new-tests

Tests for a future article. AMD EPYC 8324P 32-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 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 2401110-NE-NEWTESTS900
Jump To Table - Results

View

Do Not Show Noisy Results
Do Not Show Results With Incomplete Data
Do Not Show Results With Little Change/Spread
List Notable Results

Limit displaying results to tests within:

C++ Boost Tests 3 Tests
Timed Code Compilation 3 Tests
C/C++ Compiler Tests 3 Tests
CPU Massive 7 Tests
Creator Workloads 6 Tests
Encoding 2 Tests
HPC - High Performance Computing 6 Tests
Machine Learning 5 Tests
Multi-Core 10 Tests
Intel oneAPI 3 Tests
Programmer / Developer System Benchmarks 3 Tests
Python Tests 6 Tests
Renderers 2 Tests
Server 2 Tests
Server CPU Tests 5 Tests
Video Encoding 2 Tests

Statistics

Show Overall Harmonic Mean(s)
Show Overall Geometric Mean
Show Geometric Means Per-Suite/Category
Show Wins / Losses Counts (Pie Chart)
Normalize Results
Remove Outliers Before Calculating Averages

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Disable Color Branding
Prefer Vertical Bar Graphs
No Box Plots
On Line Graphs With Missing Data, Connect The Line Gaps

Additional Graphs

Show Perf Per Core/Thread Calculation Graphs Where Applicable
Show Perf Per Clock Calculation Graphs Where Applicable

Multi-Way Comparison

Condense Multi-Option Tests Into Single Result Graphs
Condense Test Profiles With Multiple Version Results Into Single Result Graphs

Table

Show Detailed System Result Table

Run Management

Highlight
Result
Hide
Result
Result
Identifier
View Logs
Performance Per
Dollar
Date
Run
  Test
  Duration
Zen 1 - EPYC 7601
January 07
  46 Minutes
b
January 10
  12 Minutes
c
January 10
  12 Minutes
32
January 11
  2 Hours, 56 Minutes
32 z
January 11
  2 Hours, 56 Minutes
32 c
January 11
  3 Hours, 14 Minutes
32 d
January 11
  2 Hours, 55 Minutes
Invert Hiding All Results Option
  1 Hour, 53 Minutes

Only show results where is faster than
Only show results matching title/arguments (delimit multiple options with a comma):
Do not show results matching title/arguments (delimit multiple options with a comma):

