Benchmarks 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 2211102-PTS-GENOAEXT88
AMD EPYC 9554 EPYC 9654 Benchmarks Genoa
Benchmarks for a future article.
,,"EPYC 9654 2P","EPYC 9654 2P Repeat","EPYC 9654 2P - Perf M","EPYC 9654","EPYC 9654 Repeat","EPYC 9654 Power","9654 Power","AMD EPYC 75F3 32-Core","75F32","9554 TwoP","EPYC 9554","8380 2p"
Processor,,2 x AMD EPYC 9654 96-Core @ 3.71GHz (192 Cores / 384 Threads),2 x AMD EPYC 9654 96-Core @ 3.71GHz (192 Cores / 384 Threads),2 x AMD EPYC 9654 96-Core @ 3.71GHz (192 Cores / 384 Threads),AMD EPYC 9654 96-Core @ 3.71GHz (96 Cores / 192 Threads),AMD EPYC 9654 96-Core @ 3.71GHz (96 Cores / 192 Threads),AMD EPYC 9654 96-Core @ 3.71GHz (96 Cores / 192 Threads),AMD EPYC 9654 96-Core @ 3.71GHz (96 Cores / 192 Threads),AMD EPYC 75F3 32-Core @ 2.95GHz (32 Cores / 64 Threads),AMD EPYC 75F3 32-Core @ 2.95GHz (32 Cores / 64 Threads),2 x AMD EPYC 9554 64-Core @ 3.76GHz (128 Cores / 256 Threads),AMD EPYC 9554 64-Core @ 3.76GHz (64 Cores / 128 Threads),2 x Intel Xeon Platinum 8380 @ 3.40GHz (80 Cores / 160 Threads)
Motherboard,,AMD Titanite_4G (RTI1002E BIOS),AMD Titanite_4G (RTI1002E BIOS),AMD Titanite_4G (RTI1002E BIOS),AMD Titanite_4G (RTI1002E BIOS),AMD Titanite_4G (RTI1002E BIOS),AMD Titanite_4G (RTI1002E BIOS),AMD Titanite_4G (RTI1002E BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD DAYTONA_X (RYM1009B BIOS),AMD Titanite_4G (RTI1002E BIOS),AMD Titanite_4G (RTI1002E BIOS),Intel M50CYP2SB2U (SE5C6200.86B.0022.D08.2103221623 BIOS)
Chipset,,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4,AMD Device 14a4,AMD Starship/Matisse,AMD Starship/Matisse,AMD Device 14a4,AMD Device 14a4,Intel Ice Lake IEH
Memory,,1520GB,1520GB,1520GB,768GB,768GB,768GB,768GB,256GB,256GB,1520GB,768GB,512GB
Disk,,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP,3841GB Micron_9300_MTFDHAL3T8TDP
Graphics,,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED,ASPEED
Monitor,,VGA HDMI,VGA HDMI,VGA HDMI,VGA HDMI,VGA HDMI,VGA HDMI,VGA HDMI,VE228,VE228,VGA HDMI,VGA HDMI,VE228
Network,,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe,2 x Mellanox MT27710,2 x Mellanox MT27710,Broadcom NetXtreme BCM5720 PCIe,Broadcom NetXtreme BCM5720 PCIe,2 x Intel X710 for 10GBASE-T + 2 x Intel E810-C for QSFP
OS,,Ubuntu 22.10,Ubuntu 22.10,Ubuntu 22.10,Ubuntu 22.10,Ubuntu 22.10,Ubuntu 22.10,Ubuntu 22.10,Ubuntu 22.10,Ubuntu 22.10,Ubuntu 22.10,Ubuntu 22.10,Ubuntu 22.10
Kernel,,6.0.0-060000rc3daily20220904-generic (x86_64),6.0.0-060000rc3daily20220904-generic (x86_64),6.0.0-060000rc3daily20220904-generic (x86_64),6.0.0-060000rc3daily20220904-generic (x86_64),6.0.0-060000rc3daily20220904-generic (x86_64),6.0.0-060000rc3daily20220904-generic (x86_64),6.0.0-060000rc3daily20220904-generic (x86_64),6.0.0-060000rc3daily20220904-generic (x86_64),6.0.0-060000rc3daily20220904-generic (x86_64),6.0.0-060000rc3daily20220904-generic (x86_64),6.0.0-060000rc3daily20220904-generic (x86_64),6.0.0-060000rc3daily20220904-generic (x86_64)
Desktop,,GNOME Shell,GNOME Shell,GNOME Shell,GNOME Shell,GNOME Shell,GNOME Shell,GNOME Shell,GNOME Shell,GNOME Shell,GNOME Shell,GNOME Shell,GNOME Shell
Display Server,,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3,X Server 1.21.1.3
Vulkan,,1.3.211,1.3.211,1.3.211,1.3.211,1.3.211,1.3.211,1.3.211,1.3.211,1.3.211,1.3.211,1.3.211,1.3.211
Compiler,,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0,GCC 12.2.0
File-System,,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4,ext4
Screen Resolution,,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080,1920x1080
,,"EPYC 9654 2P","EPYC 9654 2P Repeat","EPYC 9654 2P - Perf M","EPYC 9654","EPYC 9654 Repeat","EPYC 9654 Power","9654 Power","AMD EPYC 75F3 32-Core","75F32","9554 TwoP","EPYC 9554","8380 2p"
"Apache HBase - Rows: 1000000 - Test: Increment - Clients: 500 (us - Latency)",LIB,,,,,,,,4352,4409,,,
"Apache HBase - Rows: 1000000 - Test: Increment - Clients: 500 (Rows/sec)",HIB,,,,,,,,113983,112527,,,
"Apache HBase - Rows: 1000000 - Test: Increment - Clients: 256 (us - Latency)",LIB,1993,,,,,,,2062,2026,,,
"Apache HBase - Rows: 1000000 - Test: Increment - Clients: 256 (Rows/sec)",HIB,127105,,,,,,,123070,125256,,,
"TensorFlow - Device: CPU - Batch Size: 512 - Model: VGG-16 (images/sec)",HIB,122.13,123.2,110.75,69.57,69.54,73.65,73.86,8.39,8.39,97.32,,37.04
"TensorFlow - Device: CPU - Batch Size: 256 - Model: VGG-16 (images/sec)",HIB,111.05,113.24,104.39,66.42,66.49,70.93,70.84,8.32,8.33,92.72,,35.78
"TensorFlow - Device: CPU - Batch Size: 512 - Model: ResNet-50 (images/sec)",HIB,147.32,147.82,145.44,165,164.66,172.75,172.84,22.81,22.61,163.93,,83.01
"HammerDB - MariaDB - Virtual Users: 64 - Warehouses: 250 (Transactions/min)",HIB,,,,,,,,,,28707,,107938
"HammerDB - MariaDB - Virtual Users: 64 - Warehouses: 250 (New Orders/min)",HIB,,,,,,,,,,12322,,46470
"HammerDB - MariaDB - Virtual Users: 64 - Warehouses: 500 (Transactions/min)",HIB,,,,,,,,,,26791,,102799
"HammerDB - MariaDB - Virtual Users: 64 - Warehouses: 500 (New Orders/min)",HIB,,,,,,,,,,11578,,44267
"HammerDB - MariaDB - Virtual Users: 64 - Warehouses: 100 (Transactions/min)",HIB,,,,,,,,,,86231,,108494
"HammerDB - MariaDB - Virtual Users: 64 - Warehouses: 100 (New Orders/min)",HIB,,,,,,,,,,37109,,46690
"SMHasher - Hash: SHA3-256 (cycles/hash)",LIB,1829.798,1829.043,1829.207,1829.749,1871.004,1830.336,1829.028,,,2331.753,2331.575,1876.363
"SMHasher - Hash: SHA3-256 (MiB/sec)",HIB,216.01,216.02,216.15,216.08,211.82,216.13,216.08,,,169.55,169.57,208.31
"TensorFlow - Device: CPU - Batch Size: 256 - Model: ResNet-50 (images/sec)",HIB,111.54,110.01,108.07,146.3,146.45,150.26,149.71,22.08,21.95,127.49,,80.79
"OpenFOAM - Input: drivaerFastback, Medium Mesh Size - Execution Time (sec)",LIB,107.85826,104.23027,112.69451,246.8784,246.82702,237.49597,240.38495,662.50325,664.54696,129.83749,298.96059,365.30704
"OpenFOAM - Input: drivaerFastback, Medium Mesh Size - Mesh Time (sec)",LIB,133.96745,118.67648,141.1001,119.71925,131.63939,113.75167,111.27604,140.04797,138.87709,116.48849,103.94225,165.08078
"Apache HBase - Rows: 10000 - Test: Scan - Clients: 500 (Rows/sec)",HIB,,,,,,,,,,,,
"Apache HBase - Rows: 10000 - Test: Scan - Clients: 256 (Rows/sec)",HIB,,,,,,,,,,,,
"Apache HBase - Rows: 1000000 - Test: Scan - Clients: 1 (Rows/sec)",HIB,,,,,,,,,131234,,,
"Apache HBase - Rows: 10000 - Test: Scan - Clients: 1 (Rows/sec)",HIB,,,,,,,,,23753,,,
"JPEG XL libjxl - Input: JPEG - Quality: 100 (MP/s)",HIB,0.73,0.7,0.73,0.77,0.73,0.73,0.74,0.69,0.71,0.69,0.75,0.56
"JPEG XL libjxl - Input: PNG - Quality: 100 (MP/s)",HIB,0.8,0.79,0.8,0.82,0.82,0.82,0.81,0.75,0.75,0.82,0.81,0.58
"FFmpeg - Encoder: libx264 - Scenario: Upload (FPS)",HIB,,,,,,,,,,12.69,,10.54
"FFmpeg - Encoder: libx264 - Scenario: Upload (sec)",LIB,,,,,,,,,,198.928088198,,239.53
"Apache HBase - Rows: 10000 - Test: Increment - Clients: 500 (us - Latency)",LIB,1599,,,,,,,1821,1702,,,
"Apache HBase - Rows: 10000 - Test: Increment - Clients: 500 (Rows/sec)",HIB,149429,,,,,,,154170,153938,,,
