AMD SME Benchmark Genoa

4th Gen AMD EPYC "Genoa" Secure Memory Encryption (SME) benchmarks by Michael Larabel for a future article.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2212212-NE-AMDSMEBEN19
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AV1 3 Tests
BLAS (Basic Linear Algebra Sub-Routine) Tests 3 Tests
C++ Boost Tests 4 Tests
Timed Code Compilation 4 Tests
C/C++ Compiler Tests 11 Tests
Compression Tests 2 Tests
CPU Massive 19 Tests
Creator Workloads 18 Tests
Encoding 6 Tests
Fortran Tests 5 Tests
Game Development 6 Tests
HPC - High Performance Computing 23 Tests
Java 2 Tests
LAPACK (Linear Algebra Pack) Tests 2 Tests
Machine Learning 5 Tests
Molecular Dynamics 6 Tests
MPI Benchmarks 6 Tests
Multi-Core 30 Tests
NVIDIA GPU Compute 3 Tests
Intel oneAPI 7 Tests
OpenMPI Tests 14 Tests
Programmer / Developer System Benchmarks 6 Tests
Python Tests 9 Tests
Raytracing 2 Tests
Renderers 4 Tests
Scientific Computing 8 Tests
Software Defined Radio 2 Tests
Server 2 Tests
Server CPU Tests 15 Tests
Texture Compression 2 Tests
Video Encoding 6 Tests
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No SME
December 20 2022
  8 Hours, 15 Minutes
AMD SME Enabled
December 19 2022
  7 Hours, 52 Minutes
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  8 Hours, 4 Minutes
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AMD SME Benchmark Genoa Suite 1.0.0 System Test suite extracted from AMD SME Benchmark Genoa. pts/quantlib-1.0.0 pts/hpcg-1.2.1 pts/npb-1.4.5 bt.C Test / Class: BT.C pts/npb-1.4.5 ep.C Test / Class: EP.C pts/npb-1.4.5 ft.C Test / Class: FT.C pts/npb-1.4.5 sp.C Test / Class: SP.C pts/minibude-1.0.0 --deck ../data/bm1 --iterations 500 Implementation: OpenMP - Input Deck: BM1 pts/minibude-1.0.0 --deck ../data/bm2 --iterations 10 Implementation: OpenMP - Input Deck: BM2 pts/rodinia-1.3.2 OMP_LAVAMD Test: OpenMP LavaMD pts/rodinia-1.3.2 OMP_CFD Test: OpenMP CFD Solver pts/namd-1.2.1 ATPase Simulation - 327,506 Atoms pts/nwchem-1.1.1 Input: C240 Buckyball pts/incompact3d-2.0.2 input_193_nodes.i3d Input: input.i3d 193 Cells Per Direction 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/openradioss-1.0.0 Bumper_Beam_AP_meshed_0000.rad Bumper_Beam_AP_meshed_0001.rad Model: Bumper Beam pts/openradioss-1.0.0 Cell_Phone_Drop_0000.rad Cell_Phone_Drop_0001.rad Model: Cell Phone Drop Test pts/openradioss-1.0.0 fsi_drop_container_0000.rad fsi_drop_container_0001.rad Model: INIVOL and Fluid Structure Interaction Drop Container pts/relion-1.0.1 --iter 1 --cpu --j 2 Test: Basic - Device: CPU pts/lulesh-1.1.1 pts/xmrig-1.1.0 --bench=1M Variant: Monero - Hash Count: 1M pts/xmrig-1.1.0 -a rx/wow --bench=1M Variant: Wownero - Hash Count: 1M pts/dacapobench-1.0.1 h2 Java Test: H2 pts/renaissance-1.3.0 finagle-http Test: Finagle HTTP Requests pts/renaissance-1.3.0 db-shootout Test: In-Memory Database Shootout 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/srsran-1.2.0 lib/src/phy/dft/test/ofdm_test -N 2048 -n 100 -r 500000 Test: OFDM_Test pts/srsran-1.2.0 lib/test/phy/phy_dl_test -p 100 -s 20000 -m 28 -t 4 Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM pts/srsran-1.2.0 lib/test/phy/phy_dl_test -p 100 -s 20000 -m 28 -t 1 Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM pts/srsran-1.2.0 lib/test/phy/phy_dl_test -p 100 -s 20000 -m 27 -t 4 -q Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM pts/srsran-1.2.0 lib/test/phy/phy_dl_test -p 100 -s 20000 -m 27 -t 1 -q Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM pts/srsran-1.2.0 lib/test/phy/phy_dl_nr_test -P 52 -p 52 -m 28 -n 20000 Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM pts/aom-av1-3.5.0 --cpu-used=10 --rt Bosphorus_3840x2160.y4m Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K pts/embree-1.2.1 pathtracer_ispc -c crown/crown.ecs Binary: Pathtracer ISPC - Model: Crown pts/kvazaar-1.1.1 -i Bosphorus_3840x2160.y4m --preset veryfast Video Input: Bosphorus 4K - Video Preset: Very Fast pts/kvazaar-1.1.1 -i Bosphorus_3840x2160.y4m --preset ultrafast Video Input: Bosphorus 4K - Video Preset: Ultra Fast pts/svt-av1-2.7.0 --preset 13 -i Bosphorus_3840x2160.y4m -w 3840 -h 2160 Encoder Mode: Preset 13 - Input: Bosphorus 4K pts/x264-2.7.0 Bosphorus_3840x2160.y4m Video Input: Bosphorus 4K pts/x265-1.3.0 Bosphorus_3840x2160.y4m Video Input: Bosphorus 4K pts/mt-dgemm-1.2.0 Sustained Floating-Point Rate pts/oidn-1.4.0 -r RTLightmap.hdr.4096x4096 Run: RTLightmap.hdr.4096x4096 pts/openvkl-1.3.0 vklBenchmark --benchmark_filter=ispc Benchmark: vklBenchmark ISPC pts/ospray-2.10.0 --benchmark_filter=particle_volume/pathtracer/real_time Benchmark: particle_volume/pathtracer/real_time pts/ospray-2.10.0 --benchmark_filter=gravity_spheres_volume/dim_512/ao/real_time Benchmark: gravity_spheres_volume/dim_512/ao/real_time pts/compress-7zip-1.10.0 Test: Compression Rating pts/compress-7zip-1.10.0 Test: Decompression Rating pts/avifenc-1.3.0 -s 2 Encoder Speed: 2 pts/avifenc-1.3.0 -s 6 Encoder Speed: 6 pts/build-gem5-1.0.0 Time To Compile pts/build-godot-1.0.0 Time To Compile pts/build-linux-kernel-1.15.0 defconfig Build: defconfig pts/build-linux-kernel-1.15.0 allmodconfig Build: allmodconfig pts/build-llvm-1.4.0 Ninja Build System: Ninja pts/build-llvm-1.4.0 Build System: Unix Makefiles pts/ospray-studio-1.1.0 --cameras 3 3 --resolution 3840 2160 --spp 32 --renderer pathtracer Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer pts/liquid-dsp-1.0.0 -n 256 -b 256 -f 57 Threads: 256 - Buffer Length: 256 - Filter Length: 57 pts/liquid-dsp-1.0.0 -n 384 -b 256 -f 57 Threads: 384 - Buffer Length: 256 - Filter Length: 57 pts/askap-2.1.0 tConvolveMPI Test: tConvolve MPI - Degridding pts/askap-2.1.0 tConvolveMPI Test: tConvolve MPI - Gridding pts/astcenc-1.4.0 -thorough -repeats 10 Preset: Thorough pts/astcenc-1.4.0 -exhaustive -repeats 2 Preset: Exhaustive pts/graph500-1.0.1 26 Scale: 26 pts/gromacs-1.7.0 mpi-build water-cut1.0_GMX50_bare/1536 Implementation: MPI CPU - Input: water_GMX50_bare pts/pgbench-1.12.0 -s 100 -c 250 -S Scaling Factor: 100 - Clients: 250 - Mode: Read Only pts/tensorflow-2.0.0 --device cpu --batch_size=64 --model=alexnet Device: CPU - Batch Size: 64 - Model: AlexNet pts/toktx-1.0.1 --zcmp 9 Settings: Zstd Compression 9 pts/toktx-1.0.1 --zcmp 19 Settings: Zstd Compression 19 pts/deepsparse-1.0.1 zoo:nlp/document_classification/obert-base/pytorch/huggingface/imdb/base-none --scenario async Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.0.1 zoo:nlp/question_answering/bert-base/pytorch/huggingface/squad/12layer_pruned90-none --scenario async Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.0.1 zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none --scenario async Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.0.1 zoo:cv/classification/resnet_v1-50/pytorch/sparseml/imagenet/base-none --scenario async Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.0.1 zoo:nlp/text_classification/distilbert-none/pytorch/huggingface/mnli/base-none --scenario async Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.0.1 zoo:nlp/text_classification/bert-base/pytorch/huggingface/sst2/base-none --scenario async Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream pts/deepsparse-1.0.1 zoo:nlp/token_classification/bert-base/pytorch/huggingface/conll2003/base-none --scenario async Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream pts/wrf-1.0.1 -i conus 2.5km Input: conus 2.5km pts/gpaw-1.1.0 carbon-nanotube Input: Carbon Nanotube pts/blender-3.4.0 -b ../classroom_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: Classroom - Compute: CPU-Only pts/blender-3.4.0 -b ../barbershop_interior_gpu.blend -o output.test -x 1 -F JPEG -f 1 -- --cycles-device CPU Blend File: Barbershop - Compute: CPU-Only pts/openvino-1.1.0 -m models/intel/face-detection-0206/FP16/face-detection-0206.xml -d CPU Model: Face Detection FP16 - Device: CPU pts/openvino-1.1.0 -m models/intel/person-detection-0106/FP16/person-detection-0106.xml -d CPU Model: Person Detection FP16 - Device: CPU pts/openvino-1.1.0 -m models/intel/person-detection-0106/FP32/person-detection-0106.xml -d CPU Model: Person Detection FP32 - Device: CPU pts/openvino-1.1.0 -m models/intel/vehicle-detection-0202/FP16/vehicle-detection-0202.xml -d CPU Model: Vehicle Detection FP16 - Device: CPU pts/openvino-1.1.0 -m models/intel/face-detection-0206/FP16-INT8/face-detection-0206.xml -d CPU Model: Face Detection FP16-INT8 - Device: CPU pts/openvino-1.1.0 -m models/intel/vehicle-detection-0202/FP16-INT8/vehicle-detection-0202.xml -d CPU Model: Vehicle Detection FP16-INT8 - Device: CPU pts/openvino-1.1.0 -m models/intel/weld-porosity-detection-0001/FP16/weld-porosity-detection-0001.xml -d CPU Model: Weld Porosity Detection FP16 - Device: CPU pts/openvino-1.1.0 -m models/intel/machine-translation-nar-en-de-0002/FP16/machine-translation-nar-en-de-0002.xml -d CPU Model: Machine Translation EN To DE FP16 - Device: CPU pts/openvino-1.1.0 -m models/intel/weld-porosity-detection-0001/FP16-INT8/weld-porosity-detection-0001.xml -d CPU Model: Weld Porosity Detection FP16-INT8 - Device: CPU pts/openvino-1.1.0 -m models/intel/person-vehicle-bike-detection-2004/FP16/person-vehicle-bike-detection-2004.xml -d CPU Model: Person Vehicle Bike Detection FP16 - Device: CPU pts/openvino-1.1.0 -m models/intel/age-gender-recognition-retail-0013/FP16/age-gender-recognition-retail-0013.xml -d CPU Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU pts/openvino-1.1.0 -m models/intel/age-gender-recognition-retail-0013/FP16-INT8/age-gender-recognition-retail-0013.xml -d CPU Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU pts/xsbench-1.0.0 pts/nginx-3.0.0 -c 500 Connections: 500 pts/onnx-1.5.0 super_resolution/super_resolution.onnx -e cpu Model: super-resolution-10 - Device: CPU - Executor: Standard pts/appleseed-1.0.1 emily.appleseed Scene: Emily pts/pyhpc-3.0.0 --device cpu -b numpy -s 4194304 benchmarks/equation_of_state/ Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Equation of State pts/pyhpc-3.0.0 --device cpu -b numpy -s 4194304 benchmarks/isoneutral_mixing/ Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Isoneutral Mixing pts/onednn-3.0.0 --ip --batch=inputs/ip/shapes_3d --cfg=u8s8f32 --engine=cpu Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.0.0 --ip --batch=inputs/ip/shapes_3d --cfg=bf16bf16bf16 --engine=cpu Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU pts/onednn-3.0.0 --conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU pts/onednn-3.0.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU pts/onednn-3.0.0 --deconv --batch=inputs/deconv/shapes_1d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU pts/onednn-3.0.0 --rnn --batch=inputs/rnn/perf_rnn_training --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU