extra tests2 Tests for a future article. AMD EPYC 9124 16-Core testing with a Supermicro H13SSW (1.1 BIOS) and astdrmfb on AlmaLinux 9.2 via the Phoronix Test Suite. a: Processor: 2 x AMD EPYC 9254 24-Core @ 2.90GHz (48 Cores / 96 Threads), Motherboard: Supermicro H13DSH (1.5 BIOS), Memory: 24 x 32 GB DDR5-4800MT/s Samsung M321R4GA3BB6-CQKET, Disk: 2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07, Graphics: astdrmfb OS: AlmaLinux 9.2, Kernel: 5.14.0-284.25.1.el9_2.x86_64 (x86_64), Compiler: GCC 11.3.1 20221121, File-System: ext4, Screen Resolution: 1024x768 b: Processor: 2 x AMD EPYC 9254 24-Core @ 2.90GHz (48 Cores / 96 Threads), Motherboard: Supermicro H13DSH (1.5 BIOS), Memory: 24 x 32 GB DDR5-4800MT/s Samsung M321R4GA3BB6-CQKET, Disk: 2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07, Graphics: astdrmfb OS: AlmaLinux 9.2, Kernel: 5.14.0-284.25.1.el9_2.x86_64 (x86_64), Compiler: GCC 11.3.1 20221121, File-System: ext4, Screen Resolution: 1024x768 c: Processor: 2 x AMD EPYC 9254 24-Core @ 2.90GHz (48 Cores / 96 Threads), Motherboard: Supermicro H13DSH (1.5 BIOS), Memory: 24 x 32 GB DDR5-4800MT/s Samsung M321R4GA3BB6-CQKET, Disk: 2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07, Graphics: astdrmfb OS: AlmaLinux 9.2, Kernel: 5.14.0-284.25.1.el9_2.x86_64 (x86_64), Compiler: GCC 11.3.1 20221121, File-System: ext4, Screen Resolution: 1024x768 d: Processor: AMD EPYC 9124 16-Core @ 3.00GHz (16 Cores / 32 Threads), Motherboard: Supermicro H13SSW (1.1 BIOS), Memory: 12 x 64 GB DDR5-4800MT/s HMCG94MEBRA123N, Disk: 2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07, Graphics: astdrmfb OS: AlmaLinux 9.2, Kernel: 5.14.0-284.25.1.el9_2.x86_64 (x86_64), Compiler: GCC 11.3.1 20221121, File-System: ext4, Screen Resolution: 1024x768 e: Processor: AMD EPYC 9124 16-Core @ 3.00GHz (16 Cores / 32 Threads), Motherboard: Supermicro H13SSW (1.1 BIOS), Memory: 12 x 64 GB DDR5-4800MT/s HMCG94MEBRA123N, Disk: 2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07, Graphics: astdrmfb OS: AlmaLinux 9.2, Kernel: 5.14.0-284.25.1.el9_2.x86_64 (x86_64), Compiler: GCC 11.3.1 20221121, File-System: ext4, Screen Resolution: 1024x768 f: Processor: AMD EPYC 9124 16-Core @ 3.00GHz (16 Cores / 32 Threads), Motherboard: Supermicro H13SSW (1.1 BIOS), Memory: 12 x 64 GB DDR5-4800MT/s HMCG94MEBRA123N, Disk: 2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07, Graphics: astdrmfb OS: AlmaLinux 9.2, Kernel: 5.14.0-284.25.1.el9_2.x86_64 (x86_64), Compiler: GCC 11.3.1 20221121, File-System: ext4, Screen Resolution: 1024x768 g: Processor: AMD EPYC 9124 16-Core @ 3.00GHz (16 Cores / 32 Threads), Motherboard: Supermicro H13SSW (1.1 BIOS), Memory: 12 x 64 GB DDR5-4800MT/s HMCG94MEBRA123N, Disk: 2 x 1920GB SAMSUNG MZQL21T9HCJR-00A07, Graphics: astdrmfb OS: AlmaLinux 9.2, Kernel: 5.14.0-284.25.1.el9_2.x86_64 (x86_64), Compiler: GCC 11.3.1 20221121, File-System: ext4, Screen Resolution: 1024x768 Apache Cassandra 4.1.3 Test: Writes Op/s > Higher Is Better a . 248095 |============================================================= b . 256661 |================================================================ c . 270480 |=================================================================== d . 197866 |================================================= e . 195798 |================================================= f . 196287 |================================================= g . 197092 |================================================= Apache Hadoop 3.3.6 Operation: Open - Threads: 50 - Files: 100000 Ops per sec > Higher Is Better a . 460829 |===================================================== b . 469484 |====================================================== c . 401606 |=============================================== d . 578035 |=================================================================== e . 552486 |================================================================ f . 578035 |=================================================================== g . 546448 |=============================================================== Apache Hadoop 3.3.6 Operation: Open - Threads: 100 - Files: 100000 Ops per sec > Higher Is Better a . 420168 |===================================================== b . 404858 |=================================================== c . 403226 |=================================================== d . 529101 |=================================================================== e . 294985 |===================================== f . 523560 |================================================================== g . 460829 |========================================================== Apache Hadoop 3.3.6 Operation: Open - Threads: 50 - Files: 1000000 Ops per sec > Higher Is Better a . 1126126 |============================================================= b . 1020408 |======================================================= c . 683995 |===================================== d . 278319 |=============== e . 251004 |============== f . 1221001 |================================================================== g . 654022 |=================================== Apache Hadoop 3.3.6 Operation: Create - Threads: 50 - Files: 100000 Ops per sec > Higher Is Better a . 43649 |================================================= b . 41288 |============================================== c . 43937 |================================================= d . 58617 |================================================================== e . 58617 |================================================================== f . 58343 |================================================================= g . 60680 |==================================================================== Apache Hadoop 3.3.6 Operation: Delete - Threads: 50 - Files: 100000 Ops per sec > Higher Is Better a . 91075 |=========================================================== b . 73801 |================================================ c . 90580 |========================================================== d . 101010 |================================================================= e . 100604 |================================================================= f . 96993 |=============================================================== g . 103950 |=================================================================== Apache Hadoop 3.3.6 Operation: Open - Threads: 100 - Files: 1000000 Ops per sec > Higher Is Better a . 215332 |=========== b . 173822 |========= c . 185874 |========= d . 1248439 |=============================================================== e . 1204819 |============================================================= f . 1303781 |================================================================== g . 1107420 |======================================================== Apache Hadoop 3.3.6 Operation: Rename - Threads: 50 - Files: 100000 Ops per sec > Higher Is Better a . 70522 |========================================================== b . 73046 |============================================================ c . 77101 |================================================================ d . 82372 |==================================================================== e . 82237 |==================================================================== f . 81633 |=================================================================== g . 82237 |==================================================================== Apache Hadoop 3.3.6 Operation: Create - Threads: 100 - Files: 100000 Ops per sec > Higher Is Better a . 40733 |=============================================== b . 37425 |=========================================== c . 35075 |======================================== d . 57971 |================================================================== e . 58824 |=================================================================== f . 59382 |==================================================================== g . 58928 |=================================================================== Apache Hadoop 3.3.6 Operation: Create - Threads: 50 - Files: 1000000 Ops per sec > Higher Is Better a . 53665 |================================================== b . 52119 |================================================= c . 52260 |================================================= d . 72134 |=================================================================== e . 70897 |================================================================== f . 69920 |================================================================= g . 72706 |==================================================================== Apache Hadoop 3.3.6 Operation: Delete - Threads: 100 - Files: 100000 Ops per sec > Higher Is Better a . 87566 |======================================================== b . 90827 |========================================================== c . 73475 |=============================================== d . 105708 |=================================================================== e . 98039 |============================================================== f . 99404 |=============================================================== g . 102564 |================================================================= Apache Hadoop 3.3.6 Operation: Delete - Threads: 50 - Files: 1000000 Ops per sec > Higher Is Better a . 98932 |========================================================== b . 97314 |========================================================== c . 90147 |===================================================== d . 111012 |================================================================== e . 113327 |=================================================================== f . 111198 |================================================================== g . 110828 |================================================================== Apache Hadoop 3.3.6 Operation: Rename - Threads: 100 - Files: 100000 Ops per sec > Higher Is Better a . 75529 |============================================================= b . 69348 |======================================================== c . 67159 |====================================================== d . 82102 |=================================================================== e . 83822 |==================================================================== f . 79491 |================================================================ g . 80386 |================================================================= Apache Hadoop 3.3.6 Operation: Rename - Threads: 50 - Files: 1000000 Ops per sec > Higher Is Better a . 73239 |=========================================================== b . 71679 |========================================================= c . 74638 |============================================================ d . 83921 |=================================================================== e . 84041 |=================================================================== f . 82501 |================================================================== g . 84810 |==================================================================== Apache Hadoop 3.3.6 Operation: Create - Threads: 100 - Files: 1000000 Ops per sec > Higher Is Better a . 46145 |============================================ b . 44437 |========================================== c . 44001 |========================================== d . 71296 |==================================================================== e . 70057 |=================================================================== f . 70537 |=================================================================== g . 70922 |==================================================================== Apache Hadoop 3.3.6 Operation: Delete - Threads: 100 - Files: 1000000 Ops per sec > Higher Is Better a . 90114 |===================================================== b . 86715 |=================================================== c . 97031 |========================================================= d . 112613 |================================================================== e . 113225 |=================================================================== f . 110803 |================================================================= g . 113895 |=================================================================== Apache Hadoop 3.3.6 Operation: Rename - Threads: 100 - Files: 1000000 Ops per sec > Higher Is Better a . 73078 |========================================================== b . 72129 |========================================================= c . 66827 |===================================================== d . 81208 |================================================================ e . 84360 |=================================================================== f . 85815 |==================================================================== g . 85763 |==================================================================== Apache Hadoop 3.3.6 Operation: File Status - Threads: 50 - Files: 100000 Ops per sec > Higher Is Better a . 529101 |========================================= b . 862069 |=================================================================== c . 657895 |=================================================== d . 632911 |================================================= e . 389105 |============================== f . 709220 |======================================================= g . 561798 |============================================ Apache Hadoop 3.3.6 Operation: File Status - Threads: 100 - Files: 100000 Ops per sec > Higher Is Better a . 515464 |=============================================== b . 458716 |========================================== c . 729927 |=================================================================== d . 591716 |====================================================== e . 