"TensorFlow - Device: CPU - Batch Size: 512 - Model: GoogLeNet (images/sec)",HIB,441.71,443.93,437.65,530.05,529.62,558.92,557.52,66.93,66.56,494.2,,298.78
"Apache HBase - Rows: 10000 - Test: Random Read - Clients: 500 (us - Latency)",LIB,468,,,,,,,529,589,,,
"Apache HBase - Rows: 10000 - Test: Random Read - Clients: 500 (Rows/sec)",HIB,339482,,,,,,,306869,278941,,,
"TensorFlow - Device: CPU - Batch Size: 64 - Model: VGG-16 (images/sec)",HIB,81.58,79.43,75.72,61.53,61.54,65.62,65.84,7.99,8,79.07,54.32,33.85
"FFmpeg - Encoder: libx264 - Scenario: Platform (FPS)",HIB,,,,,,,,,,48.96,,40.44
"FFmpeg - Encoder: libx264 - Scenario: Platform (sec)",LIB,,,,,,,,,,154.70927612,,187.34
"Timed Linux Kernel Compilation - Build: allmodconfig (sec)",LIB,100.41,100.525,108.584,173.494,174.426,157.734,157.455,390.846,393.153,113.862,186.87,228.529
"FFmpeg - Encoder: libx264 - Scenario: Video On Demand (FPS)",HIB,,,,,,,,,,49.11,,40.56
"FFmpeg - Encoder: libx264 - Scenario: Video On Demand (sec)",LIB,,,,,,,,,,154.245416515,,186.74
"Blender - Blend File: Barbershop - Compute: CPU-Only (sec)",LIB,72.86,72.78,81.91,143.42,143.56,127.45,127.78,417.12,418.91,97.12,,244.02
"FFmpeg - Encoder: libx265 - Scenario: Upload (FPS)",HIB,,,,,,,,,,27.78,,21.69
"FFmpeg - Encoder: libx265 - Scenario: Upload (sec)",LIB,,,,,,,,,,90.87735054,,116.41
"FFmpeg - Encoder: libx265 - Scenario: Platform (FPS)",HIB,,,,,,,,,,56.56,,43.09
"FFmpeg - Encoder: libx265 - Scenario: Platform (sec)",LIB,,,,,,,,,,133.931322421,,175.804151458
"FFmpeg - Encoder: libx265 - Scenario: Video On Demand (FPS)",HIB,,,,,,,,,,55.92,,43.37
"FFmpeg - Encoder: libx265 - Scenario: Video On Demand (sec)",LIB,,,,,,,,,,135.461286189,,174.66
"OpenRadioss - Model: Bird Strike on Windshield (sec)",LIB,208.98,208.25,216.62,120.27,121.04,113.86,111.68,143.06,141.83,165.5,108.81,144.33
"TensorFlow - Device: CPU - Batch Size: 64 - Model: ResNet-50 (images/sec)",HIB,57.85,59.49,58.76,99.93,100.91,100.8,100.73,20.64,20.52,69.01,,75.88
"TensorFlow - Device: CPU - Batch Size: 256 - Model: GoogLeNet (images/sec)",HIB,322.23,327.47,320.99,473.4,471.92,495.44,495.35,65.83,65.33,378.96,,291.08
"Timed Node.js Compilation - Time To Compile (sec)",LIB,95.541,95.425,98.302,122.911,122.749,117.06,117.309,230.153,230.015,99.523,133.459,170.992
"TensorFlow - Device: CPU - Batch Size: 32 - Model: VGG-16 (images/sec)",HIB,60.45,59.82,55.34,57.61,57.45,60.63,61.12,7.76,7.8,65.82,51.51,32.24
"Apache HBase - Rows: 10000 - Test: Increment - Clients: 256 (us - Latency)",LIB,864,,,,,,,981,1139,,,
"Apache HBase - Rows: 10000 - Test: Increment - Clients: 256 (Rows/sec)",HIB,155246,,,,,,,141825,129941,,,
"Apache HBase - Rows: 10000 - Test: Random Read - Clients: 256 (us - Latency)",LIB,270,,,,,,,377,445,,,
"Apache HBase - Rows: 10000 - Test: Random Read - Clients: 256 (Rows/sec)",HIB,388592,,,,,,,298877,266084,,,
"JPEG XL libjxl - Input: JPEG - Quality: 80 (MP/s)",HIB,9.29,9.32,9.29,9.68,9.68,9.7,9.77,9.59,9.45,9.53,9.79,7.52
"Apache HBase - Rows: 10000 - Test: Random Write - Clients: 256 (us - Latency)",LIB,,,,,,,,1953,1871,,,
"OpenRadioss - Model: INIVOL and Fluid Structure Interaction Drop Container (sec)",LIB,75.6,76.15,82.52,103.31,104.23,90.53,90.38,197.46,197.96,87.86,117.93,146.63
"JPEG XL libjxl - Input: PNG - Quality: 80 (MP/s)",HIB,9.57,9.49,9.68,9.95,9.94,9.95,10.05,10.02,9.77,9.72,10.08,7.74
"JPEG XL libjxl - Input: JPEG - Quality: 90 (MP/s)",HIB,9.23,9.05,9.28,9.57,9.58,9.62,9.64,9.51,9.33,9.29,9.71,7.42
