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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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 4th Gen AMD EPYC "Genoa" Secure Memory Encryption (SME) benchmarks by Michael Larabel for a future article. ,,"No SME","AMD SME Enabled" Processor,,2 x AMD EPYC 9654 96-Core @ 2.40GHz (192 Cores / 384 Threads),2 x AMD EPYC 9654 96-Core @ 2.40GHz (192 Cores / 384 Threads) Motherboard,,AMD Titanite_4G (RTI1002E BIOS),AMD Titanite_4G (RTI1002E BIOS) Chipset,,AMD Device 14a4,AMD Device 14a4 Memory,,1520GB,1520GB Disk,,800GB INTEL SSDPF21Q800GB,800GB INTEL SSDPF21Q800GB Graphics,,ASPEED,ASPEED Monitor,,VGA HDMI,VGA HDMI Network,,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe OS,,Ubuntu 22.10,Ubuntu 22.10 Kernel,,6.1.0-phx (x86_64),6.1.0-phx (x86_64) Desktop,,GNOME Shell 43.0,GNOME Shell 43.0 Display Server,,X Server 1.21.1.4,X Server 1.21.1.4 Vulkan,,1.3.224,1.3.224 Compiler,,GCC 12.2.0 + Clang 15.0.2-1,GCC 12.2.0 + Clang 15.0.2-1 File-System,,ext4,ext4 Screen Resolution,,1920x1080,1920x1080 ,,"No SME","AMD SME Enabled" "QuantLib - (MFLOPS)",HIB,3052.8,3061.3 "High Performance Conjugate Gradient - (GFLOP/s)",HIB,88.3902,87.1501 "NAS Parallel Benchmarks - Test / Class: BT.C (Mop/s)",HIB,496467.98,494917.44 "NAS Parallel Benchmarks - Test / Class: EP.C (Mop/s)",HIB,16457.94,16462.35 "NAS Parallel Benchmarks - Test / Class: FT.C (Mop/s)",HIB,223096.07,220214.75 "NAS Parallel Benchmarks - Test / Class: SP.C (Mop/s)",HIB,255564.19,253299.33 "miniBUDE - Implementation: OpenMP - Input Deck: BM1 (GFInst/s)",HIB,7281.284,7290.636 "miniBUDE - Implementation: OpenMP - Input Deck: BM1 (Billion Interactions/s)",HIB,291.251,291.625 "miniBUDE - Implementation: OpenMP - Input Deck: BM2 (GFInst/s)",HIB,8633.544,8588.749 "miniBUDE - Implementation: OpenMP - Input Deck: BM2 (Billion Interactions/s)",HIB,345.342,343.550 "Rodinia - Test: OpenMP LavaMD (sec)",LIB,16.508,16.669 "Rodinia - Test: OpenMP CFD Solver (sec)",LIB,5.938,6.043 "NAMD - ATPase Simulation - 327,506 Atoms (days/ns)",LIB,0.12831,0.12991 "NWChem - Input: C240 Buckyball (sec)",LIB,1524.4,1543.1 "Xcompact3d Incompact3d - Input: input.i3d 193 Cells Per Direction (sec)",LIB,4.37420527,4.42424568 "OpenFOAM - Input: drivaerFastback, Small Mesh Size - Mesh Time (sec)",LIB,25.06787,27.099458 "OpenFOAM - Input: drivaerFastback, Small Mesh Size - Execution Time (sec)",LIB,22.084264,22.13302 "OpenRadioss - Model: Bumper Beam (sec)",LIB,79.85,79.97 "OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,18.45,18.32 "OpenRadioss - Model: INIVOL and Fluid Structure Interaction Drop Container (sec)",LIB,80.88,80.90 "RELION - Test: Basic - Device: CPU (sec)",LIB,128.655,130.426 "LULESH - (z/s)",HIB,59069.405,57686.086 "Xmrig - Variant: Monero - Hash Count: 1M (H/s)",HIB,105141.7,101932.1 "Xmrig - Variant: Wownero - Hash Count: 1M (H/s)",HIB,126508.3,123484.1 "DaCapo Benchmark - Java Test: H2 (msec)",LIB,4807,5050 "Renaissance - Test: Finagle HTTP Requests (ms)",LIB,12286.3,12347.5 "Renaissance - Test: In-Memory Database Shootout (ms)",LIB,4764.6,4838.5 "Zstd Compression - Compression Level: 19, Long Mode - Compression Speed (MB/s)",HIB,52.9,49.9 "Zstd Compression - Compression Level: 19, Long Mode - Decompression Speed (MB/s)",HIB,3825.0,3837.3 "srsRAN - Test: OFDM_Test (Samples / Second)",HIB,161733333,162633333 "srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM (eNb Mb/s)",HIB,415.1,408.5 "srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 64-QAM (UE Mb/s)",HIB,157.8,157.7 "srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM (eNb Mb/s)",HIB,413.9,415.7 "srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 64-QAM (UE Mb/s)",HIB,165.8,165.9 "srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM (eNb Mb/s)",HIB,445.2,444.8 "srsRAN - Test: 4G PHY_DL_Test 100 PRB MIMO 256-QAM (UE Mb/s)",HIB,166.0,165.7 "srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM (eNb Mb/s)",HIB,444.0,445.7 "srsRAN - Test: 4G PHY_DL_Test 100 PRB SISO 256-QAM (UE Mb/s)",HIB,172.7,172.2 "srsRAN - Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM (eNb Mb/s)",HIB,139.7,139.1 "srsRAN - Test: 5G PHY_DL_NR Test 52 PRB SISO 64-QAM (UE Mb/s)",HIB,94.4,94.9 "AOM AV1 - Encoder Mode: Speed 10 Realtime - Input: Bosphorus 4K (FPS)",HIB,34.47,33.12 "Embree - Binary: Pathtracer ISPC - Model: Crown (FPS)",HIB,183.2528,180.5717 "Kvazaar - Video Input: Bosphorus 4K - Video Preset: Very Fast (FPS)",HIB,74.31,73.32 "Kvazaar - Video Input: Bosphorus 4K - Video Preset: Ultra Fast (FPS)",HIB,77.68,76.22 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,248.334,251.441 "x264 - Video Input: Bosphorus 4K (FPS)",HIB,106.86,103.07 "x265 - Video Input: Bosphorus 4K (FPS)",HIB,23.48,23.29 "ACES DGEMM - Sustained Floating-Point Rate (GFLOP/s)",HIB,70.372095,70.277437 "Intel Open Image Denoise - Run: RTLightmap.hdr.4096x4096 (Images / Sec)",HIB,1.66,1.66 "OpenVKL - Benchmark: vklBenchmark ISPC (Items / Sec)",HIB,1322,1286 "OSPRay - Benchmark: particle_volume/pathtracer/real_time (Items/sec)",HIB,230.617,229.879 "OSPRay - Benchmark: gravity_spheres_volume/dim_512/ao/real_time (Items/sec)",HIB,43.8478,43.3785 "7-Zip Compression - Test: Compression Rating (MIPS)",HIB,917782,885135 "7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,1160632,1169038 "libavif avifenc - Encoder Speed: 2 (sec)",LIB,34.690,35.260 "libavif avifenc - Encoder Speed: 6 (sec)",LIB,2.393,2.469 "Timed Gem5 Compilation - Time To Compile (sec)",LIB,138.639,142.181 "Timed Godot Game Engine Compilation - Time To Compile (sec)",LIB,34.141,35.038 "Timed Linux Kernel Compilation - Build: defconfig (sec)",LIB,25.709,25.303 "Timed Linux Kernel Compilation - Build: allmodconfig (sec)",LIB,146.325,148.435 "Timed LLVM Compilation - Build System: Ninja (sec)",LIB,75.329,76.629 "Timed LLVM Compilation - Build System: Unix Makefiles (sec)",LIB,160.129,162.629 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer (ms)",LIB,22043,22614 "Liquid-DSP - Threads: 256 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,10332000000,10344666667 "Liquid-DSP - Threads: 384 - Buffer Length: 256 - Filter Length: 57 (samples/s)",HIB,10346000000,10350000000 "ASKAP - Test: tConvolve MPI - Degridding (Mpix/sec)",HIB,83598.3,78718.7 "ASKAP - Test: tConvolve MPI - Gridding (Mpix/sec)",HIB,93071.0,89541.8 "ASTC Encoder - Preset: Thorough (MT/s)",HIB,106.4244,106.5566 "ASTC Encoder - Preset: Exhaustive (MT/s)",HIB,11.8206,11.8379 "Graph500 - Scale: 26 (bfs median_TEPS)",HIB,1426480000,1358510000 "Graph500 - Scale: 26 (bfs max_TEPS)",HIB,1533180000,1526380000 "Graph500 - Scale: 26 (sssp median_TEPS)",HIB,593153000,572510000 "Graph500 - Scale: 26 (sssp max_TEPS)",HIB,838505000,835467000 "GROMACS - Implementation: MPI CPU - Input: water_GMX50_bare (Ns/Day)",HIB,18.712,18.623 "PostgreSQL - Scaling Factor: 100 - Clients: 250 - Mode: Read Only (TPS)",HIB,2951147,2970869 "TensorFlow - Device: CPU - Batch Size: 64 - Model: AlexNet (images/sec)",HIB,508.40,505.26 "KTX-Software toktx - Settings: Zstd Compression 9 (sec)",LIB,2.734,2.776 "KTX-Software toktx - Settings: Zstd Compression 19 (sec)",LIB,18.863,19.881 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,84.2500,83.6363 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,1134.4234,1143.0364 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,762.6984,745.6412 