613497 |======================================================== f . 478469 |============================================ g . 487805 |============================================= Apache Hadoop 3.3.6 Operation: File Status - Threads: 50 - Files: 1000000 Ops per sec > Higher Is Better a . 2173913 |================================================================== b . 1941748 |=========================================================== c . 284252 |========= d . 1818182 |======================================================= e . 320924 |========== f . 1795332 |======================================================= g . 2036660 |============================================================== Apache Hadoop 3.3.6 Operation: File Status - Threads: 100 - Files: 1000000 Ops per sec > Higher Is Better a . 1886792 |============================================================= b . 161970 |===== c . 1893939 |============================================================= d . 600601 |=================== e . 235627 |======== f . 1964637 |=============================================================== g . 2049180 |================================================================== Blender 3.6 Blend File: BMW27 - Compute: CPU-Only Seconds < Lower Is Better a . 26.20 |========================= b . 26.24 |========================= c . 26.12 |========================= d . 72.00 |==================================================================== e . 71.44 |=================================================================== f . 71.96 |==================================================================== g . 72.01 |==================================================================== Blender 3.6 Blend File: Classroom - Compute: CPU-Only Seconds < Lower Is Better a . 66.42 |======================== b . 66.64 |======================== c . 66.72 |======================== d . 182.99 |=================================================================== e . 182.56 |=================================================================== f . 181.70 |================================================================== g . 183.29 |=================================================================== Blender 3.6 Blend File: Fishy Cat - Compute: CPU-Only Seconds < Lower Is Better a . 33.22 |========================= b . 33.17 |========================= c . 33.03 |========================= d . 90.03 |==================================================================== e . 90.31 |==================================================================== f . 90.26 |==================================================================== g . 90.63 |==================================================================== Blender 3.6 Blend File: Barbershop - Compute: CPU-Only Seconds < Lower Is Better a . 254.88 |========================= b . 255.30 |========================= c . 254.72 |========================= d . 670.87 |=================================================================== e . 670.64 |=================================================================== f . 667.87 |=================================================================== g . 669.09 |=================================================================== Blender 3.6 Blend File: Pabellon Barcelona - Compute: CPU-Only Seconds < Lower Is Better a . 80.54 |======================== b . 80.76 |======================== c . 80.41 |======================== d . 224.15 |=================================================================== e . 224.10 |=================================================================== f . 223.95 |=================================================================== g . 224.12 |=================================================================== BRL-CAD 7.36 VGR Performance Metric VGR Performance Metric > Higher Is Better a . 772162 |=================================================================== b . 768517 |=================================================================== c . 762529 |================================================================== d . 298064 |========================== e . 296125 |========================== f . 295603 |========================== g . 295522 |========================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 240 Seconds < Lower Is Better d . 1.657 |==================================================================== e . 1.654 |==================================================================== f . 1.657 |==================================================================== g . 1.648 |==================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 1200 Seconds < Lower Is Better d . 38.11 |==================================================================== e . 38.07 |==================================================================== f . 38.02 |==================================================================== g . 37.95 |==================================================================== easyWave r34 Input: e2Asean Grid + BengkuluSept2007 Source - Time: 2400 Seconds < Lower Is Better d . 98.98 |==================================================================== e . 99.42 |==================================================================== f . 97.99 |=================================================================== g . 97.53 |=================================================================== Embree 4.1 Binary: Pathtracer - Model: Crown Frames Per Second > Higher Is Better a . 54.90 |=================================================================== b . 55.39 |==================================================================== c . 55.40 |==================================================================== d . 21.48 |========================== e . 21.44 |========================== f . 21.59 |=========================== g . 21.58 |========================== Embree 4.1 Binary: Pathtracer ISPC - Model: Crown Frames Per Second > Higher Is Better a . 56.09 |=================================================================== b . 56.46 |==================================================================== c . 56.81 |==================================================================== d . 22.59 |=========================== e . 22.57 |=========================== f . 22.66 |=========================== g . 22.77 |=========================== Embree 4.1 Binary: Pathtracer - Model: Asian Dragon Frames Per Second > Higher Is Better a . 60.14 |==================================================================== b . 59.91 |==================================================================== c . 59.79 |==================================================================== d . 24.69 |============================ e . 24.73 |============================ f . 24.70 |============================ g . 24.82 |============================ Embree 4.1 Binary: Pathtracer - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 53.57 |==================================================================== b . 53.81 |==================================================================== c . 53.69 |==================================================================== d . 22.26 |============================ e . 22.16 |============================ f . 22.15 |============================ g . 22.19 |============================ Embree 4.1 Binary: Pathtracer ISPC - Model: Asian Dragon Frames Per Second > Higher Is Better a . 67.34 |==================================================================== b . 67.20 |==================================================================== c . 67.50 |==================================================================== d . 28.36 |============================= e . 28.31 |============================= f . 28.32 |============================= g . 28.48 |============================= Embree 4.1 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 56.49 |=================================================================== b . 56.69 |==================================================================== c . 56.93 |==================================================================== d . 23.87 |============================= e . 23.94 |============================= f . 23.94 |============================= g . 23.88 |============================= Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Frames Per Second > Higher Is Better d . 24.85 |==================================================================== e . 24.83 |==================================================================== f . 24.89 |==================================================================== g . 24.96 |==================================================================== Embree 4.3 Binary: Pathtracer - Model: Asian Dragon Obj Frames Per Second > Higher Is Better d . 22.35 |==================================================================== e . 22.29 |==================================================================== f . 22.27 |==================================================================== g . 22.26 |==================================================================== Embree 4.3 Binary: Pathtracer - Model: Crown Frames Per Second > Higher Is Better d . 21.89 |==================================================================== e . 21.99 |==================================================================== f . 21.77 |=================================================================== g . 21.83 |==================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Frames Per Second > Higher Is Better d . 27.74 |==================================================================== e . 27.83 |==================================================================== f . 27.83 |==================================================================== g . 27.91 |==================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Frames Per Second > Higher Is Better d . 23.35 |=================================================================== e . 23.53 |=================================================================== f . 23.50 |=================================================================== g . 23.71 |==================================================================== Embree 4.3 Binary: Pathtracer ISPC - Model: Crown Frames Per Second > Higher Is Better d . 22.39 |==================================================================== e . 22.34 |==================================================================== f . 22.44 |==================================================================== g . 22.42 |==================================================================== Intel Open Image Denoise 2.0 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 1.83 |===================================================================== b . 1.83 |===================================================================== c . 1.83 |===================================================================== d . 0.72 |=========================== e . 0.72 |=========================== f . 0.72 |=========================== g . 0.72 |=========================== Intel Open Image Denoise 2.0 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 1.84 |===================================================================== b . 1.84 |===================================================================== c . 1.82 |==================================================================== d . 0.72 |=========================== e . 0.72 |=========================== f . 0.72 |=========================== g . 0.72 |=========================== Intel Open Image Denoise 2.0 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only Images / Sec > Higher Is Better a . 0.86 |==================================================================== b . 0.86 |==================================================================== c . 0.87 |===================================================================== d . 0.34 |=========================== e . 0.34 |=========================== f . 0.34 |=========================== g . 0.34 |=========================== Intel Open Image Denoise 2.1 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better d . 0.72 |===================================================================== e . 0.72 |===================================================================== f . 0.72 |===================================================================== g . 0.72 |===================================================================== Intel Open Image Denoise 2.1 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better d . 0.72 |===================================================================== e . 0.72 |===================================================================== f . 0.72 |===================================================================== g . 0.72 |===================================================================== Intel Open Image Denoise 2.1 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only Images / Sec > Higher Is Better d . 0.34 |===================================================================== e . 0.34 |===================================================================== f . 0.34 |===================================================================== g . 0.34 |===================================================================== Kripke 1.2.6 Throughput FoM > Higher Is Better d . 240994500 |================================================================ e . 236243900 |=============================================================== f . 236591000 |=============================================================== g . 237175700 |=============================================================== Liquid-DSP 1.6 Threads: 1 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 39499000 |================================================================= b . 