"TensorFlow - Device: CPU - Batch Size: 512 - Model: AlexNet (images/sec)",HIB,1672.89,1669.87,1587.05,1373.02,1369.54,1467.71,1461.6,155.16,154.55,1649.63,,701.27
"JPEG XL libjxl - Input: PNG - Quality: 90 (MP/s)",HIB,9.48,9.47,9.62,9.9,9.87,9.9,9.98,9.86,9.68,9.64,10.01,7.74
"Apache HBase - Rows: 10000 - Test: Random Write - Clients: 256 (Rows/sec)",HIB,,,,,,,,367796,507877,,,
"TensorFlow - Device: CPU - Batch Size: 32 - Model: ResNet-50 (images/sec)",HIB,39.57,40.61,39.86,76.17,75.61,77.29,76.49,20.11,19.97,46.75,,67.33
"OpenRadioss - Model: Rubber O-Ring Seal Installation (sec)",LIB,124.51,126.01,131.11,68.04,66.59,61.49,61.51,68.23,68.47,79.68,49.82,82.15
"Apache HBase - Rows: 1000000 - Test: Increment - Clients: 1 (us - Latency)",LIB,69,,,,,,,74,90,,,
"Apache HBase - Rows: 1000000 - Test: Increment - Clients: 1 (Rows/sec)",HIB,14345,,,,,,,13341,11071,,,
"OpenRadioss - Model: Bumper Beam (sec)",LIB,76.4,75.76,82.83,73.39,77.93,70.82,69.93,91.01,92.1,72.64,70.48,86.3
"TensorFlow - Device: CPU - Batch Size: 16 - Model: VGG-16 (images/sec)",HIB,41,40.06,40.86,51.31,51.6,53.71,53.84,7.41,7.4,50.73,47.62,28.64
"libavif avifenc - Encoder Speed: 0 (sec)",LIB,63.562,63.108,63.078,62.299,62.274,61.731,62.037,77.929,77.848,62.262,61.171,79.667
"Apache HBase - Rows: 1000000 - Test: Random Read - Clients: 1 (us - Latency)",LIB,55,,,,,,,54,76,,,
"Apache HBase - Rows: 1000000 - Test: Random Read - Clients: 1 (Rows/sec)",HIB,17925,,,,,,,18216,13108,,,
"TensorFlow - Device: CPU - Batch Size: 16 - Model: ResNet-50 (images/sec)",HIB,21.51,22.48,22.29,52.44,52.44,53.4,52.97,18.53,18.5,29.83,,54.51
"FFmpeg - Encoder: libx265 - Scenario: Live (FPS)",HIB,,,,,,,,,,127.92,,114.06
"FFmpeg - Encoder: libx265 - Scenario: Live (sec)",LIB,,,,,,,,,,39.477733078,,44.27
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,964.8329,969.4243,1132.3775,1115.4963,1115.9013,971.9156,970.5421,658.3907,660.7807,911.1053,,837.5412
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,98.0408,97.2856,84.4798,43.0051,42.9884,48.8409,48.8566,24.1673,24.0973,70.2107,,47.7486
"Blender - Blend File: Pabellon Barcelona - Compute: CPU-Only (sec)",LIB,22.88,23.28,25.67,48.75,49.15,43.61,43.73,131.98,130.92,32.04,,77.12
"OpenFOAM - Input: drivaerFastback, Small Mesh Size - Execution Time (sec)",LIB,19.919399,19.631093,23.083579,29.738615,28.791715,24.509173,25.756809,56.44901,56.24677,20.906018,29.848701,42.117751
"OpenFOAM - Input: drivaerFastback, Small Mesh Size - Mesh Time (sec)",LIB,24.847602,25.539527,27.078221,23.919399,26.389312,23.774357,25.707768,27.369771,28.369974,22.631593,23.813094,34.432062
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,974.0153,966.6015,1131.6891,1110.0037,1112.4846,972.4797,972.1192,658.9745,660.9895,909.1243,,836.9029
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,97.4788,97.6967,84.2018,42.2142,43.1327,49.0518,48.9538,24.2269,24.1165,68.5689,,47.6525
"JPEG XL Decoding libjxl - CPU Threads: 1 (MP/s)",HIB,48.53,48.51,49.02,49.78,49.83,49.71,50.7,47.4,46.7,48.88,50.48,36.94
"TensorFlow - Device: CPU - Batch Size: 256 - Model: AlexNet (images/sec)",HIB,1279.03,1326.14,1198.78,1258.48,1257.65,1331.08,1332.68,148.12,148.28,1366.71,,654.98
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,144.0459,142.5791,155.2956,150.6057,151.3705,142.1002,141.0342,155.2589,156.1934,124.8089,,181.3562
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,663.579,671.4008,616.4604,318.5908,316.9094,337.0033,339.5245,102.8223,102.1985,511.6331,,220.229
