dddxxx

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2308067-NE-DDDXXX42317

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dddxxx, "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 200", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 500", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500", Higher Results Are Better "a", "b", "Stress-NG 0.15.10 - Test: Hash", Higher Results Are Better "a",485362.59,562036.81 "b",677341.08,599959.93 "Stress-NG 0.15.10 - Test: MMAP", Higher Results Are Better "a",24.05,17.67 "b",32.16,24.76 "Stress-NG 0.15.10 - Test: NUMA", Higher Results Are Better "a",59.57,48.32 "b",65.76,55.22 "Stress-NG 0.15.10 - Test: Pipe", Higher Results Are Better "a",1452490.32,1391729.36 "b",1665003.28,1401706.94 "Stress-NG 0.15.10 - Test: Poll", Higher Results Are Better "a",263822.46,304779.13 "b",342313.98,294619.02 "Stress-NG 0.15.10 - Test: Zlib", Higher Results Are Better "a",241.11,304.99 "b",357.4,314.42 "Stress-NG 0.15.10 - Test: Futex", Higher Results Are Better "a",449658.79,522498.57 "b",681521.49,566506.85 "Stress-NG 0.15.10 - Test: MEMFD", Higher Results Are Better "a",57.37,55.8 "b",43.81,42.37 "Stress-NG 0.15.10 - Test: Mutex", Higher Results Are Better "a",680312.12,528001.32 "b",715293.16,673831.77 "Stress-NG 0.15.10 - Test: Atomic", Higher Results Are Better "a",235.28,213.73 "b",261.51,238.47 "Stress-NG 0.15.10 - Test: Crypto", Higher Results Are Better "a",4542.8,4638.25 "b",5780.63,5588.43 "Stress-NG 0.15.10 - Test: Malloc", Higher Results Are Better "a",336296.97,415571 "b",480917.6,387394.59 "Stress-NG 0.15.10 - Test: Cloning", Higher Results Are Better "a",640.79,698.02 "b",718.05,713.11 "Stress-NG 0.15.10 - Test: Forking", Higher Results Are Better "a",9250.51,9853.07 "b",10809.66,13471.54 "Stress-NG 0.15.10 - Test: Pthread", Higher Results Are Better "a",30241.98,39706.53 "b",37853.74,46605.47 "Stress-NG 0.15.10 - Test: AVL Tree", Higher Results Are Better "a",16.46,16.36 "b",19.1,19.4 "Stress-NG 0.15.10 - Test: IO_uring", Higher Results Are Better "a",167994.9,172989.42 "b",183436.13,182437.22 "Stress-NG 0.15.10 - Test: SENDFILE", Higher Results Are Better "a",38449.72,35109.99 "b",44903.98,42600.76 "Stress-NG 0.15.10 - Test: CPU Cache", Higher Results Are Better "a",684180.05,1174176.81 "b",1292153.26,1014232.24 "Stress-NG 0.15.10 - Test: CPU Stress", Higher Results Are Better "a",6742.23,7877.86 "b",8025,7707.7 "Stress-NG 0.15.10 - Test: Semaphores", Higher Results Are Better "a",3506040.62,2931410.39 "b",3311568.51,3171247.91 "Stress-NG 0.15.10 - Test: Matrix Math", Higher Results Are Better "a",18343.8,16293.5 "b",17971.42,16262.15 "Stress-NG 0.15.10 - Test: Vector Math", Higher Results Are Better "a",13091.83,12240.55 "b",13357.99,11530.66 "Stress-NG 0.15.10 - Test: Function Call", Higher Results Are Better "a",2155.07,1962.33 "b",2204.6,2123.79 "Stress-NG 0.15.10 - Test: x86_64 RdRand", Higher Results Are Better "a",3280.67,3253.94 "b",3202.49,3065.58 "Stress-NG 0.15.10 - Test: Floating Point", Higher Results Are Better "a",718.83,768.83 "b",788.52,737.19 "Stress-NG 0.15.10 - Test: Matrix 3D Math", Higher Results Are Better "a",378.13,388.85 "b",389.85,402.2 "Stress-NG 0.15.10 - Test: Memory Copying", Higher Results Are Better "a",1119.58,1037.87 "b",1128.8,1048.69 "Stress-NG 0.15.10 - Test: Vector Shuffle", Higher Results Are Better "a",2464.61,2397.83 "b",2448.08,2413.94 "Stress-NG 0.15.10 - Test: Socket Activity", Higher Results Are Better "a",2745.41,2245.72 "b",2779.7,2237.55 "Stress-NG 0.15.10 - Test: Wide Vector Math", Higher Results Are Better "a",150308.6,144321.09 "b",151718.42,145059.16 "Stress-NG 0.15.10 - Test: Context Switching", Higher Results Are Better "a",758460.47,652135.45 "b",717034.91,749504.66 "Stress-NG 0.15.10 - Test: Fused Multiply-Add", Higher Results Are Better "a",3041463.38,2915002.08 "b",3000044.16,2474922.44 "Stress-NG 0.15.10 - Test: Vector Floating Point", Higher Results Are Better "a",7653.43,6925.21 "b",8188.53,7566.87 "Stress-NG 0.15.10 - Test: Glibc C String Functions", Higher Results Are Better "a",2577995.44,2393716.7 "b",2518708.67,2202469.53 "Stress-NG 0.15.10 - Test: Glibc Qsort Data Sorting", Higher Results Are Better "a",75.03,63.23 "b",77.86,70.39 "Stress-NG 0.15.10 - Test: System V Message Passing", Higher Results Are Better "a",2772214.99,2532710.25 "b",2720005.31,2319826.89 "dav1d 1.2.1 - Video Input: Chimera 1080p", Higher Results Are Better "a",246.87,241.36 "b",251.57,247.67 "dav1d 1.2.1 - Video Input: Summer Nature 4K", Higher Results Are Better "a",66.7,67.32 "b",64.03,68.73 "dav1d 1.2.1 - Video Input: Summer Nature 1080p", Higher Results Are Better "a",277.49,269.2 "b",313.48,308.39 "dav1d 1.2.1 - Video Input: Chimera 1080p 10-bit", Higher Results Are Better "a",210.71,171.89 "b",203.68,178.06 "Xonotic 0.8.6 - Resolution: 1920 x 1080 - Effects Quality: Low", Higher Results Are Better "a",206.3217317,204.8907335 "b",206.0452747,204.8519772 "Xonotic 0.8.6 - Resolution: 1920 x 1080 - Effects Quality: High", Higher Results Are Better "a",91.1527989,91.0763988 "b",91.2262973,90.5897217 "Xonotic 0.8.6 - Resolution: 1920 x 1080 - Effects Quality: Ultra", Higher Results Are Better "a",78.0963229,77.7714242 "b",77.9255439,77.1136335 "Xonotic 0.8.6 - Resolution: 1920 x 1080 - Effects Quality: Ultimate", Higher Results Are Better "a",59.2384913,59.1032851 "b",58.8897832,59.010095 "Embree 4.1 - Binary: Pathtracer - Model: Crown", Higher Results Are Better "a",3.515,3.5285 "b",3.521,3.3874 "Embree 4.1 - Binary: Pathtracer ISPC - Model: Crown", Higher Results Are Better "a",3.6709,3.8029 "b",3.8001,3.5922 "Embree 4.1 - Binary: Pathtracer - Model: Asian Dragon", Higher Results Are Better "a",4.2597,4.1769 "b",4.2237,4.1759 "Embree 4.1 - Binary: Pathtracer - Model: Asian Dragon Obj", Higher Results Are Better "a",3.875,3.7708 "b",3.8381,3.8625 "Embree 4.1 - Binary: Pathtracer ISPC - Model: Asian Dragon", Higher Results Are Better "a",4.858,4.7186 "b",4.8,4.7271 "Embree 4.1 - Binary: Pathtracer ISPC - Model: Asian Dragon Obj", Higher Results Are Better "a",4.1398,4.1942 "b",4.1804,3.8041 "SVT-AV1 1.6 - Encoder Mode: Preset 4 - Input: Bosphorus 4K", Higher Results Are Better "a",1.069,1.114 "b",0.945,0.95 "SVT-AV1 1.6 - Encoder Mode: Preset 8 - Input: Bosphorus 4K", Higher Results Are Better "a",9.796,9.183 "b",10.596,8.276 "SVT-AV1 1.6 - Encoder Mode: Preset 12 - Input: Bosphorus 4K", Higher Results Are Better "a",34.585,36.409 "b",29.786,28.17 "SVT-AV1 1.6 - Encoder Mode: Preset 13 - Input: Bosphorus 4K", Higher Results Are Better "a",36.153,31.945 "b",33.684,28.266 "SVT-AV1 1.6 - Encoder Mode: Preset 4 - Input: Bosphorus 1080p", Higher Results Are Better "a",4.755,3.765 "b",4.881,4.664 "SVT-AV1 1.6 - Encoder Mode: Preset 8 - Input: Bosphorus 1080p", Higher Results Are Better "a",36.607,34.871 "b",28.432,33.596 "SVT-AV1 1.6 - Encoder Mode: Preset 12 - Input: Bosphorus 1080p", Higher Results Are Better "a",154.834,154.36 "b",158.387,156.996 "SVT-AV1 1.6 - Encoder Mode: Preset 13 - Input: Bosphorus 1080p", Higher Results Are Better "a",203.514,202.189 "b",207.604,205.933 "VVenC 1.9 - Video Input: Bosphorus 4K - Video Preset: Fast", Higher Results Are