39486000 |================================================================= c . 39453000 |================================================================= d . 35228000 |========================================================== e . 35315000 |========================================================== f . 35271000 |========================================================== g . 35236000 |========================================================== Liquid-DSP 1.6 Threads: 1 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 59401000 |================================================================= b . 59296000 |================================================================= c . 57519000 |=============================================================== d . 52665000 |========================================================== e . 52827000 |========================================================== f . 52879000 |========================================================== g . 52854000 |========================================================== Liquid-DSP 1.6 Threads: 2 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 77181000 |================================================================= b . 77019000 |================================================================= c . 76924000 |================================================================= d . 67054000 |======================================================== e . 68846000 |========================================================== f . 68861000 |========================================================== g . 68678000 |========================================================== Liquid-DSP 1.6 Threads: 2 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 117490000 |=============================================================== b . 114010000 |============================================================== c . 118550000 |================================================================ d . 105650000 |========================================================= e . 105480000 |========================================================= f . 105740000 |========================================================= g . 104800000 |========================================================= Liquid-DSP 1.6 Threads: 4 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 153850000 |================================================================ b . 153690000 |================================================================ c . 153670000 |================================================================ d . 138600000 |========================================================== e . 138620000 |========================================================== f . 138580000 |========================================================== g . 138460000 |========================================================== Liquid-DSP 1.6 Threads: 4 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 196220000 |================================================================ b . 196590000 |================================================================ c . 194510000 |=============================================================== d . 188930000 |============================================================== e . 191230000 |============================================================== f . 189880000 |============================================================== g . 190750000 |============================================================== Liquid-DSP 1.6 Threads: 8 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 307540000 |================================================================ b . 305110000 |=============================================================== c . 306760000 |================================================================ d . 278030000 |========================================================== e . 277780000 |========================================================== f . 276390000 |========================================================== g . 277410000 |========================================================== Liquid-DSP 1.6 Threads: 8 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 369430000 |================================================================ b . 366930000 |================================================================ c . 366990000 |================================================================ d . 363310000 |=============================================================== e . 357990000 |============================================================== f . 350450000 |============================================================= g . 357810000 |============================================================== Liquid-DSP 1.6 Threads: 1 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 13909000 |================================================================ b . 14021000 |================================================================ c . 14225000 |================================================================= d . 12683000 |========================================================== e . 12366000 |========================================================= f . 12681000 |========================================================== g . 12256000 |======================================================== Liquid-DSP 1.6 Threads: 16 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 594230000 |=============================================================== b . 602470000 |================================================================ c . 603650000 |================================================================ d . 545360000 |========================================================== e . 545140000 |========================================================== f . 545020000 |========================================================== g . 543050000 |========================================================== Liquid-DSP 1.6 Threads: 16 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 699740000 |================================================================ b . 692760000 |=============================================================== c . 674930000 |============================================================== d . 689150000 |=============================================================== e . 692920000 |=============================================================== f . 693340000 |=============================================================== g . 682070000 |============================================================== Liquid-DSP 1.6 Threads: 2 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 27901000 |================================================================ b . 27736000 |================================================================ c . 28227000 |================================================================= d . 24627000 |========================================================= e . 25207000 |========================================================== f . 25199000 |========================================================== g . 22727000 |==================================================== Liquid-DSP 1.6 Threads: 32 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 1183500000 |=============================================================== b . 1190300000 |=============================================================== c . 1184800000 |=============================================================== d . 1047100000 |======================================================= e . 1046600000 |======================================================= f . 1041900000 |======================================================= g . 1047100000 |======================================================= Liquid-DSP 1.6 Threads: 32 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 1192100000 |============================================================ b . 1214200000 |============================================================= c . 1254800000 |=============================================================== d . 1035000000 |==================================================== e . 1032000000 |==================================================== f . 1024600000 |=================================================== g . 1033400000 |==================================================== Liquid-DSP 1.6 Threads: 4 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 52911000 |============================================================== b . 55588000 |================================================================= c . 55165000 |================================================================= d . 50258000 |=========================================================== e . 50380000 |=========================================================== f . 49977000 |========================================================== g . 49556000 |========================================================== Liquid-DSP 1.6 Threads: 64 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 2207700000 |=============================================================== b . 2212100000 |=============================================================== c . 2206800000 |=============================================================== d . 1059500000 |============================== e . 1057500000 |============================== f . 1057100000 |============================== g . 1056200000 |============================== Liquid-DSP 1.6 Threads: 64 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 1994400000 |=============================================================== b . 2001900000 |=============================================================== c . 2010300000 |=============================================================== d . 1093300000 |================================== e . 1095400000 |================================== f . 1094600000 |================================== g . 1099300000 |================================== Liquid-DSP 1.6 Threads: 8 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 109870000 |================================================================ b . 108080000 |=============================================================== c . 109140000 |================================================================ d . 99594000 |========================================================== e . 97005000 |========================================================= f . 99441000 |========================================================== g . 100170000 |========================================================== Liquid-DSP 1.6 Threads: 96 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 3005800000 |=============================================================== b . 2995400000 |=============================================================== c . 2999800000 |=============================================================== d . 1065200000 |====================== e . 1065100000 |====================== f . 1065300000 |====================== g . 1065700000 |====================== Liquid-DSP 1.6 Threads: 96 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 2559800000 |=============================================================== b . 2571100000 |=============================================================== c . 2564900000 |=============================================================== d . 1120800000 |=========================== e . 1117800000 |=========================== f . 1120500000 |=========================== g . 1118200000 |=========================== Liquid-DSP 1.6 Threads: 16 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 216080000 |================================================================ b . 216150000 |================================================================ c . 214910000 |================================================================ d . 193850000 |========================================================= e . 196040000 |========================================================== f . 194500000 |========================================================== g . 194670000 |========================================================== Liquid-DSP 1.6 Threads: 32 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 425810000 |=============================================================== b . 429620000 |================================================================ c . 424400000 |=============================================================== d . 273760000 |========================================= e . 273480000 |========================================= f . 273390000 |========================================= g . 274070000 |========================================= Liquid-DSP 1.6 Threads: 64 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 622560000 |================================================================ b . 610950000 |=============================================================== c . 622630000 |================================================================ d . 282920000 |============================= e . 281830000 |============================= f . 283030000 |============================= g . 281730000 |============================= Liquid-DSP 1.6 Threads: 96 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 711640000 |=============================================================== b . 718140000 |================================================================ c . 715030000 |================================================================ d . 286250000 |========================== e . 285880000 |========================= f . 285920000 |========================= g . 286530000 |========================== nekRS 23.0 Input: Kershaw flops/rank > Higher Is Better a . 