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
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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
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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" "Quicksilver - Input: CTS2 (Figure Of Merit)",HIB,11426667,16270000,16260000,14320000,14290000,14430000,14280000 "Timed Linux Kernel Compilation - Build: allmodconfig (sec)",LIB,,,,433.789,434.187,453.693,452.606 "Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,,,,410.61,410.43,426.3,426.37 "Quicksilver - Input: CORAL2 P2 (Figure Of Merit)",HIB,15013333,16140000,16150000,15350000,15230000,15180000,15100000 "PyTorch - Device: CPU - Batch Size: 16 - Model: Efficientnet_v2_l (batches/sec)",HIB,,,,7.17,7.11,7.18,7.15 "Timed Gem5 Compilation - Time To Compile (sec)",LIB,,,,254.01,272.61,258.307,258.934 "Xmrig - Variant: GhostRider - Hash Count: 1M (H/s)",HIB,,,,4067.4,4038.6,4136.3,4095.7 "Quicksilver - Input: CORAL2 P1 (Figure Of Merit)",HIB,12996667,21180000,21250000,18790000,18760000,1040000,18840000 "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 "FFmpeg - Encoder: libx265 - Scenario: Video On Demand (FPS)",HIB,,,,45.18,45.08,44.95,45.10 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,136464,136312,139685,139445 "Llama.cpp - Model: llama-2-70b-chat.Q5_0.gguf (Tokens/sec)",HIB,,,,3.42,3.41,3.42,3.42 "Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,,,,139.09,138.6,148.74,148.56 "PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-152 (batches/sec)",HIB,,,,15.61,15.51,15.32,15.35 "OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,116566,116972,118980,119783 "OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,116377,115669,118221,118802 "CacheBench - Test: Read / Modify / Write (MB/s)",HIB,,,,87227.587713,87218.210974,87238.013197,87854.117672 "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 "Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,,,,112.03,112.09,119.72,119.57 "PyTorch - Device: CPU - Batch Size: 1 - Model: Efficientnet_v2_l (batches/sec)",HIB,,,,9.85,9.82,10.04,10.21 "OpenFOAM - Input: drivaerFastback, Small Mesh Size - Execution Time (sec)",LIB,,,,72.807288,71.201285,72.384007,72.305836 "OpenFOAM - Input: drivaerFastback, Small Mesh Size - Mesh Time (sec)",LIB,,,,28.372583,30.75472,30.537591,30.724194 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,71361,71495,73024,73329 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,607.935,608.1326,611.6026,611.4439 "Neural Magic DeepSparse - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,26.0566,26.0768,25.8175,25.7874 "OSPRay Studio - Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,4049,4048,4157,4132 "OSPRay Studio - Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,3451,3446,3515,3522 "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: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,61987,62113,63402,62787 "OSPRay Studio - Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU (ms)",LIB,,,,60673,61430,62802,63336 "TensorFlow - Device: CPU - Batch Size: 16 - Model: VGG-16 (images/sec)",HIB,,,,25.15,25.2,24.47,24.51 "FFmpeg - Encoder: libx265 - Scenario: Live (FPS)",HIB,,,,109.84,110.37,110.02,110.29 "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 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (ms)",LIB,,,,486.65,486.03,510.79,510.9 "OpenVINO - Model: Face Detection FP16-INT8 - Device: CPU (FPS)",HIB,,,,32.82,32.81,31.22,31.2 "QuantLib - Configuration: Multi-Threaded (MFLOPS)",HIB,,,,107079.2,107381.6,98916.2,98618.7 "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 (ms)",LIB,,,,105.48,106.44,106.43,105.64 "OpenVINO - Model: Person Detection FP16 - Device: CPU (FPS)",HIB,,,,151.45,150.06,150.07,151.25 "OpenVINO - Model: Person Detection FP32 - Device: CPU (ms)",LIB,,,,105.97,106.24,105.91,106.32 "OpenVINO - Model: Person Detection FP32 - Device: CPU (FPS)",HIB,,,,150.8,150.37,150.84,150.25 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (ms)",LIB,,,,79.82,79.39,82.18,81.87 "OpenVINO - Model: Machine Translation EN To DE FP16 - Device: CPU (FPS)",HIB,,,,199.9,201.15,194.21,195.05 "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 "OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (ms)",LIB,,,,23.95,23.95,25.22,25.16 "OpenVINO - Model: Road Segmentation ADAS FP16-INT8 - Device: CPU (FPS)",HIB,,,,666.22,666.3,632.92,634.5 "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 "OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (ms)",LIB,,,,5.41,5.42,5.78,5.78 "OpenVINO - Model: Face Detection Retail FP16-INT8 - Device: CPU (FPS)",HIB,,,,5747.65,5751.58,5416.31,5423.13 "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 "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: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (ms)",LIB,,,,0.48,0.47,0.48,0.48 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU (FPS)",HIB,,,,52441.94,52475.39,52382.31,52344.6 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (ms)",LIB,,,,0.65,0.66,0.67,0.67 "OpenVINO - Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU (FPS)",HIB,,,,40123.62,40101.8,39562.87,39843.05 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (ms)",LIB,,,,13.36,13.29,13.65,13.65 "OpenVINO - Model: Vehicle Detection FP16 - Device: CPU (FPS)",HIB,,,,1190.42,1197.46,1166.56,1166.83 "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 "Speedb - Test: Update Random (Op/s)",HIB,,,,314123,314114,317758,313683 "OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (ms)",LIB,,,,3.91,3.9,4.03,4.03 "OpenVINO - Model: Face Detection Retail FP16 - Device: CPU (FPS)",HIB,,,,3921.5,3924.86,3877.91,3869.7 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (ms)",LIB,,,,9.56,9.56,10.22,10.21 "OpenVINO - Model: Weld Porosity Detection FP16-INT8 - Device: CPU (FPS)",HIB,,,,3300.99,3299.93,3099.2,3100.95 "Speedb - Test: Read While Writing (Op/s)",HIB,,,,7457600,7210235,7746346,7105602 "RocksDB - Test: Update Random (Op/s)",HIB,,,,630575,636242,633688,630478 "Speedb - Test: Read Random Write Random (Op/s)",HIB,,,,2231403,2259344,2229494,2215896 "Speedb - Test: Random Read (Op/s)",HIB,,,,179685954,179434924,163202721,163512432 "RocksDB - Test: Read Random Write Random (Op/s)",HIB,,,,2373654,2361270,2327800,2351568 "RocksDB - Test: Read While Writing (Op/s)",HIB,,,,4284691,4364996,4419497,4244478 "RocksDB - Test: Random Read (Op/s)",HIB,,,,176770468,177167636,160665305,160707812 "DaCapo Benchmark - Java Test: Apache Cassandra (msec)",LIB,,,,5946,5938,5955,5927 "Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,,,,55.65,55.54,59.58,59.79 "Xmrig - Variant: Monero - Hash Count: 1M (H/s)",HIB,,,,18845.5,18763.8,18897.5,18866.1 "Xmrig - Variant: CryptoNight-Femto UPX2 - Hash Count: 1M (H/s)",HIB,,,,18860.1,18909,18887.5,18818.6 "Xmrig - Variant: KawPow - Hash Count: 1M (H/s)",HIB,,,,18777.2,18961.3,18947.3,18901.1 "Xmrig - Variant: CryptoNight-Heavy - Hash Count: 1M (H/s)",HIB,,,,19004.5,18936.5,18783.9,18924 "Timed Linux Kernel Compilation - Build: defconfig (sec)",LIB,,,,52.133,52.012,53.615,53.632 "PyTorch - Device: CPU - Batch Size: 16 - Model: ResNet-50 (batches/sec)",HIB,,,,40.19,39.96,40.32,40.31 "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 "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 "DaCapo Benchmark - Java Test: Eclipse (msec)",LIB,,,,12656,12735,12826,12768 "Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,,,,44.73,44.48,47.52,47.41 "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 Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,21.2933,21.2711,20.8729,21.0932 "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 "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: 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: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,21.2278,21.289,21.0419,21.0667 "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 "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 "DaCapo Benchmark - Java Test: Apache Lucene Search Index (msec)",LIB,,,,4613,4589,4580,4602 "Xmrig - Variant: Wownero - Hash Count: 1M (H/s)",HIB,,,,25814.4,25943.7,25385.9,25396.8 "DaCapo Benchmark - Java Test: H2 Database Engine (msec)",LIB,,,,2675,2655,2773,2634 "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: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,182.5085,182.7643,181.1043,181.1155 "TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,,,,51.34,51.57,51.56,51.49 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,129.8749,129.8035,130.4755,130.7937 "Neural Magic DeepSparse - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,123.0157,122.955,122.3307,121.8001 "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, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,123.8817,123.785,123.1469,122.9312 "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 "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: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,2208.1537,2199.4941,2195.9198,2189.0655 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,,,,59.8833,59.6674,60.0613,60.0284 "Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,,,,266.8799,267.8417,266.034,266.2776 "DaCapo Benchmark - Java Test: Tradebeans (msec)",LIB,,,,8561,8600,8520,8380 "7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,,,,212209,211584,211815,211383 "7-Zip Compression - Test: Compression Rating (MIPS)",HIB,,,,241545,242399,240287,241191 "SVT-AV1 - Encoder Mode: Preset 4 - Input: Bosphorus 4K (FPS)",HIB,,,,5.801,5.899,5.829,5.977 "Embree - Binary: Pathtracer - Model: Asian Dragon Obj (FPS)",HIB,,,,37.284,36.8586,37.4405,37.4056 "Llama.cpp - Model: llama-2-13b.Q4_0.gguf (Tokens/sec)",HIB,,,,17.94,17.87,17.87,18.08 "Y-Cruncher - Pi Digits To Calculate: 1B (sec)",LIB,33.923,10.416,10.476,11.676,11.595,11.902,11.975 "Embree - Binary: Pathtracer ISPC - Model: Asian Dragon Obj (FPS)",HIB,,,,38.9378,39.107,39.0046,39.1421 "DaCapo Benchmark - Java Test: Tradesoap (msec)",LIB,,,,5403,5168,5366,5149 "DaCapo Benchmark - Java Test: BioJava Biological Data Framework (msec)",LIB,,,,7874,7858,7904,7907 "PyTorch - Device: CPU - Batch Size: 1 - Model: ResNet-50 (batches/sec)",HIB,,,,52.44,52.78,53.00,53.30 "Timed FFmpeg Compilation - Time To Compile (sec)",LIB,,,,23.557,23.759,24.446,24.3 "DaCapo Benchmark - Java Test: Jython (msec)",LIB,,,,6703,6773,6865,6769 "DaCapo Benchmark - Java Test: jMonkeyEngine (msec)",LIB,,,,6914,6917,6917,6916 "DaCapo Benchmark - Java Test: GraphChi (msec)",LIB,,,,3536,3630,3538,3656 "Embree - Binary: Pathtracer - Model: Crown (FPS)",HIB,,,,36.9584,37.2545,35.9147,36.2812 "Embree - Binary: Pathtracer ISPC - Model: Crown (FPS)",HIB,,,,37.2967,37.6791,36.9967,36.9369 "DaCapo Benchmark - Java Test: H2O In-Memory Platform For Machine Learning (msec)",LIB,,,,3974,3868,3979,3755 "Llama.cpp - Model: llama-2-7b.Q4_0.gguf (Tokens/sec)",HIB,,,,29.75,29.9,29.74,29.85 "DaCapo Benchmark - Java Test: Apache Kafka (msec)",LIB,,,,5110,5121,5111,5114 "Embree - Binary: Pathtracer - Model: Asian Dragon (FPS)",HIB,,,,41.5958,41.8198,41.5696,41.557 "TensorFlow - Device: CPU - Batch Size: 1 - Model: ResNet-50 (images/sec)",HIB,,,,8.74,8.77,8.61,8.59 "DaCapo Benchmark - Java Test: Avrora AVR Simulation Framework (msec)",LIB,,,,5613,5441,5561,5572 "Embree - Binary: Pathtracer ISPC - Model: Asian Dragon (FPS)",HIB,,,,45.9374,46.3088,45.4648,45.6482 "SVT-AV1 - Encoder Mode: Preset 8 - Input: Bosphorus 4K (FPS)",HIB,,,,48.451,58.715,47.253,58.642 "Y-Cruncher - Pi Digits To Calculate: 500M (sec)",LIB,15.693,5.202,5.213,5.656,5.685,5.783,5.751 "DaCapo Benchmark - Java Test: Spring Boot (msec)",LIB,,,,2444,2460,2533,2452 "TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,,,,158.47,155.77,157.6,158.08 "TensorFlow - Device: CPU - Batch Size: 1 - Model: VGG-16 (images/sec)",HIB,,,,9.73,9.75,9.77,9.75 "DaCapo Benchmark - Java Test: Apache Tomcat (msec)",LIB,,,,2107,2082,2094,2112 "DaCapo Benchmark - Java Test: Apache Lucene Search Engine (msec)",LIB,,,,1402,1425,1379,1433 "SVT-AV1 - Encoder Mode: Preset 13 - Input: Bosphorus 4K (FPS)",HIB,,,,185.665,184.981,183.899,184.099 "SVT-AV1 - Encoder Mode: Preset 12 - Input: Bosphorus 4K (FPS)",HIB,,,,186.625,185.562,180.955,186.368 "DaCapo Benchmark - Java Test: PMD Source Code Analyzer (msec)",LIB,,,,1784,1820,1966,1833 "TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,,,,272.93,274.97,274.97,276.19 "DaCapo Benchmark - Java Test: Batik SVG Toolkit (msec)",LIB,,,,1733,1723,1718,1738 "TensorFlow - Device: CPU - Batch Size: 1 - Model: GoogLeNet (images/sec)",HIB,,,,28.99,28.71,27.73,28.79 "TensorFlow - Device: CPU - Batch Size: 1 - Model: AlexNet (images/sec)",HIB,,,,32.12,31.92,33.14,33.02 "DaCapo Benchmark - Java Test: FOP Print Formatter (msec)",LIB,,,,751,696,764,758 "DaCapo Benchmark - Java Test: Apache Xalan XSLT (msec)",LIB,,,,871,859,852,861 "DaCapo Benchmark - Java Test: Zxing 1D/2D Barcode Image Processing (msec)",LIB,,,,609,599,569,599 "CPU Power Consumption Monitor - Phoronix Test Suite System Monitoring (Watts)",,585.92,,,,,, "Meta Performance Per Watts - Performance Per Watts (Performance/Watts)",HIB,13064001.6555,,,,,, "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,,,,,,