AMD Ryzen 9 3950X Ubuntu Linux

AMD Ryzen 9 3950X 16-Core testing with a ASUS ROG CROSSHAIR VIII HERO (WI-FI) (1302 BIOS) and NVIDIA GeForce RTX 2080 Ti 11GB 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 2009247-FI-AMDRYZEN924
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BLAS (Basic Linear Algebra Sub-Routine) Tests 2 Tests
CPU Massive 4 Tests
Creator Workloads 4 Tests
HPC - High Performance Computing 5 Tests
Imaging 2 Tests
Common Kernel Benchmarks 2 Tests
Machine Learning 3 Tests
Multi-Core 3 Tests
NVIDIA GPU Compute 16 Tests
OpenCL 5 Tests
Server CPU Tests 2 Tests
Common Workstation Benchmarks 2 Tests

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Run 1
September 23 2020
  3 Hours, 47 Minutes
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September 24 2020
  3 Hours, 43 Minutes
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September 24 2020
  3 Hours, 44 Minutes
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AMD Ryzen 9 3950X Ubuntu Linux Suite 1.0.0 System Test suite extracted from AMD Ryzen 9 3950X Ubuntu Linux. pts/arrayfire-1.1.0 cg_opencl Test: Conjugate Gradient OpenCL pts/blender-1.8.0 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 CUDA Blend File: BMW27 - Compute: CUDA pts/blender-1.8.0 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 CUDA Blend File: Classroom - Compute: CUDA pts/blender-1.8.0 -b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 CUDA Blend File: Fishy Cat - Compute: CUDA pts/blender-1.8.0 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 CUDA Blend File: Barbershop - Compute: CUDA pts/blender-1.8.0 -b ../bmw27_gpu.blend -o output.test -x 1 -F JPEG -f 1 OPTIX Blend File: BMW27 - Compute: NVIDIA OptiX pts/blender-1.8.0 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 OPTIX Blend File: Classroom - Compute: NVIDIA OptiX pts/blender-1.8.0 -b ../fishy_cat_gpu.blend -o output.test -x 1 -F JPEG -f 1 OPTIX Blend File: Fishy Cat - Compute: NVIDIA OptiX pts/blender-1.8.0 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 OPTIX Blend File: Barbershop - Compute: NVIDIA OptiX pts/blender-1.8.0 -b ../pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 CUDA Blend File: Pabellon Barcelona - Compute: CUDA pts/blender-1.8.0 -b ../pavillon_barcelone_gpu.blend -o output.test -x 1 -F JPEG -f 1 OPTIX Blend File: Pabellon Barcelona - Compute: NVIDIA OptiX pts/cl-mem-1.0.1 COPY Benchmark: Copy pts/cl-mem-1.0.1 READ Benchmark: Read pts/cl-mem-1.0.1 WRITE Benchmark: Write pts/clpeak-1.0.1 --compute-integer OpenCL Test: Integer Compute INT pts/clpeak-1.0.1 --compute-sp OpenCL Test: Single-Precision Float pts/clpeak-1.0.1 --compute-dp OpenCL Test: Double-Precision Double pts/clpeak-1.0.1 --global-bandwidth OpenCL Test: Global Memory Bandwidth pts/espeak-1.6.0 Text-To-Speech Synthesis pts/fahbench-1.0.1 pts/financebench-1.0.0 Black-Scholes/OpenCL/blackScholesAnalyticEngine.exe Benchmark: Black-Scholes OpenCL pts/hashcat-1.0.0 -m 0 Benchmark: MD5 pts/hashcat-1.0.0 -m 100 Benchmark: SHA1 pts/hashcat-1.0.0 -m 11600 