11106900000 |============================================================= b . 11240300000 |============================================================== c . 10826700000 |============================================================ d . 10318900000 |========================================================= e . 10264000000 |========================================================= f . 9976450000 |======================================================= g . 10500600000 |========================================================== nekRS 23.0 Input: TurboPipe Periodic flops/rank > Higher Is Better a . 6767710000 |====================================================== b . 6757360000 |===================================================== c . 6754170000 |===================================================== d . 7934570000 |=============================================================== e . 7931010000 |=============================================================== f . 7955790000 |=============================================================== g . 7964910000 |=============================================================== Neural Magic DeepSparse 1.5 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 39.50 |==================================================================== b . 39.47 |==================================================================== c . 39.45 |==================================================================== d . 13.07 |======================= e . 12.94 |====================== f . 13.09 |======================= g . 13.07 |======================= Neural Magic DeepSparse 1.5 Model: NLP Document Classification, oBERT base uncased on IMDB - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 605.04 |=================================================================== b . 605.73 |=================================================================== c . 605.92 |=================================================================== d . 606.10 |=================================================================== e . 607.91 |=================================================================== f . 607.82 |=================================================================== g . 607.16 |=================================================================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 1417.07 |================================================================== b . 1403.07 |================================================================= c . 1418.90 |================================================================== d . 508.09 |======================== e . 511.41 |======================== f . 508.21 |======================== g . 509.14 |======================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 16.91 |=================================================================== b . 17.07 |==================================================================== c . 16.89 |=================================================================== d . 15.72 |=============================================================== e . 15.62 |============================================================== f . 15.72 |=============================================================== g . 15.69 |=============================================================== Neural Magic DeepSparse 1.5 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 672.46 |=================================================================== b . 672.37 |=================================================================== c . 671.26 |=================================================================== d . 257.27 |========================== e . 257.89 |========================== f . 257.50 |========================== g . 257.28 |========================== Neural Magic DeepSparse 1.5 Model: NLP Sentiment Analysis, 80% Pruned Quantized BERT Base Uncased - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 35.63 |==================================================================== b . 35.64 |==================================================================== c . 35.68 |==================================================================== d . 31.05 |=========================================================== e . 30.99 |=========================================================== f . 31.03 |=========================================================== g . 31.06 |=========================================================== Neural Magic DeepSparse 1.5 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 201.39 |=================================================================== b . 201.25 |=================================================================== c . 201.54 |=================================================================== d . 71.14 |======================== e . 71.27 |======================== f . 71.04 |======================== g . 70.93 |======================== Neural Magic DeepSparse 1.5 Model: NLP Question Answering, BERT base uncased SQuaD 12layer Pruned90 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 118.75 |=================================================================== b . 118.95 |=================================================================== c . 118.78 |=================================================================== d . 112.25 |=============================================================== e . 112.06 |=============================================================== f . 112.41 |=============================================================== g . 112.48 |=============================================================== Neural Magic DeepSparse 1.5 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 485.67 |=================================================================== b . 488.13 |=================================================================== c . 489.11 |=================================================================== d . 162.85 |====================== e . 163.14 |====================== f . 162.93 |====================== g . 162.99 |====================== Neural Magic DeepSparse 1.5 Model: ResNet-50, Baseline - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 49.37 |==================================================================== b . 49.11 |==================================================================== c . 49.02 |==================================================================== d . 49.09 |==================================================================== e . 49.01 |==================================================================== f . 49.07 |==================================================================== g . 49.03 |==================================================================== Neural Magic DeepSparse 1.5 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 5137.01 |================================================================== b . 5138.83 |================================================================== c . 5153.66 |================================================================== d . 1599.21 |==================== e . 1599.15 |==================== f . 1600.53 |==================== g . 1602.52 |===================== Neural Magic DeepSparse 1.5 Model: ResNet-50, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 4.6508 |============================================================== b . 4.6476 |============================================================== c . 4.6348 |============================================================== d . 4.9960 |=================================================================== e . 4.9859 |=================================================================== f . 4.9877 |=================================================================== g . 4.9787 |=================================================================== Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 215.64 |=================================================================== b . 215.93 |=================================================================== c . 215.65 |=================================================================== d . 71.92 |====================== e . 71.91 |====================== f . 71.94 |====================== g . 71.90 |====================== Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 111.01 |=================================================================== b . 110.92 |=================================================================== c . 111.03 |=================================================================== d . 111.11 |=================================================================== e . 111.09 |=================================================================== f . 110.89 |=================================================================== g . 110.98 |=================================================================== Neural Magic DeepSparse 1.5 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 49.33 |==================================================================== b . 49.17 |==================================================================== c . 47.15 |================================================================= d . 16.16 |====================== e . 16.14 |====================== f . 16.13 |====================== g . 16.07 |====================== Neural Magic DeepSparse 1.5 Model: BERT-Large, NLP Question Answering - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 485.72 |================================================================ b . 487.36 |================================================================ c . 507.48 |=================================================================== d . 493.60 |================================================================= e . 494.26 |================================================================= f . 494.22 |================================================================= g . 495.60 |================================================================= Neural Magic DeepSparse 1.5 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 489.12 |=================================================================== b . 489.45 |=================================================================== c . 487.05 |=================================================================== d . 163.56 |====================== e . 162.93 |====================== f . 162.90 |====================== g . 163.23 |====================== Neural Magic DeepSparse 1.5 Model: CV Classification, ResNet-50 ImageNet - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 49.01 |==================================================================== b . 48.97 |==================================================================== c . 49.21 |==================================================================== d . 48.87 |==================================================================== e . 49.06 |==================================================================== f . 49.07 |==================================================================== g . 48.98 |==================================================================== Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 218.15 |=================================================================== b . 219.53 |=================================================================== c . 218.52 |=================================================================== d . 72.46 |====================== e . 72.66 |====================== f . 72.57 |====================== g . 72.69 |====================== Neural Magic DeepSparse 1.5 Model: CV Detection, YOLOv5s COCO, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 109.80 |=================================================================== b . 109.23 |================================================================== c . 109.58 |=================================================================== d . 110.11 |=================================================================== e . 109.97 |=================================================================== f . 110.00 |=================================================================== g . 109.90 |=================================================================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 322.25 |=================================================================== b . 321.18 |=================================================================== c . 321.51 |=================================================================== d . 108.91 |======================= e . 109.09 |======================= f . 109.09 |======================= g . 109.22 |======================= Neural Magic DeepSparse 1.5 Model: NLP Text Classification, DistilBERT mnli - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 74.32 |==================================================================== b . 74.56 |==================================================================== c . 74.50 |==================================================================== d . 73.31 |=================================================================== e . 73.26 |=================================================================== f . 73.22 |=================================================================== g . 73.19 |=================================================================== Neural Magic DeepSparse 1.5 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 68.60 |==================================================================== b . 68.66 |==================================================================== c . 68.63 |==================================================================== d . 24.48 |======================== e . 24.47 |======================== f . 24.52 |======================== g . 