Ryzen 5 7600X Extra Linux

AMD Ryzen 5 7600X 6-Core testing with a ASUS ROG CROSSHAIR X670E HERO (0604 BIOS) and AMD Radeon RX 6800 XT on Ubuntu 22.04 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 2210045-PTS-RYZEN57670
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C/C++ Compiler Tests 4 Tests
Compression Tests 4 Tests
CPU Massive 4 Tests
Creator Workloads 2 Tests
HPC - High Performance Computing 2 Tests
Multi-Core 5 Tests
Programmer / Developer System Benchmarks 2 Tests
Server CPU Tests 4 Tests

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  Test
  Duration
Ryzen 5 7600X
October 04 2022
  3 Hours, 28 Minutes
7600X
October 04 2022
  4 Hours, 33 Minutes
AMD 7600X
October 04 2022
  3 Hours, 36 Minutes
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  3 Hours, 52 Minutes

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Ryzen 5 7600X Extra Linux Suite 1.0.0 System Test suite extracted from Ryzen 5 7600X Extra Linux. pts/smhasher-1.1.0 --test=Speed wyhash Hash: wyhash pts/smhasher-1.1.0 --test=Speed sha3-256 Hash: SHA3-256 pts/smhasher-1.1.0 --test=Speed Spooky32 Hash: Spooky32 pts/smhasher-1.1.0 --test=Speed fasthash32 Hash: fasthash32 pts/smhasher-1.1.0 --test=Speed FarmHash128 Hash: FarmHash128 pts/smhasher-1.1.0 --test=Speed t1ha2_atonce Hash: t1ha2_atonce pts/smhasher-1.1.0 --test=Speed FarmHash32 Hash: FarmHash32 x86_64 AVX pts/smhasher-1.1.0 --test=Speed t1ha0_aes_avx2 Hash: t1ha0_aes_avx2 x86_64 pts/smhasher-1.1.0 --test=Speed MeowHash Hash: MeowHash x86_64 AES-NI pts/openfoam-1.2.0 incompressible/simpleFoam/motorBike/ Input: motorBike - Mesh Time pts/openfoam-1.2.0 incompressible/simpleFoam/motorBike/ Input: motorBike - Execution Time pts/openfoam-1.2.0 incompressible/simpleFoam/drivaerFastback/ -m S Input: drivaerFastback, Small Mesh Size - Mesh Time pts/openfoam-1.2.0 incompressible/simpleFoam/drivaerFastback/ -m S Input: drivaerFastback, Small Mesh Size - Execution Time pts/compress-lz4-1.0.0 -b1 -e1 Compression Level: 1 - Compression Speed pts/compress-lz4-1.0.0 -b1 -e1 Compression Level: 1 - Decompression Speed pts/compress-lz4-1.0.0 -b3 -e3 Compression Level: 3 - Compression Speed pts/compress-lz4-1.0.0 -b3 -e3 Compression Level: 3 - Decompression Speed pts/compress-lz4-1.0.0 -b9 -e9 Compression Level: 9 - Compression Speed pts/compress-lz4-1.0.0 -b9 -e9 Compression Level: 9 - Decompression Speed pts/compress-zstd-1.5.0 -b3 Compression Level: 3 - Compression Speed pts/compress-zstd-1.5.0 -b3 Compression Level: 3 - Decompression Speed pts/compress-zstd-1.5.0 -b8 Compression Level: 8 - Compression Speed pts/compress-zstd-1.5.0 -b8 Compression Level: 8 - Decompression Speed pts/compress-zstd-1.5.0 -b19 Compression Level: 19 - Compression Speed pts/compress-zstd-1.5.0 -b19 Compression Level: 19 - Decompression Speed pts/compress-zstd-1.5.0 -b3 --long Compression Level: 3, Long Mode - Compression Speed pts/compress-zstd-1.5.0 -b3 --long Compression Level: 3, Long Mode - Decompression Speed pts/compress-zstd-1.5.0 -b8 --long Compression Level: 8, Long Mode - Compression Speed pts/compress-zstd-1.5.0 -b8 --long Compression Level: 8, Long Mode - Decompression Speed pts/compress-zstd-1.5.0 -b19 --long Compression Level: 19, Long Mode - Compression Speed pts/compress-zstd-1.5.0 -b19 --long Compression Level: 19, Long Mode - Decompression Speed pts/aom-av1-3.5.0 --cpu-used=0 --limit=20 Bosphorus_3840x2160.y4m Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 4K pts/aom-av1-3.5.0 --cpu-used=4 Bosphorus_3840x2160.y4m Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 4K pts/aom-av1-3.5.0 --cpu-used=6 --rt Bosphorus_3840x2160.y4m Encoder Mode: Speed 6 Realtime - Input: Bosphorus 4K pts/aom-av1-3.5.0 --cpu-used=6 Bosphorus_3840x2160.y4m Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 4K