Benchmark: 7-Zip pts/hashcat-1.0.0 -m 1700 Benchmark: SHA-512 pts/hashcat-1.0.0 -m 6211 Benchmark: TrueCrypt RIPEMD160 + XTS pts/influxdb-1.0.0 -c 4 -b 10000 -t 2,5000,1 -p 10000 Concurrent Streams: 4 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 pts/influxdb-1.0.0 -c 64 -b 10000 -t 2,5000,1 -p 10000 Concurrent Streams: 64 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 pts/influxdb-1.0.0 -c 1024 -b 10000 -t 2,5000,1 -p 10000 Concurrent Streams: 1024 - Batch Size: 10000 - Tags: 2,5000,1 - Points Per Series: 10000 pts/lczero-1.5.0 -b opencl Backend: OpenCL pts/libraw-1.0.0 Post-Processing Benchmark pts/mandelgpu-1.3.1 0 1 OpenCL Device: GPU pts/mixbench-1.1.1 mixbench-cuda-ro GIOPS Backend: NVIDIA CUDA - Benchmark: Integer 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 SPGFLOPS Backend: NVIDIA CUDA - Benchmark: Single Precision system/mpv-1.0.1 bbb_sunflower_2160p_30fps_normal.mp4 --hwdec=no Video Input: Big Buck Bunny Sunflower 4K - Decode: Software Only system/mpv-1.0.1 bbb_sunflower_1080p_30fps_normal.mp4 --hwdec=no Video Input: Big Buck Bunny Sunflower 1080p - Decode: Software Only pts/namd-cuda-1.1.1 ATPase Simulation - 327,506 Atoms pts/octanebench-1.2.1 Total Score pts/opencv-1.0.0 features2d Test: Features 2D pts/opencv-1.0.0 objdetect Test: Object Detection pts/osbench-1.0.2 create_files.exe target Test: Create Files pts/osbench-1.0.2 create_threads.exe Test: Create Threads pts/osbench-1.0.2 launch_programs.exe Test: Launch Programs pts/osbench-1.0.2 create_processes.exe Test: Create Processes pts/osbench-1.0.2 mem_alloc.exe Test: Memory Allocations pts/perf-bench-1.0.2 epoll wait -r 30 Benchmark: Epoll Wait pts/perf-bench-1.0.2 futex hash -r 30 -s Benchmark: Futex Hash pts/perf-bench-1.0.2 mem memcpy -l 100000 -s 1MB Benchmark: Memcpy 1MB pts/perf-bench-1.0.2 mem memset -l 100000 -s 1MB Benchmark: Memset 1MB pts/perf-bench-1.0.2 sched pipe -l 5000000 Benchmark: Sched Pipe pts/perf-bench-1.0.2 futex lock-pi -r 30 -s Benchmark: Futex Lock-Pi pts/perf-bench-1.0.2 syscall basic -l 100000000 Benchmark: Syscall Basic pts/plaidml-1.0.4 --no-fp16 --train mobilenet OPENCL FP16: No - Mode: Training - 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/plaidml-1.0.4 --no-fp16 --no-train mobilenet OPENCL FP16: No - Mode: Inference - Network: Mobilenet - Device: OpenCL pts/plaidml-1.0.4 --fp16 --no-train mobilenet OPENCL FP16: Yes - Mode: Inference - Network: Mobilenet - Device: OpenCL pts/plaidml-1.0.4 --no-fp16 --no-train densenet201 OPENCL FP16: No - Mode: Inference - Network: DenseNet 201 - Device: OpenCL pts/redshift-1.0.1 pts/rodinia-1.3.1 OCL_PARTICLEFILTER Test: OpenCL Particle Filter pts/viennacl-1.0.0 OpenCL LU Factorization pts/webp-1.0.0 Encode Settings: Default pts/webp-1.0.0 -q 100 Encode Settings: Quality 100 pts/webp-1.0.0 -q 100 -lossless Encode Settings: Quality 100, Lossless pts/webp-1.0.0 -q 100 -m 6 Encode Settings: Quality 100, Highest Compression pts/webp-1.0.0 -q 100 -lossless -m 6 Encode Settings: Quality 100, Lossless, Highest Compression