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,114.3987,113.9772,125.4096,119.0525,119.5359,112.8884,112.4239,161.2269,161.3526,101.4258,,185.2793
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,836.9886,840.234,763.1827,402.574,400.7293,424.4335,426.3633,98.9738,98.9457,629.9053,,215.8094
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,11.3456,11.7502,11.4651,11.4062,11.2064,,19.7391,19.844,11.4,,19.139
"Neural Magic DeepSparse - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Synchronous Single-Stream (items/sec)",HIB,,88.0745,85.044,87.1775,87.6256,89.1886,,50.6446,50.378,87.6574,,52.2285
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,27.2902,29.4073,28.104,28.2158,26.6697,,61.3288,61.4289,38.2116,,51.4766
"Neural Magic DeepSparse - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Synchronous Single-Stream (items/sec)",HIB,,36.633,33.9949,35.5748,35.4341,37.4876,,16.3037,16.2774,26.165,,19.4232
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,27.2133,28.9745,28.0193,28.0928,26.8063,,61.4394,61.2586,38.3383,,50.7774
"Neural Magic DeepSparse - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Synchronous Single-Stream (items/sec)",HIB,,36.7364,34.5036,35.6818,35.5886,37.2968,,16.2744,16.3224,26.0786,,19.6909
"TensorFlow - Device: CPU - Batch Size: 64 - Model: GoogLeNet (images/sec)",HIB,157.71,166.76,168.86,295.82,310.69,316.07,305.7,64.47,65.21,194.59,,249.3
"Blender - Blend File: Classroom - Compute: CPU-Only (sec)",LIB,17.65,17.75,20.11,38.67,38.71,33.63,33.55,106.78,106.73,24.2,,61.97
"FFmpeg - Encoder: libx264 - Scenario: Live (FPS)",HIB,,,,,,,,,,220.66,,182.45
"FFmpeg - Encoder: libx264 - Scenario: Live (sec)",LIB,,,,,,,,,,22.885944059,,27.68
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,9.866,10.0306,9.8478,9.8059,9.77,,25.4781,25.5925,10.8598,,12.8394
"Neural Magic DeepSparse - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Synchronous Single-Stream (items/sec)",HIB,,101.3021,99.6372,101.5028,101.9321,102.3074,,39.2348,39.0595,92.0024,,77.83
"spaCy - Model: en_core_web_trf (tokens/sec)",HIB,2515,2461,2585,3234,3307,3186,3314,1894,1873,2118,,3868
"spaCy - Model: en_core_web_lg (tokens/sec)",HIB,13481,13467,13415,13551,13517,13527,13526,13654,13644,13540,,11140
"Apache HBase - Rows: 1000000 - Test: Scan - Clients: 256 (Rows/sec)",HIB,,,,,,,,,58887584,,,
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,72.6323,72.544,80.0948,76.6433,76.8488,72.331,72.0102,79.3471,79.53,64.009,,88.3012
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,1318.3224,1320.4156,1195.8283,625.932,624.2323,662.79,666.0508,201.3251,200.8362,997.8874,,452.3605
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,99.0265,97.5018,111.4821,106.5518,107.668,96.2264,95.9686,117.105,117.0188,90.0851,,120.3456
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,967.2269,982.4985,858.8745,449.3802,444.9684,497.6848,499.0893,136.3518,136.5358,709.1653,,331.5339
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,5.1748,5.4359,5.2236,5.2613,5.1375,,10.467,10.5574,6.002,,9.9106
"Neural Magic DeepSparse - Model: NLP Text Classification, DistilBERT mnli - Scenario: Synchronous Single-Stream (items/sec)",HIB,,193.0775,183.7787,191.3244,189.9258,194.4994,,95.4844,94.6742,166.3935,,100.8229
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (ms/batch)",LIB,43.0112,42.6258,49.1409,47.4746,47.5377,42.5217,42.3645,59.4734,59.3301,39.7045,,48.3411
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream (items/sec)",HIB,2227.4198,2244.1857,1949.0047,1010.1033,1008.1787,1127.3599,1131.4819,268.728,269.3961,1608.9891,,826.8057