new-tests Tests for a future article. AMD EPYC 8324P 32-Core testing with a AMD Cinnabar (RCB1009C BIOS) and ASPEED on Ubuntu 23.10 via the Phoronix Test Suite. ,,"Zen 1 - EPYC 7601","b","c","32","32 z","32 c","32 d" Processor,,AMD EPYC 7601 32-Core @ 2.20GHz (32 Cores / 64 Threads),AMD EPYC 8534PN 64-Core @ 2.00GHz (64 Cores / 128 Threads),AMD EPYC 8534PN 64-Core @ 2.00GHz (64 Cores / 128 Threads),AMD EPYC 8534PN 32-Core @ 2.05GHz (32 Cores / 64 Threads),AMD EPYC 8534PN 32-Core @ 2.05GHz (32 Cores / 64 Threads),AMD EPYC 8324P 32-Core @ 2.65GHz (32 Cores / 64 Threads),AMD EPYC 8324P 32-Core @ 2.65GHz (32 Cores / 64 Threads) Motherboard,,TYAN B8026T70AE24HR (V1.02.B10 BIOS),AMD Cinnabar (RCB1009C BIOS),AMD Cinnabar (RCB1009C BIOS),AMD Cinnabar (RCB1009C BIOS),AMD Cinnabar (RCB1009C BIOS),AMD Cinnabar (RCB1009C BIOS),AMD Cinnabar (RCB1009C BIOS) Chipset,,AMD 17h,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4 Memory,,128GB,6 x 32 GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG,6 x 32 GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG,6 x 32 GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG,6 x 32 GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG,6 x 32 GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG,6 x 32 GB DRAM-4800MT/s Samsung M321R4GA0BB0-CQKMG Disk,,280GB INTEL SSDPE21D280GA + 1000GB INTEL SSDPE2KX010T8,1000GB INTEL SSDPE2KX010T8,1000GB INTEL SSDPE2KX010T8,1000GB INTEL SSDPE2KX010T8,1000GB INTEL SSDPE2KX010T8,1000GB INTEL SSDPE2KX010T8,1000GB INTEL SSDPE2KX010T8 Graphics,,llvmpipe,llvmpipe,llvmpipe,ASPEED,ASPEED,ASPEED,ASPEED Monitor,,VE228,,,,,, Network,,2 x Broadcom NetXtreme BCM5720 PCIe,2 x Broadcom NetXtreme BCM5720 PCIe,2 x Broadcom NetXtreme BCM5720 PCIe,2 x Broadcom NetXtreme BCM5720 PCIe,2 x Broadcom NetXtreme BCM5720 PCIe,2 x Broadcom NetXtreme BCM5720 PCIe,2 x Broadcom NetXtreme BCM5720 PCIe OS,,Ubuntu 23.10,Ubuntu 23.10,Ubuntu 23.10,Ubuntu 23.10,Ubuntu 23.10,Ubuntu 23.10,Ubuntu 23.10 Kernel,,6.6.9-060609-generic (x86_64),6.6.9-060609-generic (x86_64),6.6.9-060609-generic (x86_64),6.6.9-060609-generic (x86_64),6.6.9-060609-generic (x86_64),6.6.9-060609-generic (x86_64),6.6.9-060609-generic (x86_64) Desktop,,GNOME Shell 45.0,GNOME Shell 45.0,GNOME Shell 45.0,GNOME Shell 45.0,GNOME Shell 45.0,GNOME Shell 45.0,GNOME Shell 45.0 Display Server,,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7,X Server 1.21.1.7 OpenGL,,4.5 Mesa 23.2.1-1ubuntu3.1 (LLVM 15.0.7 256 bits),,,,,, Compiler,,GCC 13.2.0,GCC 13.2.0,GCC 13.2.0,GCC 13.2.0,GCC 13.2.0,GCC 13.2.0,GCC 13.2.0 File-System,,ext4,ext4,ext4,ext4,ext4,ext4,ext4 Screen Resolution,,1920x1080,1920x1200,1920x1200,1920x1200,1920x1200,1920x1200,1920x1200 ,,"Zen 1 - EPYC 7601","b","c","32","32 z","32 c","32 d" "Y-Cruncher - Pi Digits To Calculate: 1B (sec)",LIB,33.923,10.416,10.476,11.676,11.595,11.902,11.975 "Y-Cruncher - Pi Digits To Calculate: 500M (sec)",LIB,15.693,5.202,5.213,5.656,5.685,5.783,5.751 "Quicksilver - Input: CORAL2 P1 (Figure Of Merit)",HIB,12996667,21180000,21250000,18790000,18760000,1040000,18840000 "Quicksilver - Input: CTS2 (Figure Of Merit)",HIB,11426667,16270000,16260000,14320000,14290000,14430000,14280000 "SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,,,,48.451,58.715,47.253,58.642 "RocksDB - Test: Random Read (Op/s)",HIB,,,,176770468,177167636,160665305,160707812 "DaCapo Benchmark - Java Test: PMD Source Code Analyzer (msec)",LIB,,,,1784,1820,1966,1833 "Speedb - Test: Random Read (Op/s)",HIB,,,,179685954,179434924,163202721,163512432 "DaCapo Benchmark - Java Test: FOP