24.46 |======================== Neural Magic DeepSparse 1.5 Model: CV Segmentation, 90% Pruned YOLACT Pruned - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 347.66 |=================================================================== b . 347.22 |=================================================================== c . 347.37 |=================================================================== d . 325.88 |=============================================================== e . 325.74 |=============================================================== f . 324.96 |=============================================================== g . 325.51 |=============================================================== Neural Magic DeepSparse 1.5 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 718.92 |=================================================================== b . 717.97 |=================================================================== c . 716.14 |=================================================================== d . 240.55 |====================== e . 240.23 |====================== f . 240.16 |====================== g . 239.52 |====================== Neural Magic DeepSparse 1.5 Model: BERT-Large, NLP Question Answering, Sparse INT8 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 33.34 |==================================================================== b . 33.38 |==================================================================== c . 33.46 |==================================================================== d . 33.22 |==================================================================== e . 33.26 |==================================================================== f . 33.28 |==================================================================== g . 33.37 |==================================================================== Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 158.92 |================================================================= b . 159.06 |================================================================= c . 164.61 |=================================================================== d . 55.61 |======================= e . 55.46 |======================= f . 55.54 |======================= g . 55.43 |======================= Neural Magic DeepSparse 1.5 Model: NLP Text Classification, BERT base uncased SST2 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 150.59 |=================================================================== b . 150.61 |=================================================================== c . 145.26 |================================================================= d . 143.76 |================================================================ e . 144.10 |================================================================ f . 143.69 |================================================================ g . 144.11 |================================================================ Neural Magic DeepSparse 1.5 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream items/sec > Higher Is Better a . 39.44 |==================================================================== b . 39.45 |==================================================================== c . 39.42 |==================================================================== d . 13.13 |======================= e . 13.12 |======================= f . 13.09 |======================= g . 13.06 |======================= Neural Magic DeepSparse 1.5 Model: NLP Token Classification, BERT base uncased conll2003 - Scenario: Asynchronous Multi-Stream ms/batch < Lower Is Better a . 605.76 |=================================================================== b . 606.67 |=================================================================== c . 605.88 |=================================================================== d . 606.58 |=================================================================== e . 606.76 |=================================================================== f . 606.79 |=================================================================== g . 608.72 |=================================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU ms < Lower Is Better d . 2.13332 |================================================================== e . 2.12570 |================================================================== f . 2.13062 |================================================================== g . 2.11813 |================================================================== oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better d . 1.55824 |================================================================= e . 1.54911 |================================================================= f . 1.57282 |================================================================== g . 1.55118 |================================================================= oneDNN 3.3 Harness: Convolution Batch Shapes Auto - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better d . 1.33789 |================================================================== e . 1.33861 |================================================================== f . 1.34183 |================================================================== g . 1.33564 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: f32 - Engine: CPU ms < Lower Is Better d . 3.81576 |================================================================== e . 3.84421 |================================================================== f . 3.81823 |================================================================== g . 3.82381 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better d . 0.628236 |================================================================ e . 0.633975 |================================================================= f . 0.630325 |================================================================= g . 0.629108 |================================================================= oneDNN 3.3 Harness: Deconvolution Batch shapes_1d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better d . 3.05991 |================================================================== e . 3.06370 |================================================================== f . 3.05674 |================================================================== g . 3.05458 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: f32 - Engine: CPU ms < Lower Is Better d . 3.37782 |================================================================== e . 3.38436 |================================================================== f . 3.37956 |================================================================== g . 3.38156 |================================================================== oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better d . 0.847805 |================================================================= e . 0.844434 |================================================================= f . 0.850691 |================================================================= g . 0.843492 |================================================================ oneDNN 3.3 Harness: Deconvolution Batch shapes_3d - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better d . 1.91374 |================================================================== e . 1.91781 |================================================================== f . 1.91422 |================================================================== g . 1.91274 |================================================================== oneDNN 3.3 Harness: IP Shapes 1D - Data Type: f32 - Engine: CPU ms < Lower Is Better d . 2.49408 |================================================================ e . 2.56522 |================================================================== f . 2.49714 |================================================================ g . 2.51441 |================================================================= oneDNN 3.3 Harness: IP Shapes 1D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better d . 0.652259 |================================================================ e . 0.657610 |================================================================= f . 0.653182 |================================================================= g . 0.647700 |================================================================ oneDNN 3.3 Harness: IP Shapes 1D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better d . 1.03749 |============================================================ e . 1.14432 |================================================================== f . 1.00136 |========================================================== g . 1.12723 |================================================================= oneDNN 3.3 Harness: IP Shapes 3D - Data Type: f32 - Engine: CPU ms < Lower Is Better d . 1.25758 |================================================================= e . 1.28043 |================================================================== f . 1.20653 |============================================================== g . 1.27918 |================================================================== oneDNN 3.3 Harness: IP Shapes 3D - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better d . 0.603950 |================================================================ e . 0.575794 |============================================================= f . 0.600834 |================================================================ g . 0.612320 |================================================================= oneDNN 3.3 Harness: IP Shapes 3D - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better d . 1.02875 |================================================================ e . 1.05425 |================================================================== f . 1.06144 |================================================================== g . 1.04567 |================================================================= oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU ms < Lower Is Better d . 1641.92 |================================================================== e . 1641.00 |================================================================== f . 1636.76 |================================================================== g . 1637.37 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better d . 1642.51 |================================================================== e . 1639.36 |================================================================== f . 1636.44 |================================================================== g . 1631.99 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Training - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better d . 1643.99 |================================================================== e . 1643.97 |================================================================== f . 1642.35 |================================================================== g . 1641.40 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU ms < Lower Is Better d . 838.52 |================================================================== e . 849.71 |=================================================================== f . 851.49 |=================================================================== g . 848.03 |=================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: u8s8f32 - Engine: CPU ms < Lower Is Better d . 849.16 |=================================================================== e . 851.66 |=================================================================== f . 849.34 |=================================================================== g . 837.60 |================================================================== oneDNN 3.3 Harness: Recurrent Neural Network Inference - Data Type: bf16bf16bf16 - Engine: CPU ms < Lower Is Better d . 847.38 |=================================================================== e . 841.08 |================================================================== f . 845.31 |=================================================================== g . 847.42 |=================================================================== OpenRadioss 2023.09.15 Model: Bumper Beam Seconds < Lower Is Better OpenRadioss 2023.09.15 Model: Chrysler Neon 1M Seconds < Lower Is Better OpenRadioss 2023.09.15 Model: Cell Phone Drop Test Seconds < Lower Is Better OpenRadioss 2023.09.15 Model: Bird Strike on Windshield Seconds < Lower Is Better OpenRadioss 2023.09.15 Model: Rubber O-Ring Seal Installation Seconds < Lower Is Better OpenRadioss 2023.09.15 Model: INIVOL and Fluid Structure Interaction Drop Container Seconds < Lower Is Better OpenVINO 2023.1 Model: Face Detection FP16 - Device: CPU FPS > Higher Is Better a . 30.41 |==================================================================== b . 30.44 |==================================================================== c . 30.43 |==================================================================== d . 10.47 |======================= e . 10.47 |======================= f . 10.48 |======================= g . 10.48 |======================= OpenVINO 2023.1 Model: Face Detection FP16 - Device: CPU ms < Lower Is Better a . 393.60 |=================================== b . 393.23 |=================================== c . 393.37 |=================================== d . 761.59 |=================================================================== e . 761.16 |=================================================================== f . 760.57 |=================================================================== g . 759.92 |=================================================================== OpenVINO 2023.1 Model: Person Detection FP16 - Device: CPU FPS > Higher Is Better a . 282.55 |=================================================================== b . 