"Apache HBase - Rows: 1000000 - Test: Scan - Clients: 500 (Rows/sec)",HIB,,,,,,,,,,,,
"Cpuminer-Opt - Algorithm: Myriad-Groestl (kH/s)",HIB,,,,,,,,5323.29,69090,9939.68,,42780
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,5.0334,5.2709,5.2151,5.212,5.0333,,11.716,11.7042,5.3104,,8.3167
"Neural Magic DeepSparse - Model: CV Detection,YOLOv5s COCO - Scenario: Synchronous Single-Stream (items/sec)",HIB,,198.4991,189.5308,191.6061,191.7217,198.5208,,85.317,85.4021,188.1361,,120.0709
"ClickHouse - 100M Rows Web Analytics Dataset, First Run / Cold Cache (Queries/min, Geo Mean)",HIB,,,,,,,,376.51,377.33,,,368.06
"ClickHouse - 100M Rows Web Analytics Dataset, Second Run (Queries/min, Geo Mean)",HIB,,,,,,,,402.41,401.99,,,389.47
"ClickHouse - 100M Rows Web Analytics Dataset, Third Run (Queries/min, Geo Mean)",HIB,,,,,,,,387.02,383.67,,,382.84
"Timed Godot Game Engine Compilation - Time To Compile (sec)",LIB,33.863,33.335,33.419,33.124,33.399,32.438,32.76,52.216,52.07,32.41,34.607,44.984
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (ms/batch)",LIB,,5.2274,5.2827,5.2064,5.1744,5.2442,,6.9821,6.9796,3.921,,4.4386
"Neural Magic DeepSparse - Model: CV Classification, ResNet-50 ImageNet - Scenario: Synchronous Single-Stream (items/sec)",HIB,,191.2068,189.2062,191.9953,193.1856,190.6164,,143.1656,143.2164,254.8952,,224.8469
"libavif avifenc - Encoder Speed: 2 (sec)",LIB,34.654,34.526,35.074,33.75,33.835,33.7,33.771,40.949,41.024,34.94,33.475,44.407
"Xmrig - Variant: Monero - Hash Count: 1M (H/s)",HIB,,,,,,,,24698.1,24506.8,82027.7,,26231.6
"OpenRadioss - Model: Cell Phone Drop Test (sec)",LIB,16.87,17.06,18.64,22.99,22.73,20.45,20.25,38.53,38.96,17.27,23.19,33.59
"Cpuminer-Opt - Algorithm: Garlicoin (kH/s)",HIB,,,,,,,,4386.9,2988.41,58240,,31390
"7-Zip Compression - Test: Decompression Rating (MIPS)",HIB,1323090,1309354,1176187,652935,653127,737688,739434,247362,247381,945724,527376,363204
"7-Zip Compression - Test: Compression Rating (MIPS)",HIB,940574,930946,908312,677342,673198,717647,719579,280572,277568,776447,565650,403978
"TensorFlow - Device: CPU - Batch Size: 32 - Model: GoogLeNet (images/sec)",HIB,108.56,108.94,108.71,227.88,225.06,214.98,229,65.28,65.53,138.44,,209.5
"ClickHouse - (Queries/min, Geo Mean)",HIB,,,,,,,,,,,,
"Stress-NG - Test: Atomic (Bogo Ops/s)",HIB,,,,,,,,160435.98,165666.65,241171.38,,197789.23
"Cpuminer-Opt - Algorithm: Ringcoin (kH/s)",HIB,,,,,,,,3864.56,3795.43,591.17,,4737
"Stress-NG - Test: Context Switching (Bogo Ops/s)",HIB,,,,,,,,14657098.15,14724434.09,7907313.68,,4007912.58
"Stress-NG - Test: Glibc C String Functions (Bogo Ops/s)",HIB,,,,,,,,5593873.2,5591675.77,28081271,,9412669.51
"Stress-NG - Test: Malloc (Bogo Ops/s)",HIB,,,,,,,,140011498.66,139310693.59,576947450.43,,210690160.09
"Stress-NG - Test: IO_uring (Bogo Ops/s)",HIB,,,,,,,,67389.93,67158.17,65946.55,,64705.57
"Stress-NG - Test: Futex (Bogo Ops/s)",HIB,,,,,,,,2573853.71,2708005.03,3307879.37,,1294371.34
"Stress-NG - Test: CPU Cache (Bogo Ops/s)",HIB,,,,,,,,88.14,100.49,33.95,,15.96
"Stress-NG - Test: System V Message Passing (Bogo Ops/s)",HIB,,,,,,,,8704140.32,8711498.67,8962692.12,,6498292.38
"Stress-NG - Test: NUMA (Bogo Ops/s)",HIB,,,,,,,,926.64,925.07,904.2,,693.4
"Stress-NG - Test: Socket Activity (Bogo Ops/s)",HIB,,,,,,,,52568.44,52321.47,79908.39,,8958.77
"Stress-NG - Test: Mutex (Bogo Ops/s)",HIB,,,,,,,,18586817.03,18679911.5,77897090.19,,43926099.15
"Stress-NG - Test: MEMFD (Bogo Ops/s)",HIB,,,,,,,,1076.68,1078.69,2624.53,,3857.49