Print Formatter (msec)",LIB,,,,751,696,764,758 "Speedb - Test: Read While Writing (Op/s)",HIB,,,,7457600,7210235,7746346,7105602 "QuantLib - Configuration: Multi-Threaded (MFLOPS)",HIB,,,,107079.2,107381.6,98916.2,98618.7 "OpenFOAM - Input: drivaerFastback, Small Mesh Size - Mesh Time (sec)",LIB,,,,28.372583,30.75472,30.537591,30.724194 "OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (ms)",LIB,,,,42.87,43.71,46.17,46.28 "OpenVINO - Model: Handwritten English Recognition FP16-INT8 - Device: CPU (FPS)",HIB,,,,745,730.82,692.02,690.24 "Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,,,,55.65,55.54,59.58,59.79 "Quicksilver - Input: CORAL2 P2 (Figure Of Merit)",HIB,15013333,16140000,16150000,15350000,15230000,15180000,15100000 "Timed Gem5 Compilation - Time To Compile (sec)",LIB,,,,254.01,272.61,258.307,258.934 "Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,,,,139.09,138.6,148.74,148.56 "DaCapo Benchmark - Java Test: Zxing 1D/2D Barcode Image Processing (msec)",LIB,,,,609,599,569,599 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,,,,9.56,9.56,10.22,10.21 "Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,,,,112.03,112.09,119.72,119.57 "OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (ms)",LIB,,,,5.41,5.42,5.78,5.78 "Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,,,,44.73,44.48,47.52,47.41 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,,,,3300.99,3299.93,3099.2,3100.95 "OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (FPS)",HIB,,,,5747.65,5751.58,5416.31,5423.13 "DaCapo Benchmark - Java Test: H2O In-Memory Platform For Machine Learning (msec)",LIB,,,,3974,3868,3979,3755 "OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (ms)",LIB,,,,35.51,35.59,37.4,37.61 "OpenVINO - Model: Handwritten English Recognition FP16 - Device: CPU (FPS)",HIB,,,,898.6,896.69,853.38,848.62 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (ms)",LIB,,,,8.07,8.05,8.52,8.52 "OpenVINO - Model: Vehicle Detection FP16-INT8 - Device: CPU (FPS)",HIB,,,,1960.18,1964.99,1860.99,1862.24 "OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (ms)",LIB,,,,23.95,23.95,25.22,25.16 "DaCapo Benchmark - Java Test: H2 Database Engine (msec)",LIB,,,,2675,2655,2773,2634 "OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (FPS)",HIB,,,,666.22,666.3,632.92,634.5 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,,,,32.82,32.81,31.22,31.2 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,,,,486.65,486.03,510.79,510.9 "DaCapo Benchmark - Java Test: Tradesoap (msec)",LIB,,,,5403,5168,5366,5149 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (ms)",LIB,,,,18.69,18.69,19.58,19.56 "OpenVINO - Model: Weld Porosity Detection FP16 - Device: CPU (FPS)",HIB,,,,1704.26,1704.02,1627.93,1628.91 "OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (ms)",LIB,,,,27.69,27.53,28.77,28.82 "OpenVINO - Model: Road Segmentation ADAS FP16 - Device: CPU (FPS)",HIB,,,,576.18,579.41,554.68,553.65 "Timed Linux Kernel Compilation - Build: allmodconfig (sec)",LIB,,,,433.789,434.187,453.693,452.606 "TensorFlow - Device: CPU - Batch Size: 1 - Model: GoogLeNet (images/sec)",HIB,,,,28.99,28.71,27.73,28.79 "OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,60673,61430,62802,63336 "RocksDB - Test: Read While Writing (Op/s)",HIB,,,,4284691,4364996,4419497,4244478 "OpenVINO - Model: Face Detection FP16 - Device: CPU (ms)",LIB,,,,929.23,927.57,964.2,965.35 "OpenVINO - Model: Face Detection FP16 - Device: CPU (FPS)",HIB,,,,17.17,17.18,16.51,16.54 "PyTorch - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l (batches/sec)",HIB,,,,9.85,9.82,10.04,10.21 "DaCapo Benchmark - Java Test: Apache Lucene Search Engine (msec)",LIB,,,,1402,1425,1379,1433 "Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,,,,410.61,410.43,426.3,426.37 "TensorFlow - Device: CPU - Batch Size: 1 - Model: AlexNet (images/sec)",HIB,,,,32.12,31.92,33.14,33.02 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,396.2914,397.9593,411.3435,410.3267 "Timed FFmpeg Compilation - Time To Compile (sec)",LIB,,,,23.557,23.759,24.446,24.3 "Embree - Binary: Pathtracer - Model: Crown (FPS)",HIB,,,,36.9584,37.2545,35.9147,36.2812 "DaCapo Benchmark - Java Test: Spring Boot (msec)",LIB,,,,2444,2460,2533,2452 "Neural Magic DeepSparse - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,40.1688,39.9467,38.7708,38.8343 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,,,,199.9,201.15,194.21,195.05 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,,,,79.82,79.39,82.18,81.87 "DaCapo Benchmark - Java Test: GraphChi (msec)",LIB,,,,3536,3630,3538,3656 "OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (ms)",LIB,,,,3.91,3.9,4.03,4.03 "DaCapo Benchmark - Java Test: Avrora AVR Simulation Framework (msec)",LIB,,,,5613,5441,5561,5572 "SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,,,,186.625,185.562,180.955,186.368 "Timed Linux Kernel Compilation - Build: defconfig (sec)",LIB,,,,52.133,52.012,53.615,53.632 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,,,,0.65,0.66,0.67,0.67 "SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,,,,5.801,5.899,5.829,5.977 "TensorFlow - Device: CPU - Batch Size: 16 - Model: VGG-16 (images/sec)",HIB,,,,25.15,25.2,24.47,24.51 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (ms)",LIB,,,,9.12,9.16,9.39,9.37 "OpenVINO - Model: Person Vehicle Bike Detection FP16 - Device: CPU (FPS)",HIB,,,,1741.57,1735.64,1694.01,1696.5 "OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,3404,3406,3493,3499 "OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,116566,116972,118980,119783 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,71361,71495,73024,73329 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,,,,13.36,13.29,13.65,13.65 "OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,116377,115669,118221,118802 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,4049,4048,4157,4132 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,,,,1190.42,1197.46,1166.56,1166.83 "DaCapo Benchmark - Java Test: Tradebeans (msec)",LIB,,,,8561,8600,8520,8380 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,836.4214,835.262,816.2785,815.9768 "Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,19.1107,19.1338,19.5831,19.5858 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,136464,136312,139685,139445 "Xmrig - Variant: GhostRider - Hash Count: 1M (H/s)",HIB,,,,4067.4,4038.6,4136.3,4095.7 "DaCapo Benchmark - Java Test: Jython (msec)",LIB,,,,6703,6773,6865,6769 "OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,61987,62113,63402,62787 "OpenFOAM - Input: drivaerFastback, Small Mesh Size - Execution Time (sec)",LIB,,,,72.807288,71.201285,72.384007,72.305836 "DaCapo Benchmark - Java Test: Apache Xalan XSLT (msec)",LIB,,,,871,859,852,861 "OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,3451,3446,3515,3522 "Xmrig - Variant: Wownero - Hash Count: 1M (H/s)",HIB,,,,25814.4,25943.7,25385.9,25396.8 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,,,,0.48,0.47,0.48,0.48 "TensorFlow - Device: CPU - Batch Size: 1 - Model: ResNet-50 (images/sec)",HIB,,,,8.74,8.77,8.61,8.59 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,21.2933,21.2711,20.8729,21.0932 "Embree - Binary: Pathtracer ISPC - Model: Crown (FPS)",HIB,,,,37.2967,37.6791,36.9967,36.9369 "RocksDB - Test: Read Random Write Random (Op/s)",HIB,,,,2373654,2361270,2327800,2351568 "Speedb - Test: Read Random Write Random (Op/s)",HIB,,,,2231403,2259344,2229494,2215896 "PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-152 (batches/sec)",HIB,,,,15.61,15.51,15.32,15.35 "Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS)",HIB,,,,45.9374,46.3088,45.4648,45.6482 "TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,,,,158.47,155.77,157.6,158.08 "PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-50 (batches/sec)",HIB,,,,52.44,52.78,53.00,53.30 "Embree - Binary: Pathtracer - Model: Asian Dragon Obj (FPS)",HIB,,,,37.284,36.8586,37.4405,37.4056 "DaCapo Benchmark - Java Test: Apache Tomcat (msec)",LIB,,,,2107,2082,2094,2112 "OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (FPS)",HIB,,,,3921.5,3924.86,3877.91,3869.7 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,,,,40123.62,40101.8,39562.87,39843.05 "DaCapo Benchmark - Java Test: Eclipse (msec)",LIB,,,,12656,12735,12826,12768 "Speedb - Test: Update Random (Op/s)",HIB,,,,314123,314114,317758,313683 "TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,,,,272.93,274.97,274.97,276.19 "Llama.cpp - Model: llama-2-13b.Q4_0.gguf (Tokens/sec)",HIB,,,,17.94,17.87,17.87,18.08 "Xmrig - Variant: CryptoNight-Heavy - Hash Count: 1M (H/s)",HIB,,,,19004.5,18936.5,18783.9,18924 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,21.2278,21.289,21.0419,21.0667 "DaCapo Benchmark - Java Test: Batik SVG Toolkit (msec)",LIB,,,,1733,1723,1718,1738 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,26.0566,26.0768,25.8175,25.7874 "Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,747.0674,745.1806,753.1229,751.2117 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,87.4908,87.325,88.1952,88.2278 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,383.9746,385.6481,384.3164,381.7839 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,123.0157,122.955,122.3307,121.8001 "PyTorch - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l (batches/sec)",HIB,,,,7.17,7.11,7.18,7.15 "Xmrig - Variant: KawPow - Hash Count: 1M (H/s)",HIB,,,,18777.2,18961.3,18947.3,18901.1 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,41.6314,41.4377,41.5889,41.8438 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,,,,185.665,184.981,183.899,184.099 "PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-152 (batches/sec)",HIB,,,,19.04,18.92,18.86,18.86 "OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,,,,151.45,150.06,150.07,151.25 "Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,182.5085,182.7643,181.1043,181.1155 "RocksDB - Test: Update Random (Op/s)",HIB,,,,630575,636242,633688,630478 "OpenVINO - Model: Person Detection FP16 - Device: CPU (ms)",LIB,,,,105.48,106.44,106.43,105.64 "PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-50 (batches/sec)",HIB,,,,40.19,39.96,40.32,40.31 "7-Zip Compression - Test: Compression Rating (MIPS)",HIB,,,,241545,242399,240287,241191 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,2208.1537,2199.4941,2195.9198,2189.0655 "Neural Magic DeepSparse - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,7.2332,7.261,7.2738,7.2896 "Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,747.314,746.128,751.9259,750.3997 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,123.8817,123.785,123.1469,122.9312 