284.22 |=================================================================== c . 282.67 |=================================================================== d . 107.02 |========================= e . 107.27 |========================= f . 107.39 |========================= g . 107.04 |========================= OpenVINO 2023.1 Model: Person Detection FP16 - Device: CPU ms < Lower Is Better a . 42.44 |======================================= b . 42.20 |====================================== c . 42.43 |======================================= d . 74.71 |==================================================================== e . 74.50 |==================================================================== f . 74.43 |==================================================================== g . 74.71 |==================================================================== OpenVINO 2023.1 Model: Person Detection FP32 - Device: CPU FPS > Higher Is Better a . 283.97 |=================================================================== b . 284.99 |=================================================================== c . 284.31 |=================================================================== d . 106.90 |========================= e . 107.24 |========================= f . 106.76 |========================= g . 107.24 |========================= OpenVINO 2023.1 Model: Person Detection FP32 - Device: CPU ms < Lower Is Better a . 42.24 |====================================== b . 42.09 |====================================== c . 42.19 |====================================== d . 74.81 |==================================================================== e . 74.54 |==================================================================== f . 74.87 |==================================================================== g . 74.58 |==================================================================== OpenVINO 2023.1 Model: Vehicle Detection FP16 - Device: CPU FPS > Higher Is Better a . 2033.17 |================================================================== b . 2028.01 |================================================================== c . 2029.79 |================================================================== d . 797.64 |========================== e . 793.75 |========================== f . 791.74 |========================== g . 793.90 |========================== OpenVINO 2023.1 Model: Vehicle Detection FP16 - Device: CPU ms < Lower Is Better a . 5.89 |======================================== b . 5.91 |======================================== c . 5.90 |======================================== d . 10.01 |=================================================================== e . 10.06 |==================================================================== f . 10.09 |==================================================================== g . 10.06 |==================================================================== OpenVINO 2023.1 Model: Face Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 56.01 |==================================================================== b . 56.06 |==================================================================== c . 56.02 |==================================================================== d . 20.03 |======================== e . 20.00 |======================== f . 20.01 |======================== g . 20.05 |======================== OpenVINO 2023.1 Model: Face Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 213.94 |==================================== b . 213.62 |==================================== c . 213.79 |==================================== d . 398.52 |=================================================================== e . 398.91 |=================================================================== f . 399.24 |=================================================================== g . 398.13 |=================================================================== OpenVINO 2023.1 Model: Face Detection Retail FP16 - Device: CPU FPS > Higher Is Better a . 5882.91 |================================================================== b . 5836.27 |================================================================= c . 5840.53 |================================================================== d . 2564.78 |============================= e . 2562.54 |============================= f . 2539.97 |============================ g . 2557.66 |============================= OpenVINO 2023.1 Model: Face Detection Retail FP16 - Device: CPU ms < Lower Is Better a . 2.03 |============================================= b . 2.05 |============================================= c . 2.05 |============================================= d . 3.11 |==================================================================== e . 3.11 |==================================================================== f . 3.14 |===================================================================== g . 3.12 |===================================================================== OpenVINO 2023.1 Model: Road Segmentation ADAS FP16 - Device: CPU FPS > Higher Is Better a . 748.44 |================================================================== b . 750.49 |================================================================== c . 757.38 |=================================================================== d . 344.67 |============================== e . 342.81 |============================== f . 343.49 |============================== g . 341.36 |============================== OpenVINO 2023.1 Model: Road Segmentation ADAS FP16 - Device: CPU ms < Lower Is Better a . 16.02 |=============================================== b . 15.98 |============================================== c . 15.83 |============================================== d . 23.20 |=================================================================== e . 23.32 |==================================================================== f . 23.28 |==================================================================== g . 23.42 |==================================================================== OpenVINO 2023.1 Model: Vehicle Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 2873.24 |================================================================== b . 2880.58 |================================================================== c . 2881.14 |================================================================== d . 1175.67 |=========================== e . 1174.60 |=========================== f . 1180.85 |=========================== g . 1175.58 |=========================== OpenVINO 2023.1 Model: Vehicle Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 4.17 |========================================== b . 4.16 |========================================== c . 4.16 |========================================== d . 6.79 |===================================================================== e . 6.80 |===================================================================== f . 6.76 |===================================================================== g . 6.79 |===================================================================== OpenVINO 2023.1 Model: Weld Porosity Detection FP16 - Device: CPU FPS > Higher Is Better a . 2945.26 |================================================================= b . 2986.46 |================================================================== c . 2987.33 |================================================================== d . 1039.61 |======================= e . 1039.82 |======================= f . 1038.47 |======================= g . 1039.37 |======================= OpenVINO 2023.1 Model: Weld Porosity Detection FP16 - Device: CPU ms < Lower Is Better a . 16.26 |==================================================================== b . 16.02 |=================================================================== c . 16.02 |=================================================================== d . 15.36 |================================================================ e . 15.36 |================================================================ f . 15.38 |================================================================ g . 15.37 |================================================================ OpenVINO 2023.1 Model: Face Detection Retail FP16-INT8 - Device: CPU FPS > Higher Is Better a . 9837.58 |================================================================== b . 9849.07 |================================================================== c . 9845.27 |================================================================== d . 3540.88 |======================== e . 3544.18 |======================== f . 3548.78 |======================== g . 3533.64 |======================== OpenVINO 2023.1 Model: Face Detection Retail FP16-INT8 - Device: CPU ms < Lower Is Better a . 4.86 |===================================================================== b . 4.85 |===================================================================== c . 4.86 |===================================================================== d . 4.51 |================================================================ e . 4.51 |================================================================ f . 4.50 |================================================================ g . 4.52 |================================================================ OpenVINO 2023.1 Model: Road Segmentation ADAS FP16-INT8 - Device: CPU FPS > Higher Is Better a . 842.91 |================================================================== b . 854.51 |=================================================================== c . 849.30 |=================================================================== d . 370.57 |============================= e . 373.64 |============================= f . 369.26 |============================= g . 372.26 |============================= OpenVINO 2023.1 Model: Road Segmentation ADAS FP16-INT8 - Device: CPU ms < Lower Is Better a . 14.23 |============================================= b . 14.03 |============================================ c . 14.12 |============================================ d . 21.57 |==================================================================== e . 21.40 |=================================================================== f . 21.65 |==================================================================== g . 21.47 |=================================================================== OpenVINO 2023.1 Model: Machine Translation EN To DE FP16 - Device: CPU FPS > Higher Is Better a . 317.22 |=================================================================== b . 317.28 |=================================================================== c . 317.33 |=================================================================== d . 124.12 |========================== e . 123.61 |========================== f . 124.30 |========================== g . 123.41 |========================== OpenVINO 2023.1 Model: Machine Translation EN To DE FP16 - Device: CPU ms < Lower Is Better a . 37.80 |======================================== b . 37.79 |======================================== c . 37.79 |======================================== d . 64.41 |==================================================================== e . 64.68 |==================================================================== f . 64.31 |==================================================================== g . 64.77 |==================================================================== OpenVINO 2023.1 Model: Weld Porosity Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 5776.94 |================================================================== b . 5780.44 |================================================================== c . 5802.65 |================================================================== d . 2013.77 |======================= e . 2007.53 |======================= f . 2004.76 |======================= g . 2006.09 |======================= OpenVINO 2023.1 Model: Weld Porosity Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 8.28 |===================================================================== b . 8.27 |===================================================================== c . 8.24 |===================================================================== d . 7.93 |================================================================== e . 7.96 |================================================================== f . 7.97 |================================================================== g . 7.96 |================================================================== OpenVINO 2023.1 Model: Person Vehicle Bike Detection FP16 - Device: CPU FPS > Higher Is Better a . 2454.09 |================================================================== b . 2450.26 |================================================================== c . 2455.51 |================================================================== d . 1036.99 |============================ e . 1028.64 |============================ f . 1041.87 |============================ g . 1031.60 |============================ OpenVINO 2023.1 Model: Person Vehicle Bike Detection FP16 - Device: CPU ms < Lower Is Better a . 4.88 |=========================================== b . 4.89 |=========================================== c . 4.88 |=========================================== d . 7.70 |==================================================================== e . 7.77 |===================================================================== f . 7.67 |==================================================================== g . 7.74 |===================================================================== OpenVINO 2023.1 Model: Handwritten English Recognition FP16 - Device: CPU FPS > Higher Is Better a . 1560.03 |================================================================== b . 