"Stress-NG - Test: CPU Stress (Bogo Ops/s)",HIB,,,,,,,,85344.04,85478.88,366719.77,,213661.33
"Cpuminer-Opt - Algorithm: Quad SHA-256, Pyrite (kH/s)",HIB,,,,,,,,285840,286410,1795800,,909470
"Stress-NG - Test: Crypto (Bogo Ops/s)",HIB,,,,,,,,55423.94,55510.14,250785.92,,85416.53
"Stress-NG - Test: SENDFILE (Bogo Ops/s)",HIB,,,,,,,,645248.68,648949.28,2643264.33,,958441.04
"Stress-NG - Test: Forking (Bogo Ops/s)",HIB,,,,,,,,80179.88,80711.89,2370,,64952.62
"Stress-NG - Test: Vector Math (Bogo Ops/s)",HIB,,,,,,,,202508.2,202547.6,832532.65,,304766.81
"Stress-NG - Test: MMAP (Bogo Ops/s)",HIB,,,,,,,,508.45,511.98,4187.21,,3557.26
"Cpuminer-Opt - Algorithm: scrypt (kH/s)",HIB,,,,,,,,554.99,554.88,3939.46,,2222.77
"Stress-NG - Test: Matrix Math (Bogo Ops/s)",HIB,,,,,,,,141942.95,141780.31,683986.91,,320154.03
"Stress-NG - Test: Glibc Qsort Data Sorting (Bogo Ops/s)",HIB,,,,,,,,434.57,432.8,2210.09,,900.61
"Stress-NG - Test: Semaphores (Bogo Ops/s)",HIB,,,,,,,,6533513.16,6558615.43,19242578.69,,12534447.06
"Stress-NG - Test: Memory Copying (Bogo Ops/s)",HIB,,,,,,,,6643.95,6634.24,20141.24,,10739.63
"Cpuminer-Opt - Algorithm: Deepcoin (kH/s)",HIB,,,,,,,,31770,31760,122790,,63270
"Cpuminer-Opt - Algorithm: Triple SHA-256, Onecoin (kH/s)",HIB,,,,,,,,645080,644780,2560590,,1323260
"Cpuminer-Opt - Algorithm: Blake-2 S (kH/s)",HIB,,,,,,,,1493100,1476790,8659890,,4384310
"Cpuminer-Opt - Algorithm: x25x (kH/s)",HIB,,,,,,,,1399.59,1398.47,6438.59,,2657.99
"Cpuminer-Opt - Algorithm: Magi (kH/s)",HIB,,,,,,,,1432.98,1433.6,6463.85,,2250.31
"Cpuminer-Opt - Algorithm: LBC, LBRY Credits (kH/s)",HIB,,,,,,,,89790,89690,854630,,416520
"Cpuminer-Opt - Algorithm: Skeincoin (kH/s)",HIB,,,,,,,,287340,287340,1631830,,622200
"Xmrig - Variant: Wownero - Hash Count: 1M (H/s)",HIB,,,,,,,,25865.2,25841.1,97285.7,,40987
"Timed Linux Kernel Compilation - Build: defconfig (sec)",LIB,19.725,19.658,20.486,24.519,24.63,23.195,23.248,41.343,41.401,20.122,25.377,30.556
"Blender - Blend File: Fishy Cat - Compute: CPU-Only (sec)",LIB,10.56,10.46,11.51,20.38,20.83,18.21,18.14,52.15,52.23,13.6,,31.11
"TensorFlow - Device: CPU - Batch Size: 16 - Model: GoogLeNet (images/sec)",HIB,62.44,62.69,63.05,130.47,144.38,145.11,144.15,57.67,58.27,87.38,,167.05
"JPEG XL Decoding libjxl - CPU Threads: All (MP/s)",HIB,275.97,275.75,284.19,317.83,316.47,318.9,320.16,332.73,320.16,278.06,341.13,246.91
"x265 - Video Input: Bosphorus 4K (FPS)",HIB,22.94,24.3,22.86,31.16,31.32,31.57,31.33,28.64,28.73,23.42,31.73,24.77
"Timed Mesa Compilation - Time To Compile (sec)",LIB,20.089,20.131,20.01,20.75,20.828,20.398,20.496,26.151,26.319,20.195,20.721,26.702
"TensorFlow - Device: CPU - Batch Size: 64 - Model: AlexNet (images/sec)",HIB,475.54,545.59,535.77,834.42,838.94,870.59,866.54,129.35,129.43,645.23,,498.31
"Blender - Blend File: BMW27 - Compute: CPU-Only (sec)",LIB,7.53,7.47,8.47,15.69,15.43,14,13.73,41.47,41.41,9.93,,23.57
"TensorFlow - Device: CPU - Batch Size: 32 - Model: AlexNet (images/sec)",HIB,296.29,286.45,289.65,581.17,580.97,599.98,600.31,113.41,112.33,387.92,,402.14
"Y-Cruncher - Pi Digits To Calculate: 1B (sec)",LIB,10.154,10.13,10.164,6.516,6.54,6.47,6.354,14.505,14.462,7.996,6.36,10.499
"OpenFOAM - Input: motorBike - Execution Time (sec)",LIB,,5.98052,5.90181,4.301,4.35122,4.352,,4.66741,4.66676,5.92274,,
"SMHasher - Hash: FarmHash128 (cycles/hash)",LIB,47.828,47.825,47.829,47.825,47.825,47.825,47.824,,,61.345,61.351,50.218