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,128.8158,128.845,129.5421,129.8101 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,129.8749,129.8035,130.4755,130.7937 "CacheBench - Test: Read / Modify / Write (MB/s)",HIB,,,,87227.587713,87218.210974,87238.013197,87854.117672 "DaCapo Benchmark - Java Test: Apache Lucene Search Index (msec)",LIB,,,,4613,4589,4580,4602 "Xmrig - Variant: Monero - Hash Count: 1M (H/s)",HIB,,,,18845.5,18763.8,18897.5,18866.1 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,266.8799,267.8417,266.034,266.2776 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,59.8833,59.6674,60.0613,60.0284 "Embree - Binary: Pathtracer - Model: Asian Dragon (FPS)",HIB,,,,41.5958,41.8198,41.5696,41.557 "DaCapo Benchmark - Java Test: BioJava Biological Data Framework (msec)",LIB,,,,7874,7858,7904,7907 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,607.935,608.1326,611.6026,611.4439 "Llama.cpp - Model: llama-2-7b.Q4_0.gguf (Tokens/sec)",HIB,,,,29.75,29.9,29.74,29.85 "Embree - Binary: Pathtracer ISPC - Model: Asian Dragon Obj (FPS)",HIB,,,,38.9378,39.107,39.0046,39.1421 "FFmpeg - Encoder: libx265 - Scenario: Video On Demand (FPS)",HIB,,,,45.18,45.08,44.95,45.10 "FFmpeg - Encoder: libx265 - Scenario: Live (FPS)",HIB,,,,109.84,110.37,110.02,110.29 "Xmrig - Variant: CryptoNight-Femto UPX2 - Hash Count: 1M (H/s)",HIB,,,,18860.1,18909,18887.5,18818.6 "DaCapo Benchmark - Java Test: Apache Cassandra (msec)",LIB,,,,5946,5938,5955,5927 "TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,,,,51.34,51.57,51.56,51.49 "TensorFlow - Device: CPU - Batch Size: 1 - Model: VGG-16 (images/sec)",HIB,,,,9.73,9.75,9.77,9.75 "OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,,,,150.8,150.37,150.84,150.25 "7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,,,,212209,211584,211815,211383 "OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,,,,105.97,106.24,105.91,106.32 "FFmpeg - Encoder: libx265 - Scenario: Upload (FPS)",HIB,,,,22.28,22.20,22.21,22.22 "FFmpeg - Encoder: libx265 - Scenario: Platform (FPS)",HIB,,,,45.13,45.05,45.13,44.97 "Llama.cpp - Model: llama-2-70b-chat.Q5_0.gguf (Tokens/sec)",HIB,,,,3.42,3.41,3.42,3.42 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,,,,52441.94,52475.39,52382.31,52344.6 "DaCapo Benchmark - Java Test: Apache Kafka (msec)",LIB,,,,5110,5121,5111,5114 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,59.8638,59.8673,59.9016,59.9698 "Neural Magic DeepSparse - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,266.8574,266.9761,266.8428,266.5343 "DaCapo Benchmark - Java Test: jMonkeyEngine (msec)",LIB,,,,6914,6917,6917,6916 "CacheBench - Test: Write (MB/s)",HIB,,,,45646.091353,45646.816107,45645.091133,45643.038713 "CacheBench - Test: Read (MB/s)",HIB,,,,7616.087334,7616.334142,7615.948086,7615.833145 "Meta Performance Per Watts - Performance Per Watts (Performance/Watts)",HIB,13064001.6555,,,,,, "CPU Power Consumption Monitor - Phoronix Test Suite System Monitoring (Watts)",,585.92,,,,,, "Y-Cruncher - CPU Power Consumption Monitor (Watts)",LIB,602.05,,,,,, "Y-Cruncher - CPU Power Consumption Monitor (Watts)",LIB,542.54,,,,,, "Quicksilver - CPU Power Consumption Monitor (Watts)",LIB,624.15,,,,,, "Quicksilver - Input: CTS2 (Figure Of Merit/Watt)",HIB,18307.655,,,,,, "Quicksilver - CPU Power Consumption Monitor (Watts)",LIB,553.65,,,,,, "Quicksilver - Input: CORAL2 P2 (Figure Of Merit/Watt)",HIB,27116.867,,,,,, "Quicksilver - CPU Power Consumption Monitor (Watts)",LIB,584.16,,,,,, "Quicksilver - Input: CORAL2 P1 (Figure Of Merit/Watt)",HIB,22248.554,,,,,,