1546.02 |================================================================= c . 1551.63 |================================================================== d . 532.59 |======================= e . 530.99 |====================== f . 533.74 |======================= g . 538.01 |======================= OpenVINO 2023.1 Model: Handwritten English Recognition FP16 - Device: CPU ms < Lower Is Better a . 30.72 |=================================================================== b . 31.00 |==================================================================== c . 30.89 |==================================================================== d . 30.02 |================================================================== e . 30.10 |================================================================== f . 29.95 |================================================================== g . 29.72 |================================================================= OpenVINO 2023.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU FPS > Higher Is Better a . 86884.64 |================================================================= b . 87359.23 |================================================================= c . 86789.80 |================================================================= d . 32002.62 |======================== e . 32032.06 |======================== f . 31951.64 |======================== g . 32008.03 |======================== OpenVINO 2023.1 Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU ms < Lower Is Better a . 0.54 |===================================================================== b . 0.54 |===================================================================== c . 0.54 |===================================================================== d . 0.49 |=============================================================== e . 0.49 |=============================================================== f . 0.49 |=============================================================== g . 0.49 |=============================================================== OpenVINO 2023.1 Model: Handwritten English Recognition FP16-INT8 - Device: CPU FPS > Higher Is Better a . 1244.69 |================================================================== b . 1239.67 |================================================================== c . 1237.29 |================================================================== d . 395.66 |===================== e . 432.32 |======================= f . 431.94 |======================= g . 432.20 |======================= OpenVINO 2023.1 Model: Handwritten English Recognition FP16-INT8 - Device: CPU ms < Lower Is Better a . 38.50 |================================================================= b . 38.66 |================================================================= c . 38.75 |================================================================= d . 40.40 |==================================================================== e . 36.98 |============================================================== f . 37.01 |============================================================== g . 36.98 |============================================================== OpenVINO 2023.1 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU FPS > Higher Is Better a . 120606.38 |=============================================================== b . 120728.22 |=============================================================== c . 123484.28 |================================================================ d . 44958.07 |======================= e . 44933.27 |======================= f . 44968.43 |======================= g . 45097.99 |======================= OpenVINO 2023.1 Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU ms < Lower Is Better a . 0.34 |=================================================================== b . 0.34 |=================================================================== c . 0.34 |=================================================================== d . 0.35 |===================================================================== e . 0.35 |===================================================================== f . 0.35 |===================================================================== g . 0.35 |===================================================================== OpenVKL 2.0.0 Benchmark: vklBenchmarkCPU Scalar Items / Sec > Higher Is Better d . 191 |====================================================================== e . 190 |====================================================================== f . 191 |====================================================================== g . 191 |====================================================================== OpenVKL 2.0.0 Benchmark: vklBenchmarkCPU ISPC Items / Sec > Higher Is Better d . 487 |====================================================================== e . 487 |====================================================================== f . 488 |====================================================================== g . 489 |====================================================================== OSPRay 2.12 Benchmark: particle_volume/ao/real_time Items Per Second > Higher Is Better a . 15.98600 |================================================================= b . 15.97850 |================================================================= c . 15.98720 |================================================================= d . 5.57469 |======================= e . 5.54107 |======================= f . 5.57320 |======================= g . 5.57553 |======================= OSPRay 2.12 Benchmark: particle_volume/scivis/real_time Items Per Second > Higher Is Better a . 15.95280 |================================================================= b . 15.98880 |================================================================= c . 15.97780 |================================================================= d . 5.57001 |======================= e . 5.56353 |======================= f . 5.55581 |======================= g . 5.56539 |======================= OSPRay 2.12 Benchmark: particle_volume/pathtracer/real_time Items Per Second > Higher Is Better a . 215.10 |=================================================================== b . 214.07 |=================================================================== c . 214.14 |=================================================================== d . 151.91 |=============================================== e . 151.51 |=============================================== f . 151.78 |=============================================== g . 151.68 |=============================================== OSPRay 2.12 Benchmark: gravity_spheres_volume/dim_512/ao/real_time Items Per Second > Higher Is Better a . 14.23690 |================================================================= b . 14.17830 |================================================================= c . 14.13990 |================================================================= d . 5.60747 |========================== e . 5.62040 |========================== f . 5.61454 |========================== g . 5.62278 |========================== OSPRay 2.12 Benchmark: gravity_spheres_volume/dim_512/scivis/real_time Items Per Second > Higher Is Better a . 13.87390 |================================================================= b . 13.76660 |================================================================ c . 13.83170 |================================================================= d . 5.45329 |========================== e . 5.46153 |========================== f . 5.45227 |========================== g . 5.47725 |========================== OSPRay 2.12 Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time Items Per Second > Higher Is Better a . 16.34680 |================================================================ b . 16.43650 |================================================================= c . 16.53500 |================================================================= d . 6.58745 |========================== e . 6.58270 |========================== f . 6.59563 |========================== g . 6.60085 |========================== Remhos 1.0 Test: Sample Remap Example Seconds < Lower Is Better a . 16.35 |==================================== b . 16.79 |===================================== c . 16.24 |==================================== d . 30.76 |==================================================================== e . 30.85 |==================================================================== f . 30.73 |==================================================================== g . 30.75 |==================================================================== SPECFEM3D 4.0 Model: Mount St. Helens Seconds < Lower Is Better a . 11.02 |=========================== b . 11.32 |============================ c . 11.33 |============================ d . 26.74 |================================================================== e . 26.80 |================================================================== f . 26.87 |================================================================== g . 27.70 |==================================================================== SPECFEM3D 4.0 Model: Layered Halfspace Seconds < Lower Is Better a . 26.89 |========================== b . 28.65 |=========================== c . 27.49 |========================== d . 71.61 |==================================================================== e . 70.19 |=================================================================== f . 70.54 |=================================================================== g . 69.96 |================================================================== SPECFEM3D 4.0 Model: Tomographic Model Seconds < Lower Is Better a . 12.31 |============================== b . 12.10 |============================== c . 12.04 |============================== d . 27.33 |=================================================================== e . 27.46 |=================================================================== f . 26.97 |================================================================== g . 27.75 |==================================================================== SPECFEM3D 4.0 Model: Homogeneous Halfspace Seconds < Lower Is Better a . 15.11 |============================= b . 14.46 |============================ c . 14.81 |============================ d . 35.57 |==================================================================== e . 35.03 |=================================================================== f . 35.54 |==================================================================== g . 35.38 |==================================================================== SPECFEM3D 4.0 Model: Water-layered Halfspace Seconds < Lower Is Better a . 26.99 |============================= b . 29.46 |================================ c . 27.06 |============================= d . 62.44 |==================================================================== e . 62.33 |=================================================================== f . 61.28 |================================================================== g . 62.81 |==================================================================== SVT-AV1 1.7 Encoder Mode: Preset 4 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 5.203 |==================================================================== b . 5.149 |=================================================================== c . 5.049 |================================================================== d . 4.107 |====================================================== e . 4.114 |====================================================== f . 4.138 |====================================================== g . 4.143 |====================================================== SVT-AV1 1.7 Encoder Mode: Preset 8 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 90.81 |==================================================================== b . 91.32 |==================================================================== c . 90.42 |=================================================================== d . 66.99 |================================================== e . 67.72 |================================================== f . 67.39 |================================================== g . 67.81 |================================================== SVT-AV1 1.7 Encoder Mode: Preset 12 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 163.46 |================================================================== b . 166.38 |=================================================================== c . 163.06 |================================================================== d . 163.19 |================================================================== e . 162.61 |================================================================= f . 161.85 |================================================================= g . 160.32 |================================================================= SVT-AV1 1.7 Encoder Mode: Preset 13 - Input: Bosphorus 4K Frames Per Second > Higher Is Better a . 163.01 |================================================================== b . 166.69 |=================================================================== c . 161.50 |================================================================= d . 161.85 |================================================================= e . 162.05 |================================================================= f . 160.80 |================================================================= g . 161.32 |================================================================= SVT-AV1 1.7 Encoder Mode: Preset 4 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 12.48 |=================================================================== b . 