Better "a",1.192,1.167 "b",1.182,1.157 "VVenC 1.9 - Video Input: Bosphorus 4K - Video Preset: Faster", Higher Results Are Better "a",2.745,2.641 "b",2.716,2.627 "VVenC 1.9 - Video Input: Bosphorus 1080p - Video Preset: Fast", Higher Results Are Better "a",3.919,3.89 "b",3.748,3.832 "VVenC 1.9 - Video Input: Bosphorus 1080p - Video Preset: Faster", Higher Results Are Better "a",9.792,9.971 "b",10.47,9.265 "vkpeak 20230730 - fp32-scalar", Higher Results Are Better "a",268.33,268.33 "b",268.34,268.31 "libxsmm 2-1.17-3645 - M N K: 128", Higher Results Are Better "a",84.5,75.3 "b",87.8,79.6 "libxsmm 2-1.17-3645 - M N K: 32", Higher Results Are Better "a",47.3,48 "b",47.4,48.5 "libxsmm 2-1.17-3645 - M N K: 64", Higher Results Are Better "a",95.3,86.4 "b",95.6,86 "Intel Open Image Denoise 2.0 - Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only", Higher Results Are Better "a",0.11702873406508,0.11764871974663 "b",0.11672547685275,0.1154050775926 "Intel Open Image Denoise 2.0 - Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only", Higher Results Are Better "a",0.11745429559723,0.11640874369356 "b",0.11498587973397,0.11544144809753 "Intel Open Image Denoise 2.0 - Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only", Higher Results Are Better "a",0.058828028025673,0.058614242088543 "b",0.057217403245371,0.057874724371625 "OSPRay 2.12 - Benchmark: particle_volume/ao/real_time", Higher Results Are Better "a",1.39648,1.59019 "b",1.3411,1.3972 "OSPRay 2.12 - Benchmark: particle_volume/scivis/real_time", Higher Results Are Better "a",1.37483,1.37315 "b",1.34754,1.34179 "OSPRay 2.12 - Benchmark: particle_volume/pathtracer/real_time", Higher Results Are Better "a",52.0041,53.1767 "b",50.0668,50.0989 "OSPRay 2.12 - Benchmark: gravity_spheres_volume/dim_512/ao/real_time", Higher Results Are Better "a",0.735338,0.754953 "b",0.725822,0.743744 "OSPRay 2.12 - Benchmark: gravity_spheres_volume/dim_512/scivis/real_time", Higher Results Are Better "a",0.607886,0.636478 "b",0.684773,0.735198 "OSPRay 2.12 - Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time", Higher Results Are Better "a",1.0498,1.07347 "b",1.02982,0.996086 "Neural Magic DeepSparse 1.5 - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",2.558,2.1474 "b",2.5675,2.1029 "Neural Magic DeepSparse 1.5 - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",65.7971,65.0528 "b",65.6473,65.0654 "Neural Magic DeepSparse 1.5 - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",31.2184,26.6185 "b",31.1293,25.7986 "Neural Magic DeepSparse 1.5 - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",9.3824,7.2193 "b",9.377,7.1893 "Neural Magic DeepSparse 1.5 - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",33.3984,27.7362 "b",33.0577,26.4628 "Neural Magic DeepSparse 1.5 - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",216.8403,176.7283 "b",217.2391,173.7324 "Neural Magic DeepSparse 1.5 - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",16.2846,13.0593 "b",16.4261,12.7876 "Neural Magic DeepSparse 1.5 - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",3.0647,2.2706 "b",3.2273,3.2648 "Neural Magic DeepSparse 1.5 - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",32.5325,26.7845 "b",26.2928,31.6315 "Neural Magic DeepSparse 1.5 - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",14.2222,10.8659 "b",12.8495,13.0509 "Neural Magic DeepSparse 1.5 - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",19.8726,15.1521 "b",23.8494,17.6034 "Neural Magic DeepSparse 1.5 - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",3.0309,2.932 "b",3.6435,2.8204 "Neural