -D renderengine.type PATHOCL -D opencl.native.threads.count 0 -D context.cuda.optix.enable 0 Scene: Rainbow Colors and Prism - Acceleration: GPU pts/mandelgpu-1.3.1 0 1 OpenCL Device: GPU pts/mixbench-1.1.1 mixbench-cuda-ro SPGFLOPS Backend: NVIDIA CUDA - Benchmark: Single Precision pts/mixbench-1.1.1 mixbench-cuda-ro HPGFLOPS Backend: NVIDIA CUDA - Benchmark: Half Precision pts/mixbench-1.1.1 mixbench-cuda-ro DPGFLOPS Backend: NVIDIA CUDA - Benchmark: Double Precision pts/mixbench-1.1.1 mixbench-cuda-ro GIOPS Backend: NVIDIA CUDA - Benchmark: Integer pts/lczero-1.7.0 -b opencl Backend: OpenCL pts/redshift-1.0.1