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,125.5335,128.4001 "Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,858.4729,840.9404 "Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,111.4614,113.8270 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,1962.1024,1911.3999 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,48.8291,50.1080 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,1204.8491,1178.9990 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,79.4895,81.2258 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,617.0281,601.9341 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,155.1029,158.9428 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,84.2764,83.8173 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,1133.3132,1143.0106 "WRF - Input: conus 2.5km (sec)",LIB,4077.189,4116.62 "GPAW - Input: Carbon Nanotube (sec)",LIB,23.167,22.981 "Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,20.99,20.95 "Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,80.77,81.57 "OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,101.90,101.55 "OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,469.81,471.53 "OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,43.29,42.33 "OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,1102.15,1127.51 "OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,42.76,42.03 "OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,1115.56,1134.68 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,7437.73,7274.98 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,6.44,6.59 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,193.95,193.83 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,246.95,247.23 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,11180.63,11184.76 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,4.28,4.28 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,9997.68,9990.19 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,4.79,4.79 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,967.90,963.14 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,49.54,49.78 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,19801.40,19704.84 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,9.62,9.67 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,9027.72,8993.90 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,5.31,5.33 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,150792.42,148736.04 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,0.55,0.55 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,165194.42,167545.54 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,0.36,0.36 "Xsbench - (Lookups/s)",HIB,29806415,29021428 "nginx - Connections: 500 (Reqs/sec)",HIB,201056.69,196386.41 "ONNX Runtime - Model: super-resolution-10 - Device: CPU - Executor: Standard (Inferences/min)",HIB,5600,5583 "Appleseed - Scene: Emily (sec)",LIB,142.94702,150.92071 "PyHPC Benchmarks - Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Equation of State (sec)",LIB,0.884,0.934 "PyHPC Benchmarks - Device: CPU - Backend: Numpy - Project Size: 4194304 - Benchmark: Isoneutral Mixing (sec)",LIB,1.691,1.744 "oneDNN - Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.863726,0.850418 "oneDNN - Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU (ms)",LIB,3.89299,3.92313 "oneDNN - Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU (ms)",LIB,0.522052,0.526628 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU (ms)",LIB,22.6795,23.1429 "oneDNN - Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU (ms)",LIB,0.916133,0.918482 "oneDNN - Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU (ms)",LIB,2011.15,2002.43