12.59 |==================================================================== c . 12.62 |==================================================================== d . 10.91 |=========================================================== e . 10.98 |=========================================================== f . 10.74 |========================================================== g . 11.02 |=========================================================== SVT-AV1 1.7 Encoder Mode: Preset 8 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 141.22 |================================================================== b . 138.34 |================================================================= c . 143.55 |=================================================================== d . 118.95 |======================================================== e . 119.31 |======================================================== f . 118.49 |======================================================= g . 118.48 |======================================================= SVT-AV1 1.7 Encoder Mode: Preset 12 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 422.99 |====================================================== b . 427.69 |====================================================== c . 431.90 |======================================================= d . 526.22 |=================================================================== e . 525.17 |=================================================================== f . 521.52 |================================================================== g . 528.53 |=================================================================== SVT-AV1 1.7 Encoder Mode: Preset 13 - Input: Bosphorus 1080p Frames Per Second > Higher Is Better a . 510.36 |========================================================= b . 542.61 |============================================================ c . 516.91 |========================================================= d . 604.99 |=================================================================== e . 597.01 |================================================================== f . 585.37 |================================================================= g . 586.75 |================================================================= TiDB Community Server 7.3 Test: oltp_read_write - Threads: 1 Queries Per Second > Higher Is Better a . 2540 |====================================================== b . 2510 |====================================================== c . 2485 |===================================================== e . 3209 |===================================================================== f . 3218 |===================================================================== g . 3195 |===================================================================== TiDB Community Server 7.3 Test: oltp_read_write - Threads: 16 Queries Per Second > Higher Is Better a . 38331 |==================================================================== b . 36950 |================================================================== c . 37368 |================================================================== d . 36480 |================================================================= e . 36784 |================================================================= f . 36125 |================================================================ g . 36088 |================================================================ TiDB Community Server 7.3 Test: oltp_read_write - Threads: 32 Queries Per Second > Higher Is Better a . 58974 |================================================================= b . 61520 |==================================================================== c . 59630 |================================================================== d . 46977 |==================================================== e . 46737 |==================================================== f . 47141 |==================================================== g . 46993 |==================================================== TiDB Community Server 7.3 Test: oltp_read_write - Threads: 64 Queries Per Second > Higher Is Better a . 79090 |=================================================================== b . 80183 |==================================================================== c . 78469 |=================================================================== d . 55334 |=============================================== e . 53893 |============================================== f . 54956 |=============================================== g . 55301 |=============================================== TiDB Community Server 7.3 Test: oltp_point_select - Threads: 1 Queries Per Second > Higher Is Better a . 4331 |================================================== b . 4405 |=================================================== c . 4471 |==================================================== d . 5898 |==================================================================== e . 5976 |===================================================================== f . 5954 |===================================================================== TiDB Community Server 7.3 Test: oltp_read_write - Threads: 128 Queries Per Second > Higher Is Better a . 85757 |================================================================= b . 89099 |==================================================================== d . 59727 |============================================== e . 60145 |============================================== f . 60310 |============================================== g . 59944 |============================================== TiDB Community Server 7.3 Test: oltp_update_index - Threads: 1 Queries Per Second > Higher Is Better a . 1212 |======================================================== c . 1189 |======================================================= d . 1479 |==================================================================== e . 1490 |===================================================================== f . 1483 |===================================================================== g . 1481 |===================================================================== TiDB Community Server 7.3 Test: oltp_point_select - Threads: 16 Queries Per Second > Higher Is Better b . 67515 |================================================================= c . 65406 |=============================================================== e . 70250 |==================================================================== f . 70105 |==================================================================== g . 69923 |==================================================================== TiDB Community Server 7.3 Test: oltp_point_select - Threads: 32 Queries Per Second > Higher Is Better a . 104627 |================================================================== b . 106180 |=================================================================== d . 98149 |============================================================== e . 96907 |============================================================= f . 97368 |============================================================= g . 96840 |============================================================= TiDB Community Server 7.3 Test: oltp_point_select - Threads: 64 Queries Per Second > Higher Is Better a . 127567 |================================================================= b . 130802 |=================================================================== d . 115675 |=========================================================== e . 118657 |============================================================= f . 119092 |============================================================= g . 118549 |============================================================= TiDB Community Server 7.3 Test: oltp_update_index - Threads: 16 Queries Per Second > Higher Is Better a . 12558 |=================================================================== c . 12681 |==================================================================== d . 12622 |==================================================================== e . 12567 |=================================================================== f . 12692 |==================================================================== g . 12627 |==================================================================== TiDB Community Server 7.3 Test: oltp_update_index - Threads: 32 Queries Per Second > Higher Is Better a . 18361 |==================================================================== b . 17817 |================================================================== c . 17565 |================================================================= d . 17612 |================================================================= e . 17117 |=============================================================== g . 17135 |=============================================================== TiDB Community Server 7.3 Test: oltp_update_index - Threads: 64 Queries Per Second > Higher Is Better b . 24371 |==================================================================== c . 23324 |================================================================= d . 21108 |=========================================================== e . 21271 |=========================================================== f . 21067 |=========================================================== TiDB Community Server 7.3 Test: oltp_point_select - Threads: 128 Queries Per Second > Higher Is Better a . 159242 |=================================================================== b . 159728 |=================================================================== c . 149962 |=============================================================== d . 129492 |====================================================== e . 129904 |====================================================== f . 130389 |======================================================= TiDB Community Server 7.3 Test: oltp_update_index - Threads: 128 Queries Per Second > Higher Is Better a . 27087 |=================================================================== b . 27464 |==================================================================== c . 26546 |================================================================== e . 24611 |============================================================= f . 24830 |============================================================= g . 24574 |============================================================= TiDB Community Server 7.3 Test: oltp_update_non_index - Threads: 1 Queries Per Second > Higher Is Better a . 1328 |====================================================== b . 1312 |===================================================== c . 1381 |======================================================== d . 1693 |==================================================================== e . 1708 |===================================================================== f . 1697 |===================================================================== g . 1705 |===================================================================== TiDB Community Server 7.3 Test: oltp_update_non_index - Threads: 16 Queries Per Second > Higher Is Better a . 18095 |================================================================== b . 18068 |================================================================== d . 18563 |=================================================================== e . 18557 |=================================================================== g . 18735 |==================================================================== TiDB Community Server 7.3 Test: oltp_update_non_index - Threads: 32 Queries Per Second > Higher Is Better a . 28735 |==================================================================== b . 28914 |==================================================================== d . 26273 |============================================================== e . 26285 |============================================================== f . 26695 |=============================================================== TiDB Community Server 7.3 Test: oltp_update_non_index - Threads: 64 Queries Per Second > Higher Is Better a . 41281 |==================================================================== b . 39759 |================================================================= c . 39106 |================================================================ d . 34224 |======================================================== e . 33881 |======================================================== f . 34470 |========================================================= g . 34107 |======================================================== TiDB Community Server 7.3 Test: oltp_update_non_index - Threads: 128 Queries Per Second > Higher Is Better a . 51105 |================================================================== c . 52865 |==================================================================== e . 42138 |====================================================== f . 41424 |===================================================== g . 41695 |====================================================== Timed Linux Kernel Compilation 6.1 Build: defconfig Seconds < Lower Is Better a . 27.35 |================================== b . 27.24 |================================== c . 27.41 |================================== d . 55.17 |==================================================================== e . 55.09 |==================================================================== f . 55.15 |==================================================================== g . 55.17 |==================================================================== Timed Linux Kernel Compilation 6.1 Build: allmodconfig Seconds < Lower Is Better