Magic DeepSparse 1.5 - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",21.2257,21.3712 "b",34.4544,34.1917 "Neural Magic DeepSparse 1.5 - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",8.8508,10.0597 "b",11.4082,10.9355 "Neural Magic DeepSparse 1.5 - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream", Higher Results Are Better "a",2.0224,2.0394 "b",2.421,2.3555 "QuantLib 1.30 - ", Higher Results Are Better "a",2169.6,2590 "b",2170.5,2639 "Apache Cassandra 4.1.3 - Test: Writes", Higher Results Are Better "a",26571,26273 "b",26509,26366 "Memcached 1.6.19 - Set To Get Ratio: 1:5", Higher Results Are Better "a",537655.32,513081.46 "b",532274.82,504341.58 "Memcached 1.6.19 - Set To Get Ratio: 1:10", Higher Results Are Better "a",511598.27,492502.59 "b",482317.32,491297.66 "Memcached 1.6.19 - Set To Get Ratio: 1:100", Higher Results Are Better "a",507090.65,485528.86 "b",500704.28,471140.98 "Redis 7.0.12 + memtier_benchmark 2.0 - Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:5", Higher Results Are Better "a",1082776.68,995845.55 "b",1403612.89,1394153.12 "Redis 7.0.12 + memtier_benchmark 2.0 - Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:5", Higher Results Are Better "a",1061563.79,971842.74 "b",1411424.72,1332641.63 "Redis 7.0.12 + memtier_benchmark 2.0 - Protocol: Redis - Clients: 50 - Set To Get Ratio: 1:10", Higher Results Are Better "a",1090630.95,1128993.92 "b",1473184.51,1437159.21 "Redis 7.0.12 + memtier_benchmark 2.0 - Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:5", Higher Results Are Better "a",898748.65,881999.8 "b",1274284.14,1222937.26 "Redis 7.0.12 + memtier_benchmark 2.0 - Protocol: Redis - Clients: 100 - Set To Get Ratio: 1:10", Higher Results Are Better "a",1028072.2,1029210.18 "b",1385940.7,1369726.26 "Redis 7.0.12 + memtier_benchmark 2.0 - Protocol: Redis - Clients: 500 - Set To Get Ratio: 1:10", Higher Results Are Better "a",959741.15,869182.88 "b",1316823.16,1190224.22 "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 200", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 100 - Sensor Count: 500", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 200", Higher Results Are Better "a", "b", "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 100 - Sensor Count: 500", Higher Results Are Better "a", "b", "Liquid-DSP 1.6 - Threads: 1 - Buffer Length: 256 - Filter Length: 32", Higher Results Are Better "a",46968000,46065000 "b",46748000,46902000 "Liquid-DSP 1.6 - Threads: 1 - Buffer Length: 256 - Filter Length: 57", Higher Results Are Better "a",43654000,43204000 "b",43582000,43273000 "Liquid-DSP 1.6 - Threads: 2 - Buffer Length: 256 - Filter Length: 32", Higher Results Are Better "a",86424000,84677000 "b",86825000,84503000 "Liquid-DSP 1.6 - Threads: 2 - Buffer Length: 256 - Filter Length: 57", Higher Results Are Better "a",73924000,73667000 "b",74241000,73000000 "Liquid-DSP 1.6 - Threads: 4 - Buffer Length: 256 - Filter Length: 32", Higher Results Are Better "a",142930000,137630000 "b",142560000,137340000 "Liquid-DSP 1.6 - Threads: 4 - Buffer Length: 256 - Filter Length: 57", Higher Results Are Better "a",125950000,113230000 "b",115600000,108810000 "Liquid-DSP 1.6 - Threads: 8 - Buffer Length: 256 - Filter Length: 32", Higher Results Are Better "a",189420000,166470000 "b",191020000,180060000 "Liquid-DSP 1.6 - Threads: 8 - Buffer Length: 256 - Filter Length: 57", Higher Results Are Better "a",145960000,134730000 "b",140100000,125560000 "Liquid-DSP 1.6 - Threads: 1 - Buffer Length: 256 - Filter Length: 512", Higher Results Are Better "a",7713700,7729900 "b",7690000,7731700 "Liquid-DSP 1.6 - Threads: 2 - Buffer Length: 256 - Filter Length: 512", Higher Results Are Better "a",15338000,15021000 "b",14874000,15173000 "Liquid-DSP 1.6 - Threads: 4 - Buffer Length: 256 - Filter Length: 512", Higher Results Are Better "a",26297000,25364000 "b",26291000,25334000 "Liquid-DSP 1.6 - Threads: 8 - Buffer Length: 256 - Filter Length: 512", Higher Results Are Better "a",39187000,32251000 "b",33953000,39093000 "NCNN 20230517 - Target: CPU - Model: mobilenet", Lower Results Are Better "a",25.74,26.11 "b",27.7,27.65 "NCNN 20230517 - Target: CPU-v2-v2 - Model: mobilenet-v2", Lower Results Are Better "a",5.99,7.39 "b",6.08,6.21 "NCNN 20230517 - Target: CPU-v3-v3 - Model: mobilenet-v3", Lower Results Are Better "a",4.34,5.94 "b",4.27,4.34 "NCNN 20230517 - Target: CPU - Model: shufflenet-v2", Lower Results Are Better "a",4.26,4.31 "b",3,3.03 "NCNN 20230517 - Target: CPU - Model: mnasnet", Lower Results Are Better "a",6.01,6.06 "b",4.46,4.51 "NCNN 20230517 - Target: CPU - Model: efficientnet-b0", Lower Results Are Better "a",9.13,10.42 "b",9.4,9.45 "NCNN 20230517 - Target: CPU - Model: blazeface", Lower Results Are Better "a",0.9,0.91 "b",0.93,0.93 "NCNN 20230517 - Target: CPU - Model: googlenet", Lower Results Are Better "a",16.15,16.3 "b",16.09,16.28 "NCNN 20230517 - Target: CPU - Model: vgg16", Lower Results Are Better "a",97.16,97.67 "b",101.08,96.41 "NCNN 20230517 - Target: CPU - Model: resnet18", Lower Results Are Better "a",12.57,12.65 "b",12.51,12.73 "NCNN 20230517 - Target: CPU - Model: alexnet", Lower Results Are Better "a",11.62,11.73 "b",11.57,11.71 "NCNN 20230517 - Target: CPU - Model: resnet50", Lower Results Are Better "a",36.06,35.97 "b",32.37,36.28 "NCNN 20230517 - Target: CPU - Model: yolov4-tiny", Lower Results Are Better "a",38.29,38.45 "b",40.13,38.48 "NCNN 20230517 - Target: CPU - Model: squeezenet_ssd", Lower Results Are Better "a",16.25,16.84 "b",15.43,16.17 "NCNN 20230517 - Target: CPU - Model: regnety_400m", Lower Results Are Better "a",10.17,9.89 "b",10.08,10.15 "NCNN 20230517 - Target: CPU - Model: vision_transformer", Lower Results Are Better "a",234.13,233.79 "b",237.2,227.13 "NCNN 20230517 - Target: CPU - Model: FastestDet", Lower Results Are Better "a",5.43,5.35 "b",5.7,5.39 "NCNN 20230517 - Target: Vulkan GPU - Model: mobilenet", Lower Results Are Better "a",28.34,27.96 "b",27.95,26.8 "NCNN 20230517 - Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2", Lower Results Are Better "a",6,7.33 "b",6.02,7.32 "NCNN 20230517 - Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3", Lower Results Are Better "a",4.34,5.87 "b",4.31,5.9 "NCNN 20230517 - Target: Vulkan GPU - Model: shufflenet-v2", Lower Results Are Better "a",3.03,4.29 "b",3.05,4.28 "NCNN 20230517 - Target: Vulkan GPU - Model: mnasnet", Lower Results Are Better "a",4.42,6.04 "b",4.48,6.03 "NCNN 20230517 - Target: Vulkan GPU - Model: efficientnet-b0", Lower Results Are Better "a",9.29,9.14 "b",9.36,9.32 "NCNN 20230517 - Target: Vulkan GPU - Model: blazeface", Lower Results Are Better "a",0.94,0.93 "b",0.95,0.96 "NCNN 20230517 - Target: Vulkan GPU - Model: googlenet", Lower Results Are Better "a",16.29,16.29 "b",16.2,16.18 "NCNN 20230517 - Target: Vulkan GPU - Model: vgg16", Lower Results Are Better "a",97.47,97.93 "b",96.15,96.37 "NCNN 20230517 - Target: Vulkan GPU - Model: resnet18", Lower Results Are Better "a",12.77,12.68 "b",12.52,12.6 "NCNN 20230517 - Target: Vulkan GPU - Model: alexnet", Lower Results Are Better "a",11.64,11.7 "b",11.65,11.72 "NCNN 20230517 - Target: Vulkan GPU - Model: resnet50", Lower Results Are Better "a",32.63,33.73 "b",32.24,34.96 "NCNN 20230517 - Target: Vulkan GPU - Model: yolov4-tiny", Lower Results Are Better "a",40.41,38.37 "b",40.27,38.06 "NCNN 20230517 - Target: Vulkan GPU - Model: squeezenet_ssd", Lower Results Are Better "a",15.5,16.43 "b",14.64,16.32 "NCNN 20230517 - Target: Vulkan GPU - Model: regnety_400m", Lower Results Are Better "a",9.81,9.83 "b",10.48,10.34 "NCNN 20230517 - Target: Vulkan GPU - Model: vision_transformer", Lower Results Are Better "a",236.83,243.23 "b",232.33,238.68 "NCNN 20230517 - Target: Vulkan GPU - Model: FastestDet", Lower Results Are Better "a",5.46,5.86 "b",5.43,5.51 "Neural Magic DeepSparse 1.5 - Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",780.0149,931.3389 "b",778.957,951.0294 "Neural Magic DeepSparse 1.5 - Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",30.3697,30.7099 "b",30.4348,30.6979 "Neural Magic DeepSparse 1.5 - Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",64.0224,75.0962 "b",64.1819,77.4607 "Neural Magic DeepSparse 1.5 - Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",212.9987,276.1247 "b",213.1979,278.0881 "Neural Magic DeepSparse 1.5 - Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",59.8602,72.0431 "b",60.4507,75.5498 "Neural Magic DeepSparse 1.5 - Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",9.2016,11.2914 "b",9.185,11.487 "Neural Magic DeepSparse 1.5 - Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",122.7855,153.1123 "b",121.7285,156.3664 "Neural Magic DeepSparse 1.5 - Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",650.5357,877.9995 "b",616.7822,612.5763 "Neural Magic DeepSparse 1.5 - Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",61.4536,74.6446 "b",76.0385,63.1976 "Neural Magic DeepSparse 1.5 - Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",140.427,183.9024 "b",155.3094,153.2077 "Neural Magic DeepSparse 1.5 - Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",100.6122,131.9244 "b",83.8397,113.5888 "Neural Magic DeepSparse 1.5 - Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",656.3411,682.0206 "b",548.8936,707.8341 "Neural Magic DeepSparse 1.5 - Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",94.1678,93.5286 "b",58.0157,58.4578 "Neural Magic DeepSparse 1.5 - Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",225.4551,198.5109 "b",175.2894,182.865 "Neural Magic DeepSparse 1.5 - Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream", Lower Results Are Better "a",979.468,978.8914 "b",822.6656,849.0378 "SQLite 3.41.2 - Threads / Copies: 1", Lower Results Are Better "a",29.464,31.189 "b",88.392,88.778 "SQLite 3.41.2 - Threads / Copies: 2", Lower Results Are Better "a",98.537,148.393 "b",168.593,171.435 "SQLite 3.41.2 - Threads / Copies: 4", Lower Results Are Better "a",108.344,143.315 "b",172.54,173.549 "Z3 Theorem Prover 4.12.1 - SMT File: 1.smt2", Lower Results Are Better "a",44.023,43.922 "b",43.595,43.243 "Z3 Theorem Prover 4.12.1 - SMT File: 2.smt2", Lower Results Are Better "a",130.83,131.052 "b",131.355,131.454 "Timed Godot Game Engine Compilation 4.0 - Time To Compile", Lower Results Are Better "a",1372.89,1372.318 "b",1397.722,1371.809 "Timed LLVM Compilation 16.0 - Build System: Ninja", Lower Results Are Better "a",2887.333,2896.842 "b",2903.932,2913.823 "Timed LLVM Compilation 16.0 - Build System: Unix Makefiles", Lower Results Are Better "a",2921.916,3013.14 "b",2937.52,2922.301 "Build2 0.15 - Time To Compile", Lower Results Are Better "a",554.793,557.079 "b",565.391,573.827 "Opus Codec Encoding 1.4 - WAV To Opus Encode", Lower Results Are Better "a",35.497,35.294 "b",35.365,35.487