"SMHasher - Hash: FarmHash128 (MiB/sec)",HIB,21167.17,21167.48,21167.29,21167.64,21166.21,21168.01,21167.11,,,16608.92,16609.29,19206.25
"SMHasher - Hash: MeowHash x86_64 AES-NI (cycles/hash)",LIB,45.11,45.11,45.114,45.11,45.112,45.112,45.106,,,57.74,57.732,51.419
"SMHasher - Hash: MeowHash x86_64 AES-NI (MiB/sec)",HIB,54190.54,54192.22,54144.85,54220.23,54212.96,54202.27,54175.08,,,42531.56,42535.23,45558.18
"TensorFlow - Device: CPU - Batch Size: 16 - Model: AlexNet (images/sec)",HIB,153.29,161.41,160.4,360.18,358.82,366.73,367.14,92.21,93.37,219.45,426.56,306.58
"Y-Cruncher - Pi Digits To Calculate: 500M (sec)",LIB,4.925,4.947,4.983,3.969,3.959,3.872,3.917,7.151,7.118,4.389,3.3,5.324
"x264 - Video Input: Bosphorus 4K (FPS)",HIB,104.77,104.56,65.37,65.8,109.74,65.5,66.6,59.01,73.97,97.7,58.79,51.8
"SMHasher - Hash: Spooky32 (cycles/hash)",LIB,26.855,27.617,26.662,26.703,26.663,26.683,27.617,,,34.264,34.268,37.699
"SMHasher - Hash: Spooky32 (MiB/sec)",HIB,20577.15,20580.28,20576.77,20581.55,20582.57,20582.79,20577.01,,,16145.69,16149.3,17883.71
"SMHasher - Hash: FarmHash32 x86_64 AVX (MiB/sec)",HIB,39795.99,39794.95,39795.43,39796.13,39795.04,39795.02,39794.11,,,31226.87,31226.57,32568.14
"SMHasher - Hash: FarmHash32 x86_64 AVX (cycles/hash)",LIB,26.387,26.387,26.387,26.387,26.387,26.387,26.387,,,33.661,33.656,31.909
"x265 - Video Input: Bosphorus 1080p (FPS)",HIB,,72.76,70.5,91.88,91.8,93.54,,84.07,84.18,69.28,,74.49
"SMHasher - Hash: fasthash32 (cycles/hash)",LIB,22.076,22.077,22.078,22.077,22.077,22.08,22.079,,,28.349,28.329,28.831
"SMHasher - Hash: fasthash32 (MiB/sec)",HIB,8803.42,8803.35,8803.4,8803.52,8775.9,8802.19,8803.73,,,6903.87,6907.82,8453.99
"SMHasher - Hash: t1ha2_atonce (MiB/sec)",HIB,20135.2,19789.96,20135.14,20134.69,20135.19,20135.17,20135.1,,,15798.76,15799.09,20601.61
"SMHasher - Hash: t1ha2_atonce (cycles/hash)",LIB,20.097,20.097,20.097,20.097,20.097,20.097,20.097,,,26.81,25.759,25.897
"SMHasher - Hash: t1ha0_aes_avx2 x86_64 (cycles/hash)",LIB,20.472,20.472,20.472,20.472,20.472,20.477,20.472,,,26.258,26.258,25.687
"SMHasher - Hash: t1ha0_aes_avx2 x86_64 (MiB/sec)",HIB,102425.27,101829.9,102396.46,102376.03,102315.37,102400.95,102394,,,80341.36,80231.04,64712.67
"Apache HBase - Rows: 10000 - Test: Increment - Clients: 1 (us - Latency)",LIB,181,,,,,,,237,267,,,
"Apache HBase - Rows: 10000 - Test: Increment - Clients: 1 (Rows/sec)",HIB,5319,,,,,,,4097,3631,,,
"libavif avifenc - Encoder Speed: 6, Lossless (sec)",LIB,5.323,5.21,5.241,5.161,5.226,5.083,5.227,6.536,6.651,5.316,5.247,7.447
"Apache HBase - Rows: 10000 - Test: Random Read - Clients: 1 (us - Latency)",LIB,142,,,,,,,186,189,,,
"Apache HBase - Rows: 10000 - Test: Random Read - Clients: 1 (Rows/sec)",HIB,6698,,,,,,,5189,5071,,,
"SMHasher - Hash: wyhash (MiB/sec)",HIB,31218.05,31247.36,31248.91,31198.52,31201.2,31197.92,31245.47,,,24475.93,24509.44,27859.54
"SMHasher - Hash: wyhash (cycles/hash)",LIB,13.988,13.968,14.215,13.968,13.968,13.968,13.984,,,18.19,18.085,19.627
"libavif avifenc - Encoder Speed: 10, Lossless (sec)",LIB,4.322,4.288,4.244,4.124,4.427,4.078,4.099,4.725,4.945,4.25,4.106,5.806
"Apache HBase - Rows: 10000 - Test: Random Write - Clients: 1 (us - Latency)",LIB,36,,,,,,,34,34,,,
"Apache HBase - Rows: 10000 - Test: Random Write - Clients: 1 (Rows/sec)",HIB,25907,,,,,,,26954,27027,,,
"x264 - Video Input: Bosphorus 1080p (FPS)",HIB,,265.96,200.65,211.7,265.77,221.25,,205.05,217.75,262.79,,193.65
"libavif avifenc - Encoder Speed: 6 (sec)",LIB,2.422,2.415,2.422,2.29,2.321,2.311,2.297,3.265,3.304,2.404,2.342,3.365