pts/aom-av1-3.5.0 --cpu-used=8 --rt Bosphorus_3840x2160.y4m Encoder Mode: Speed 8 Realtime - Input: Bosphorus 4K pts/aom-av1-3.5.0 --cpu-used=9 --rt Bosphorus_3840x2160.y4m Encoder Mode: Speed 9 Realtime - Input: Bosphorus 4K pts/aom-av1-3.5.0 --cpu-used=10 --rt Bosphorus_3840x2160.y4m Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K pts/aom-av1-3.5.0 --cpu-used=0 --limit=20 Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 0 Two-Pass - Input: Bosphorus 1080p pts/aom-av1-3.5.0 --cpu-used=4 Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 4 Two-Pass - Input: Bosphorus 1080p pts/aom-av1-3.5.0 --cpu-used=6 --rt Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 6 Realtime - Input: Bosphorus 1080p pts/aom-av1-3.5.0 --cpu-used=6 Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 6 Two-Pass - Input: Bosphorus 1080p pts/aom-av1-3.5.0 --cpu-used=8 --rt Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 8 Realtime - Input: Bosphorus 1080p pts/aom-av1-3.5.0 --cpu-used=9 --rt Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 9 Realtime - Input: Bosphorus 1080p pts/aom-av1-3.5.0 --cpu-used=10 --rt Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Encoder Mode: Speed 10 Realtime - Input: Bosphorus 1080p pts/compress-7zip-1.10.0 Test: Compression Rating pts/compress-7zip-1.10.0 Test: Decompression Rating pts/build-linux-kernel-1.14.0 defconfig Build: defconfig pts/build-linux-kernel-1.14.0 allmodconfig Build: allmodconfig pts/y-cruncher-1.2.0 1b Pi Digits To Calculate: 1B pts/y-cruncher-1.2.0 500m Pi Digits To Calculate: 500M pts/onednn-2.7.0 --ip --batch=inputs/ip/shapes_1d --cfg=f32 --engine=cpu Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU pts/onednn-2.7.0 --ip --batch=inputs/ip/shapes_3d --cfg=f32 --engine=cpu Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU pts/onednn-2.7.0 --ip --batch=inputs/ip/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU pts/onednn-2.7.0 --ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU pts/onednn-2.7.0 --ip --batch=inputs/ip/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-2.7.0 --ip --batch=inputs/ip/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-2.7.0 --conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU pts/onednn-2.7.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU pts/onednn-2.7.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU pts/onednn-2.7.0 --conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU pts/onednn-2.7.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU pts/onednn-2.7.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU pts/onednn-2.7.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU pts/onednn-2.7.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU pts/onednn-2.7.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU pts/onednn-2.7.0 --conv --batch=inputs/conv/shapes_auto --cfg=bf16bf16bf16 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-2.7.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-2.7.0 --deconv --batch=inputs/deconv/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-2.7.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=u8s8f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU pts/onednn-2.7.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU pts/onednn-2.7.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-2.7.0 --rnn --batch=inputs/rnn/perf_rnn_inference_lb --cfg=bf16bf16bf16 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-2.7.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=u8s8f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU pts/onednn-2.7.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=bf16bf16bf16 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: bf16bf16bf16 - Engine: CPU pts/compress-gzip-1.2.0 Linux Source Tree Archiving To .tar.gz