AMD EPYC 9754 Bergamo SMT On/Off Comparison

Benchmarks by Michael Larabel for a future article (post 19th) looking at SMT on/off comparison toggled via BIOS. SMT comparison testing of AMD EPYC 9754 128-Core CPUs on Titanite with Ubuntu 22.04 LTS.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2307190-NE-BERGAMOSM27
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C++ Boost Tests 2 Tests
Timed Code Compilation 5 Tests
C/C++ Compiler Tests 8 Tests
CPU Massive 14 Tests
Creator Workloads 11 Tests
Cryptography 4 Tests
Database Test Suite 2 Tests
Fortran Tests 5 Tests
Game Development 5 Tests
HPC - High Performance Computing 11 Tests
Common Kernel Benchmarks 2 Tests
Machine Learning 3 Tests
Molecular Dynamics 4 Tests
MPI Benchmarks 2 Tests
Multi-Core 23 Tests
NVIDIA GPU Compute 2 Tests
Intel oneAPI 6 Tests
OpenMPI Tests 8 Tests
Programmer / Developer System Benchmarks 5 Tests
Python Tests 8 Tests
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Scientific Computing 4 Tests
Software Defined Radio 2 Tests
Server 3 Tests
Server CPU Tests 12 Tests

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  Test
  Duration
EPYC 9754 1P: SMT On
July 14 2023
  16 Hours, 51 Minutes
EPYC 9754 1P: SMT Off
July 13 2023
  15 Hours, 43 Minutes
EPYC 9754 2P: SMT On
July 11 2023
  14 Hours, 12 Minutes
EPYC 9754 2P: SMT Off
July 12 2023
  13 Hours, 40 Minutes
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  15 Hours, 6 Minutes

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AMD EPYC 9754 Bergamo SMT On/Off Comparison Benchmarks by Michael Larabel for a future article (post 19th) looking at SMT on/off comparison toggled via BIOS. SMT comparison testing of AMD EPYC 9754 128-Core CPUs on Titanite with Ubuntu 22.04 LTS. ,,"EPYC 9754 1P: SMT On","EPYC 9754 1P: SMT Off","EPYC 9754 2P: SMT On","EPYC 9754 2P: SMT Off" Processor,,AMD EPYC 9754 128-Core @ 2.25GHz (128 Cores / 256 Threads),AMD EPYC 9754 128-Core @ 2.25GHz (128 Cores),2 x AMD EPYC 9754 128-Core @ 2.25GHz (256 Cores / 512 Threads),2 x AMD EPYC 9754 128-Core @ 2.25GHz (256 Cores) Motherboard,,AMD Titanite_4G (RTI1007B BIOS),AMD Titanite_4G (RTI1007B BIOS),AMD Titanite_4G (RTI1007B BIOS),AMD Titanite_4G (RTI1007B BIOS) Chipset,,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4 Memory,,768GB,768GB,1520GB,1520GB Disk,,2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007,2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007,2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007,2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007 Graphics,,ASPEED,ASPEED,ASPEED,ASPEED Network,,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe OS,,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04,Ubuntu 22.04 Kernel,,5.19.0-41-generic (x86_64),5.19.0-41-generic (x86_64),5.19.0-41-generic (x86_64),5.19.0-41-generic (x86_64) Desktop,,GNOME Shell 42.5,GNOME Shell 42.5,GNOME Shell 42.5,GNOME Shell 42.5 Display Server,,X Server 1.21.1.4,X Server 1.21.1.4,X Server 1.21.1.4,X Server 1.21.1.4 Vulkan,,1.3.224,1.3.224,1.3.224,1.3.224 Compiler,,GCC 11.3.0,GCC 11.3.0,GCC 11.3.0,GCC 11.3.0 File-System,,ext4,ext4,ext4,ext4 Screen Resolution,,1024x768,1024x768,1024x768,1024x768 ,,"EPYC 9754 1P: SMT On","EPYC 9754 1P: SMT Off","EPYC 9754 2P: SMT On","EPYC 9754 2P: SMT Off" "CPU Power Consumption Monitor - Phoronix Test Suite System Monitoring (Watts)",,248.93,238.75,460.57,446.01 "Graph500 - Scale: 26 (bfs max_TEPS)",HIB,880249000,928320000,1724030000,2078880000 "Graph500 - Scale: 26 (bfs median_TEPS)",HIB,857890000,893624000,1571100000,1815160000 "miniBUDE - Implementation: OpenMP - Input Deck: BM1 (Billion Interactions/s)",HIB,237.763,234.684,253.123,439.067 "miniBUDE - Implementation: OpenMP - Input Deck: BM1 (Billion Interactions/s/Watt)",HIB,1.525,1.524,0.94,1.965 "miniBUDE - Implementation: OpenMP - Input Deck: BM2 (Billion Interactions/s/Watt)",HIB,0.883,0.881,0.819,0.949 "miniBUDE - Implementation: OpenMP - Input Deck: BM2 (Billion Interactions/s)",HIB,238.905,236.128,315.524,439.597 "OpenSSL - Algorithm: SHA256 (byte/s/Watt)",HIB,491268818.212,390668971.638,485100025.271,368054429.028 "OpenSSL - Algorithm: SHA256 (byte/s)",HIB,163633625553,111414557280,327926038513,222269428867 "OpenSSL - Algorithm: SHA512 (byte/s)",HIB,53005879330,51804333637,106049655203,102232233590 "OpenSSL - Algorithm: SHA512 (byte/s/Watt)",HIB,157871758.838,155713911.664,156820493.537,150591857.125 "OpenSSL - Algorithm: ChaCha20 (byte/s/Watt)",HIB,1812397903.613,1787936411.25,1804203926.06,1666389521.267 "OpenSSL - Algorithm: AES-128-GCM (byte/s/Watt)",HIB,3408107334.725,3373392798.471,3375379415.528,3357766493.214 "OpenSSL - Algorithm: AES-256-GCM (byte/s/Watt)",HIB,2960716545.712,2959773610.694,2919004979.804,2960156985.811 "OpenSSL - Algorithm: ChaCha20-Poly1305 (byte/s/Watt)",HIB,1284331827.017,1218755474.838,1256483723.09,1185929906.409 "OpenSSL - Algorithm: ChaCha20 (byte/s)",HIB,659346857987,550700307433,1317549954027,1100453394570 "OpenSSL - Algorithm: AES-128-GCM (byte/s)",HIB,1169673735557,1152838928063,2339890700107,2307524535457 "OpenSSL - Algorithm: AES-256-GCM (byte/s)",HIB,1012537766210,997034621883,2019317070327,1998234148863 "OpenSSL - Algorithm: ChaCha20-Poly1305 (byte/s)",HIB,462415837320,392782689987,909817360110,784489570523 "miniFE - Problem Size: Small (CG Mflops/Watt)",HIB,419.544,430.065,268.287,236.176 "miniFE - Problem Size: Small (CG Mflops)",HIB,51784.1,51741.0,62774.2,53798.6 "nekRS - Input: Kershaw (flops/rank)",HIB,5808636667,5734266667,, "nekRS - Input: TurboPipe Periodic (flops/rank)",HIB,2538406923,2586083333,, "nekRS - Input: Kershaw (flops/rank/Watt)",HIB,19786057.99,19236505.506,, "nekRS - Input: TurboPipe Periodic (flops/rank/Watt)",HIB,8806106.185,8992432.836,, "OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,60.77,62.18,121.03,121.08 "OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,26.61,28.74,40.67,41.05 "OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,26.57,28.83,40.90,40.20 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,1464.29,2784.67,5810.41,6242.68 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,117.88,119.01,235.65,235.37 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,5311.48,6744.66,13214.20,13141.51 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,6067.78,5837.62,11299.32,11373.95 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,582.08,545.13,1159.99,1174.99 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,11794.32,11710.59,22954.44,22955.64 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,6148.89,5118.29,9889.61,9878.88 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,120515.11,113162.29,168372.89,142135.58 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,85400.88,71673.85,133931.53,118225.55 "Embree - Binary: Pathtracer ISPC - Model: Crown (FPS)",HIB,125.5813,85.2893,210.0714,146.2051 "Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS)",HIB,157.6504,107.3608,255.9864,178.3046 "Embree - Binary: Pathtracer ISPC - Model: Crown (FPS/Watt)",HIB,0.655,0.416,0.668,0.42 "Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS/Watt)",HIB,0.925,0.584,0.895,0.57 "miniBUDE - Implementation: OpenMP - Input Deck: BM1 (GFInst/s)",HIB,5944.062,5867.108,6328.069,10976.682 "miniBUDE - Implementation: OpenMP - Input Deck: BM2 (GFInst/s)",HIB,5972.643,5903.205,7888.085,10989.938 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 512 (GFLOP/s)",HIB,34.8451,35.4049,109.645,112.413 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 512 (GFLOP/s/Watt)",HIB,0.682,0.692,0.548,0.569 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 512 (GFLOP/s/Watt)",HIB,1.445,1.507,1.289,1.263 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 512 (GFLOP/s)",HIB,66.3418,67.9907,207.197,210.933 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 512 (GFLOP/s/Watt)",HIB,0.14,0.144,0.239,0.252 "HeFFTe - Highly Efficient FFT for Exascale - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 512 (GFLOP/s)",HIB,128.124,128.597,221.765,223.584 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 512 (GFLOP/s/Watt)",HIB,0.284,0.296,0.507,0.521 "HeFFTe - Highly Efficient FFT for Exascale - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 512 (GFLOP/s)",HIB,245.542,248.557,433.601,430.265 "libxsmm - M N K: 128 (GFLOPS/s/Watt)",HIB,13.236,13.207,15.411,13.894 "libxsmm - M N K: 256 (GFLOPS/s/Watt)",HIB,15.777,18.121,19.039,19.923 "libxsmm - M N K: 128 (GFLOPS/s)",HIB,2713.4,2696.5,4976.7,4505.5 "libxsmm - M N K: 256 (GFLOPS/s)",HIB,3331.7,3813.4,6112.6,6373.0 "Xmrig - Variant: Monero - Hash Count: 1M (H/s/Watt)",HIB,109.988,191.101,177.288,185.91 "Xmrig - Variant: Wownero - Hash Count: 1M (H/s/Watt)",HIB,279.934,235.829,323.165,225.358 "Xmrig - Variant: Monero - Hash Count: 1M (H/s)",HIB,24409.4,51218.9,86533.7,85946.0 "Xmrig - Variant: Wownero - Hash Count: 1M (H/s)",HIB,74803.6,63182.2,142082.7,100754.3 "Intel Open Image Denoise - Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,3.62,3.57,4.76,4.35 "Intel Open Image Denoise - Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec)",HIB,3.62,3.57,4.78,4.31 "Intel Open Image Denoise - Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec/Watt)",HIB,0.021,0.021,0.016,0.015 "Intel Open Image Denoise - Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only (Images / Sec/Watt)",HIB,0.021,0.021,0.016,0.015 "Intel Open Image Denoise - Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only (Images / Sec/Watt)",HIB,0.008,0.008,0.006,0.006 "Intel Open Image Denoise - Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only (Images / Sec)",HIB,1.74,1.72,2.35,2.09 "TensorFlow - Device: CPU - Batch Size: 256 - Model: AlexNet (images/sec)",HIB,1422.08,1375.33,1225.41,1581.66 "TensorFlow - Device: CPU - Batch Size: 512 - Model: AlexNet (images/sec)",HIB,1628.80,1526.81,1770.91,1908.76 "TensorFlow - Device: CPU - Batch Size: 256 - Model: ResNet-50 (images/sec/Watt)",HIB,0.536,0.546,0.319,0.361 "TensorFlow - Device: CPU - Batch Size: 512 - Model: GoogLeNet (images/sec/Watt)",HIB,1.767,1.879,1.227,1.391 "TensorFlow - Device: CPU - Batch Size: 512 - Model: ResNet-50 (images/sec/Watt)",HIB,0.544,0.556,0.409,0.429 "TensorFlow - Device: CPU - Batch Size: 256 - Model: GoogLeNet (images/sec)",HIB,504.09,525.39,329.22,452.99 "TensorFlow - Device: CPU - Batch Size: 256 - Model: AlexNet (images/sec/Watt)",HIB,7.058,7.177,3.665,4.206 "TensorFlow - Device: CPU - Batch Size: 512 - Model: AlexNet (images/sec/Watt)",HIB,6.922,7.159,4.584,4.54 "TensorFlow - Device: CPU - Batch Size: 256 - Model: GoogLeNet (images/sec/Watt)",HIB,2.072,2.216,0.859,1.099 "TensorFlow - Device: CPU - Batch Size: 256 - Model: ResNet-50 (images/sec)",HIB,118.45,121.47,124.98,146.74 "TensorFlow - Device: CPU - Batch Size: 512 - Model: GoogLeNet (images/sec)",HIB,416.03,429.16,538.52,634.13 "TensorFlow - Device: CPU - Batch Size: 512 - Model: ResNet-50 (images/sec)",HIB,122.77,123.88,172.36,189.40 "OpenVKL - Benchmark: vklBenchmark ISPC (Items / Sec/Watt)",HIB,5.853,4.955,3.676,3.512 "OpenVKL - Benchmark: vklBenchmark ISPC (Items / Sec)",HIB,1396,1107,1720,1530 "OSPRay - Benchmark: particle_volume/ao/real_time (Items/sec)",HIB,30.8507,23.7333,49.1328,41.6567 "OSPRay - Benchmark: particle_volume/scivis/real_time (Items/sec)",HIB,30.8165,23.7210,49.2311,41.5531 "OSPRay - Benchmark: gravity_spheres_volume/dim_512/scivis/real_time (Items/sec)",HIB,31.9245,25.5121,52.7318,44.2889 "OSPRay - Benchmark: particle_volume/ao/real_time (Items/sec/Watt)",HIB,0.106,0.091,0.089,0.078 "OSPRay - Benchmark: gravity_spheres_volume/dim_512/ao/real_time (Items/sec)",HIB,32.6750,25.7178,53.8295,44.7104 "OSPRay - Benchmark: particle_volume/scivis/real_time (Items/sec/Watt)",HIB,0.127,0.112,0.102,0.09 "OSPRay - Benchmark: gravity_spheres_volume/dim_512/ao/real_time (Items/sec/Watt)",HIB,0.118,0.101,0.095,0.082 "OSPRay - Benchmark: gravity_spheres_volume/dim_512/scivis/real_time (Items/sec/Watt)",HIB,0.115,0.1,0.092,0.081 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,73.3807,96.9697,139.6590,182.4453 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,1376.2142,1780.4421,2627.3142,2730.4980 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,240.8667,246.3732,556.9411,590.8789 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,417.1186,504.3578,797.6248,1058.6776 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,968.6267,1275.7707,1868.3310,2409.8035 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,624.4789,812.1023,1190.7168,1541.9512 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,126.9310,134.5717,242.9589,290.7562 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,316.0466,404.2338,602.2602,770.1392 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,73.2077,97.0913,139.8821,182.5974 "Aircrack-ng - (k/s)",HIB,171120.354,149056.953,,128050.219 "Aircrack-ng - (k/s/Watt)",HIB,729.353,649.605,,352.948 "LuxCoreRender - Scene: DLSC - Acceleration: CPU (M samples/sec/Watt)",HIB,0.054,0.047,0.036,0.031 "LuxCoreRender - Scene: DLSC - Acceleration: CPU (M samples/sec)",HIB,16.34,13.27,18.61,14.45 "LuxCoreRender - Scene: Orange Juice - Acceleration: CPU (M samples/sec)",HIB,24.47,20.98,34.45,25.11 "LuxCoreRender - Scene: LuxCore Benchmark - Acceleration: CPU (M samples/sec)",HIB,12.18,8.88,9.86,6.97 "LuxCoreRender - Scene: Rainbow Colors and Prism - Acceleration: CPU (M samples/sec)",HIB,20.88,14.37,19.02,13.51 "LuxCoreRender - Scene: Orange Juice - Acceleration: CPU (M samples/sec/Watt)",HIB,0.082,0.071,0.062,0.05 "LuxCoreRender - Scene: LuxCore Benchmark - Acceleration: CPU (M samples/sec/Watt)",HIB,0.043,0.036,0.022,0.017 "LuxCoreRender - Scene: Rainbow Colors and Prism - Acceleration: CPU (M samples/sec/Watt)",HIB,0.147,0.105,0.068,0.048 "srsRAN Project - Test: PUSCH Processor Benchmark, Throughput Total (Mbps/Watt)",HIB,32.09,78.408,31.904,70.644 "srsRAN Project - Test: PUSCH Processor Benchmark, Throughput Total (Mbps)",HIB,8389.0,20430.9,17891.4,36573.8 "7-Zip Compression - Test: Decompression Rating (MIPS/Watt)",HIB,2973.577,2063.781,2700.351,1933.657 "7-Zip Compression - Test: Compression Rating (MIPS)",HIB,726271,592741,925820,771462 "7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,791787,510470,1353957,913091 "ASTC Encoder - Preset: Fast (MT/s)",HIB,1190.7549,1278.6466,610.1137,693.3961 "ASTC Encoder - Preset: Thorough (MT/s)",HIB,75.0831,68.3072,134.8853,127.2088 "ASTC Encoder - Preset: Exhaustive (MT/s)",HIB,8.1743,7.3147,15.9305,14.4099 "ASTC Encoder - Preset: Fast (MT/s/Watt)",HIB,9.671,10.898,2.47,2.954 "ASTC Encoder - Preset: Thorough (MT/s/Watt)",HIB,0.561,0.507,0.592,0.577 "ASTC Encoder - Preset: Exhaustive (MT/s/Watt)",HIB,0.047,0.042,0.056,0.052 "Stockfish - Total Time (Nodes/s/Watt)",HIB,1117842.325,881021.758,896399.09,746293.69 "Stockfish - Total Time (Nodes/s)",HIB,365034349,272722940,582386924,447023143 "MariaDB - Clients: 2048 (Queries/sec/Watt)",HIB,6.371,6.363,2.365,2.322 "MariaDB - Clients: 2048 (Queries/sec)",HIB,780,783,580,591 "MariaDB - Clients: 4096 (Queries/sec)",HIB,655,695,545,579 "MariaDB - Clients: 4096 (Queries/sec/Watt)",HIB,5.367,5.642,2.176,2.249 "John The Ripper - Test: bcrypt (Real C/S)",HIB,216064,163220,407860,317046 "John The Ripper - Test: bcrypt (Real C/S/Watt)",HIB,770.869,642.02,736.92,585.474 "John The Ripper - Test: WPA PSK (Real C/S)",HIB,810375,676218,1524533,1301500 "John The Ripper - Test: Blowfish (Real C/S)",HIB,216115,163263,409850,320885 "John The Ripper - Test: MD5 (Real C/S)",HIB,20312667,16751667,34879333,30221667 "John The Ripper - Test: WPA PSK (Real C/S/Watt)",HIB,2324.365,2240.311,2235.809,2047.362 "John The Ripper - Test: Blowfish (Real C/S/Watt)",HIB,768.1,632.575,726.352,582.125 "John The Ripper - Test: MD5 (Real C/S/Watt)",HIB,69625.899,56420.63,67440.803,57347.314 "Liquid-DSP - Threads: 256 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,1696766667,1313933333,2544400000,2542633333 "Liquid-DSP - Threads: 256 - Buffer Length: 256 - Filter Length: 512 (samples/s/Watt)",HIB,6258723.142,5048094.719,4829201.803,4850824.912 "Liquid-DSP - Threads: 512 - Buffer Length: 256 - Filter Length: 512 (samples/s)",HIB,1783700000,1414700000,3330166667,2610933333 "Liquid-DSP - Threads: 512 - Buffer Length: 256 - Filter Length: 512 (samples/s/Watt)",HIB,6669884.777,5445501.581,6142943.885,5062810.801 "OpenSSL - Algorithm: RSA4096 (sign/s)",HIB,54195.1,56647.3,108490.5,113251.4 "Graph500 - Scale: 26 (sssp max_TEPS/Watt)",HIB,1520544.666,1719832.822,1513281.143,1664973.761 "Graph500 - Scale: 26 (sssp max_TEPS)",HIB,445912000,493535000,960471000,1075900000 "Graph500 - Scale: 26 (sssp median_TEPS)",HIB,333445000,363750000,672541000,770180000 "NAS Parallel Benchmarks - Test / Class: CG.C (Mop/s/Watt)",HIB,304.945,340.217,246.351,257.047 "NAS Parallel Benchmarks - Test / Class: EP.D (Mop/s/Watt)",HIB,55.591,62.247,59.29,69.13 "NAS Parallel Benchmarks - Test / Class: FT.C (Mop/s/Watt)",HIB,1044.17,1105.804,823.016,896.921 "NAS Parallel Benchmarks - Test / Class: IS.D (Mop/s/Watt)",HIB,35.7,35.4,31.241,28.072 "NAS Parallel Benchmarks - Test / Class: LU.C (Mop/s/Watt)",HIB,1448.627,1504.968,1821.348,2122.504 "NAS Parallel Benchmarks - Test / Class: MG.C (Mop/s/Watt)",HIB,1449.058,1502.137,1433.884,1554.078 "NAS Parallel Benchmarks - Test / Class: SP.B (Mop/s/Watt)",HIB,1171.422,1347.26,1034.034,1082.899 "NAS Parallel Benchmarks - Test / Class: SP.C (Mop/s/Watt)",HIB,625.95,657.404,567.818,602.823 "NAS Parallel Benchmarks - Test / Class: BT.C (Mop/s)",HIB,292243.61,298801.44,491231.83,536518.74 "NAS Parallel Benchmarks - Test / Class: CG.C (Mop/s)",HIB,45686.88,48672.24,67554.74,66822.97 "NAS Parallel Benchmarks - Test / Class: EP.D (Mop/s)",HIB,13264.79,14274.53,23705.40,25983.74 "NAS Parallel Benchmarks - Test / Class: FT.C (Mop/s)",HIB,140791.52,147448.72,211432.89,224178.10 "NAS Parallel Benchmarks - Test / Class: IS.D (Mop/s)",HIB,5300.29,5315.15,9849.01,8635.30 "NAS Parallel Benchmarks - Test / Class: BT.C (Mop/s/Watt)",HIB,1328.181,1382.295,1236.192,1408.279 "NAS Parallel Benchmarks - Test / Class: LU.C (Mop/s)",HIB,279662.55,289518.14,591505.17,658754.21 "NAS Parallel Benchmarks - Test / Class: MG.C (Mop/s)",HIB,128129.56,136942.13,249109.09,268721.05 "NAS Parallel Benchmarks - Test / Class: SP.B (Mop/s)",HIB,149355.54,161475.24,236490.76,246272.79 "NAS Parallel Benchmarks - Test / Class: SP.C (Mop/s)",HIB,131909.91,133415.42,224243.28,231041.57 "PostgreSQL - Scaling Factor: 1000 - Clients: 800 - Mode: Read Only (TPS)",HIB,855569,877722,827878,785968 "OpenSSL - Algorithm: RSA4096 (verify/s/Watt)",HIB,6020.72,6318.78,6122.565,6002.69 "OpenSSL - Algorithm: RSA4096 (verify/s)",HIB,1890935.3,1799293.0,3782091.8,3598946.3 "NAMD - ATPase Simulation - 327,506 Atoms (days/ns)",LIB,0.20702,0.20595,0.10646,0.13969 "toyBrot Fractal Generator - Implementation: TBB (ms)",LIB,3591,5590,2014,2976 "toyBrot Fractal Generator - Implementation: OpenMP (ms)",LIB,4081,6242,3321,3671 "OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer (ms)",LIB,861,1127,482,631 "OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer (ms)",LIB,873,1146,495,645 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer (ms)",LIB,1032,1358,582,763 "OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer (ms)",LIB,13759,18004,7698,10046 "OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer (ms)",LIB,27538,35926,15619,20133 "OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer (ms)",LIB,13963,18269,7817,10232 "OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer (ms)",LIB,27885,36539,15731,20545 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer (ms)",LIB,16484,21666,9253,12127 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer (ms)",LIB,32972,43371,18455,24238 "PostgreSQL - Scaling Factor: 1000 - Clients: 800 - Mode: Read Only - Average Latency (ms)",LIB,0.952,0.917,0.974,1.018 "OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,1049.31,513.23,526.98,526.46 "OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,2377.79,1105.96,1559.95,1545.23 "OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,2378.07,1102.82,1552.15,1579.14 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,43.73,11.49,11.03,10.26 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,541.29,268.82,270.93,271.24 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,12.07,4.74,4.83,4.86 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,10.53,5.47,5.64,5.61 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,110.00,58.71,55.12,54.42 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,10.84,10.91,11.00,11.10 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,10.40,6.24,6.46,6.47 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,0.83,0.70,0.62,0.67 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,1.21,1.30,1.08,1.13 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,859.8653,644.9768,902.8593,676.8128 "Neural Magic DeepSparse - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,46.4318,35.5549,48.6206,45.8765 "Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,267.7088,259.2779,229.1624,212.6821 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,152.9895,125.4467,159.8861,118.1285 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,65.9747,49.5111,68.3638,51.8103 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,102.2265,77.8148,107.1835,81.1994 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,499.5866,468.7809,521.3108,426.7362 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,201.6258,156.0563,211.4848,162.0191 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,859.877,645.0019,902.7792,676.4342 "CloverLeaf - Lagrangian-Eulerian Hydrodynamics (sec)",LIB,12.00,9.27,21.65,15.15 "CP2K Molecular Dynamics - Input: H2O-DFT-LS (sec)",LIB,5012.26,4957.686,2143.513,2363.579 "SPECFEM3D - Model: Mount St. Helens (sec)",LIB,6.216379849,5.030031580,3.906675095,2.630122599 "SPECFEM3D - Model: Layered Halfspace (sec)",LIB,15.964931688,15.028121929,9.997447570,7.470772930 "SPECFEM3D - Model: Tomographic Model (sec)",LIB,7.480674706,4.937265506,3.782741798,2.709205428 "SPECFEM3D - Model: Homogeneous Halfspace (sec)",LIB,9.404348500,6.092750299,4.727830148,3.451830169 "SPECFEM3D - Model: Water-layered Halfspace (sec)",LIB,17.194492779,13.419454501,9.778381437,6.218069257 "Timed Gem5 Compilation - Time To Compile (sec)",LIB,161.648,148.484,152.586,148.376 "Timed Godot Game Engine Compilation - Time To Compile (sec)",LIB,105.797,102.588,100.790,100.240 "Timed Linux Kernel Compilation - Build: defconfig (sec)",LIB,26.225,22.984,20.344,18.474 "Timed Linux Kernel Compilation - Build: allmodconfig (sec)",LIB,227.517,177.758,145.929,118.099 "Timed LLVM Compilation - Build System: Ninja (sec)",LIB,125.364,119.576,107.721,99.215 "Timed LLVM Compilation - Build System: Unix Makefiles (sec)",LIB,211.079,213.907,199.365,198.750 "Timed Node.js Compilation - Time To Compile (sec)",LIB,113.704,116.122,93.271,93.952 "Primesieve - Length: 1e12 (sec)",LIB,1.944,1.796,1.508,1.160 "Primesieve - Length: 1e13 (sec)",LIB,21.286,21.132,11.120,11.152 "Helsing - Digit Range: 14 digit (sec)",LIB,50.473,57.956,27.280,50.054 "Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,12.77,15.15,7.12,8.45 "Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,31.12,38.44,16.28,20.24 "Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,16.49,20.47,9.87,11.72 "Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,116.54,147.22,69.03,85.54 "Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,39.27,50.01,21.75,27.47 "Appleseed - Scene: Emily (sec)",LIB,122.587709,123.298396,164.567164,159.906614 "Appleseed - Scene: Disney Material (sec)",LIB,44.30492,38.492263,,40.570691 "Appleseed - Scene: Material Tester (sec)",LIB,166.676131,167.900597,,265.885808 "NAS Parallel Benchmarks - CPU Power Consumption Monitor (Watts)",LIB,220.03,216.16,397.37,380.97 "NAS Parallel Benchmarks - CPU Power Consumption Monitor (Watts)",LIB,149.82,143.06,274.22,259.96 "NAS Parallel Benchmarks - CPU Power Consumption Monitor (Watts)",LIB,238.61,229.32,399.82,375.87 "NAS Parallel Benchmarks - CPU Power Consumption Monitor (Watts)",LIB,134.84,133.34,256.9,249.94 "NAS Parallel Benchmarks - CPU Power Consumption Monitor (Watts)",LIB,148.47,150.15,315.26,307.61 "NAS Parallel Benchmarks - CPU Power Consumption Monitor (Watts)",LIB,193.05,192.37,324.76,310.37 "NAS Parallel Benchmarks - CPU Power Consumption Monitor (Watts)",LIB,88.42,91.16,173.73,172.91 "miniFE - CPU Power Consumption Monitor (Watts)",LIB,123.43,120.31,233.98,227.79 "NAS Parallel Benchmarks - CPU Power Consumption Monitor (Watts)",LIB,127.5,119.85,228.71,227.42 "NAS Parallel Benchmarks - CPU Power Consumption Monitor (Watts)",LIB,210.74,202.94,394.92,383.27 "miniBUDE - CPU Power Consumption Monitor (Watts)",LIB,155.92,154.01,269.38,223.4 "miniBUDE - CPU Power Consumption Monitor (Watts)",LIB,270.52,268.1,385.07,463.17 "CloverLeaf - CPU Power Consumption Monitor (Watts)",LIB,156.83,142.48,322.81,293.85 "CP2K Molecular Dynamics - CPU Power Consumption Monitor (Watts)",LIB,291.52,290.26,614.44,623.68 "NAMD - CPU Power Consumption Monitor (Watts)",LIB,258.84,242.43,386.17,421.91 "toyBrot Fractal Generator - CPU Power Consumption Monitor (Watts)",LIB,150.09,161.83,232.68,257.24 "toyBrot Fractal Generator - CPU Power Consumption Monitor (Watts)",LIB,148.84,154.08,242.46,251.07 "libxsmm - CPU Power Consumption Monitor (Watts)",LIB,205.01,204.17,322.92,324.27 "libxsmm - CPU Power Consumption Monitor (Watts)",LIB,211.17,210.44,321.06,319.88 "HeFFTe - Highly Efficient FFT for Exascale - CPU Power Consumption Monitor (Watts)",LIB,187.92,185.74,404.61,392.95 "HeFFTe - Highly Efficient FFT for Exascale - CPU Power Consumption Monitor (Watts)",LIB,169.96,164.96,336.38,340.8 "HeFFTe - Highly Efficient FFT for Exascale - CPU Power Consumption Monitor (Watts)",LIB,248.88,246.69,458.33,446.09 "HeFFTe - Highly Efficient FFT for Exascale - CPU Power Consumption Monitor (Watts)",LIB,233.52,229.75,408.39,404.72 "SPECFEM3D - CPU Power Consumption Monitor (Watts)",LIB,185.39,173.78,310.22,283.61 "SPECFEM3D - CPU Power Consumption Monitor (Watts)",LIB,234.87,226.26,396.49,355.84 "SPECFEM3D - CPU Power Consumption Monitor (Watts)",LIB,203.93,175.44,321.36,299.85 "SPECFEM3D - CPU Power Consumption Monitor (Watts)",LIB,218.63,188.68,338.57,314 "SPECFEM3D - CPU Power Consumption Monitor (Watts)",LIB,249.37,228.45,415.4,358.64 "Xmrig - CPU Power Consumption Monitor (Watts)",LIB,221.93,268.02,488.1,462.3 "Xmrig - CPU Power Consumption Monitor (Watts)",LIB,267.22,267.92,439.66,447.09 "srsRAN Project - CPU Power Consumption Monitor (Watts)",LIB,261.42,260.57,560.78,517.72 "John The Ripper - CPU Power Consumption Monitor (Watts)",LIB,280.29,254.23,564.26,541.52 "John The Ripper - CPU Power Consumption Monitor (Watts)",LIB,348.64,301.84,681.87,635.7 "John The Ripper - CPU Power Consumption Monitor (Watts)",LIB,291.74,296.91,517.18,526.99 "LuxCoreRender - CPU Power Consumption Monitor (Watts)",LIB,303.49,285.26,510.83,468.61 "LuxCoreRender - CPU Power Consumption Monitor (Watts)",LIB,298.35,293.46,558.11,501.47 "LuxCoreRender - CPU Power Consumption Monitor (Watts)",LIB,286.22,247.27,445.45,402.3 "LuxCoreRender - CPU Power Consumption Monitor (Watts)",LIB,142.31,136.45,281.59,279.04 "Embree - CPU Power Consumption Monitor (Watts)",LIB,191.71,204.9,314.33,347.93 "Embree - CPU Power Consumption Monitor (Watts)",LIB,170.51,183.96,286.01,312.56 "Intel Open Image Denoise - CPU Power Consumption Monitor (Watts)",LIB,176.53,172.35,298.49,294.18 "Intel Open Image Denoise - CPU Power Consumption Monitor (Watts)",LIB,170.54,174.13,294.58,295.21 "Intel Open Image Denoise - CPU Power Consumption Monitor (Watts)",LIB,219.82,215.85,383.91,379.66 "OpenVKL - CPU Power Consumption Monitor (Watts)",LIB,238.51,223.41,467.94,435.67 "OSPRay - CPU Power Consumption Monitor (Watts)",LIB,291.76,261.53,553.35,534.35 "OSPRay - CPU Power Consumption Monitor (Watts)",LIB,241.99,211.09,483.3,462.03 "OSPRay - CPU Power Consumption Monitor (Watts)",LIB,276.76,254.24,566.91,542.85 "OSPRay - CPU Power Consumption Monitor (Watts)",LIB,278.61,255.54,572.66,544.27 "7-Zip Compression - CPU Power Consumption Monitor (Watts)",LIB,266.27,247.35,501.4,472.21 "Stockfish - CPU Power Consumption Monitor (Watts)",LIB,326.55,309.55,649.7,598.99 "Timed Gem5 Compilation - CPU Power Consumption Monitor (Watts)",LIB,126.31,131.21,253.79,250.05 "Timed Godot Game Engine Compilation - CPU Power Consumption Monitor (Watts)",LIB,148.45,154.5,275.11,275.62 "Timed Linux Kernel Compilation - CPU Power Consumption Monitor (Watts)",LIB,158.04,149.41,285.97,267.88 "Timed Linux Kernel Compilation - CPU Power Consumption Monitor (Watts)",LIB,255.95,265.69,468.11,462.79 "Timed LLVM Compilation - CPU Power Consumption Monitor (Watts)",LIB,209.56,218.43,337.35,351.2 "Timed LLVM Compilation - CPU Power Consumption Monitor (Watts)",LIB,159.32,159.92,282.76,283.34 "Timed Node.js Compilation - CPU Power Consumption Monitor (Watts)",LIB,192.96,195.41,330.87,335.02 "Primesieve - CPU Power Consumption Monitor (Watts)",LIB,113.25,104.83,202.59,164.82 "Primesieve - CPU Power Consumption Monitor (Watts)",LIB,268.37,261.85,485.63,464.71 "OSPRay Studio - CPU Power Consumption Monitor (Watts)",LIB,286.61,277.45,609,558.64 "OSPRay Studio - CPU Power Consumption Monitor (Watts)",LIB,287.03,278.21,586.29,559.72 "OSPRay Studio - CPU Power Consumption Monitor (Watts)",LIB,287.82,281.21,585.98,564.46 "OSPRay Studio - CPU Power Consumption Monitor (Watts)",LIB,305.02,295.01,617.3,587.43 "OSPRay Studio - CPU Power Consumption Monitor (Watts)",LIB,303.95,283.12,572.24,551.43 "OSPRay Studio - CPU Power Consumption Monitor (Watts)",LIB,305.15,295.55,615.69,589.05 "OSPRay Studio - CPU Power Consumption Monitor (Watts)",LIB,307.82,284.22,575.16,573.14 "OSPRay Studio - CPU Power Consumption Monitor (Watts)",LIB,282.67,274.66,616.86,566.27 "OSPRay Studio - CPU Power Consumption Monitor (Watts)",LIB,291.25,290.35,625.58,568.08 "Helsing - CPU Power Consumption Monitor (Watts)",LIB,316.26,310.21,589.87,512.26 "OpenSSL - CPU Power Consumption Monitor (Watts)",LIB,333.08,285.19,676,603.9 "OpenSSL - CPU Power Consumption Monitor (Watts)",LIB,335.75,332.69,676.25,678.87 "OpenSSL - CPU Power Consumption Monitor (Watts)",LIB,314.07,284.75,617.73,599.56 "OpenSSL - CPU Power Consumption Monitor (Watts)",LIB,363.8,308.01,730.27,660.38 "OpenSSL - CPU Power Consumption Monitor (Watts)",LIB,343.2,341.74,693.22,687.22 "OpenSSL - CPU Power Consumption Monitor (Watts)",LIB,341.99,336.86,691.78,675.04 "OpenSSL - CPU Power Consumption Monitor (Watts)",LIB,360.04,322.28,724.1,661.5 "Liquid-DSP - CPU Power Consumption Monitor (Watts)",LIB,271.1,260.28,526.88,524.17 "Liquid-DSP - CPU Power Consumption Monitor (Watts)",LIB,267.43,259.79,542.11,515.71 "ASTC Encoder - CPU Power Consumption Monitor (Watts)",LIB,123.13,117.33,247.05,234.69 "ASTC Encoder - CPU Power Consumption Monitor (Watts)",LIB,133.8,134.61,227.98,220.5 "ASTC Encoder - CPU Power Consumption Monitor (Watts)",LIB,172.1,174.24,283.59,278.8 "Graph500 - CPU Power Consumption Monitor (Watts)",LIB,293.26,286.97,634.69,646.2 "MariaDB - CPU Power Consumption Monitor (Watts)",LIB,122.43,123.06,245.22,254.51 "MariaDB - CPU Power Consumption Monitor (Watts)",LIB,122.04,123.19,250.44,257.46 "PostgreSQL - CPU Power Consumption Monitor (Watts)",LIB,141,137.98,294.82,297.52 "TensorFlow - CPU Power Consumption Monitor (Watts)",LIB,201.49,191.63,334.38,376.07 "TensorFlow - CPU Power Consumption Monitor (Watts)",LIB,235.29,213.28,386.28,420.4 "TensorFlow - CPU Power Consumption Monitor (Watts)",LIB,243.24,237.07,383.45,412.23 "TensorFlow - CPU Power Consumption Monitor (Watts)",LIB,220.96,222.59,391.59,406.75 "TensorFlow - CPU Power Consumption Monitor (Watts)",LIB,235.45,228.42,439.04,456.01 "TensorFlow - CPU Power Consumption Monitor (Watts)",LIB,225.8,222.86,421.61,441.9 "Neural Magic DeepSparse - CPU Power Consumption Monitor (Watts)",LIB,247.92,233.36,482.63,478.36 "Neural Magic DeepSparse - CPU Power Consumption Monitor (Watts)",LIB,250.7,251.27,517.56,505.33 "Neural Magic DeepSparse - CPU Power Consumption Monitor (Watts)",LIB,231.96,236.78,496.12,504.41 "Neural Magic DeepSparse - CPU Power Consumption Monitor (Watts)",LIB,291.22,281.81,568.51,576 "Neural Magic DeepSparse - CPU Power Consumption Monitor (Watts)",LIB,279.75,278.52,556.63,553.79 "Neural Magic DeepSparse - CPU Power Consumption Monitor (Watts)",LIB,256.18,257.43,535.06,534.41 "Neural Magic DeepSparse - CPU Power Consumption Monitor (Watts)",LIB,235.18,228.97,453.79,460.64 "Neural Magic DeepSparse - CPU Power Consumption Monitor (Watts)",LIB,247.32,235.42,459.55,482.32 "Neural Magic DeepSparse - CPU Power Consumption Monitor (Watts)",LIB,250.83,235.91,486.69,479.5 "Blender - CPU Power Consumption Monitor (Watts)",LIB,242.87,245.21,405.53,459.78 "Blender - CPU Power Consumption Monitor (Watts)",LIB,294.4,290.08,525.55,557.64 "Blender - CPU Power Consumption Monitor (Watts)",LIB,259.04,257.96,439.22,484.54 "Blender - CPU Power Consumption Monitor (Watts)",LIB,319.26,315.38,604.43,605.16 "Blender - CPU Power Consumption Monitor (Watts)",LIB,303.74,297.19,552.47,571.12 "OpenVINO - CPU Power Consumption Monitor (Watts)",LIB,315.89,316.32,611.1,621.51 "OpenVINO - CPU Power Consumption Monitor (Watts)",LIB,304.04,306.74,524.02,537.68 "OpenVINO - CPU Power Consumption Monitor (Watts)",LIB,304.46,307.41,527.63,529.98 "OpenVINO - CPU Power Consumption Monitor (Watts)",LIB,252.92,276.2,597.65,615.75 "OpenVINO - CPU Power Consumption Monitor (Watts)",LIB,295.03,294.88,578.64,585.67 "OpenVINO - CPU Power Consumption Monitor (Watts)",LIB,297.12,299.11,602.26,613.08 "OpenVINO - CPU Power Consumption Monitor (Watts)",LIB,327.23,318.56,643.58,655.04 "OpenVINO - CPU Power Consumption Monitor (Watts)",LIB,293.93,303.27,611.86,618.57 "OpenVINO - CPU Power Consumption Monitor (Watts)",LIB,307.35,301.27,603.75,614.16 "OpenVINO - CPU Power Consumption Monitor (Watts)",LIB,301.97,267.68,563.32,575.68 "OpenVINO - CPU Power Consumption Monitor (Watts)",LIB,320.15,294.6,504.47,511.7 "OpenVINO - CPU Power Consumption Monitor (Watts)",LIB,310.01,278.47,599.24,577.61 "Appleseed - CPU Power Consumption Monitor (Watts)",LIB,177.28,173.02,290.19,289.71 "Aircrack-ng - CPU Power Consumption Monitor (Watts)",LIB,234.62,229.46,,362.8 "Appleseed - CPU Power Consumption Monitor (Watts)",LIB,219.92,222.18,,357.2 "Appleseed - CPU Power Consumption Monitor (Watts)",LIB,150.04,148.63,,258.14 "nekRS - CPU Power Consumption Monitor (Watts)",LIB,293.57,298.09,, "nekRS - CPU Power Consumption Monitor (Watts)",LIB,288.26,287.58,,