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.

Compare your own system(s) to this result file with the Phoronix Test Suite by running the command: phoronix-test-suite benchmark 2310228-NE-EXTRATEST37

Jump To Table - Results

Statistics

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

Graph Settings

Force Line Graphs Where Applicable
Convert To Scalar Where Applicable
Prefer Vertical Bar Graphs

Additional Graphs

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

Multi-Way Comparison

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

Table

Show Detailed System Result Table

Run Management

Only show results where is faster than

Only show results matching title/arguments (delimit multiple options with a comma):

Do not show results matching title/arguments (delimit multiple options with a comma):

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 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 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 |==================================================================== 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 |=============================================================== 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 |============================= 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 |================================================================= 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 |=========================== 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 |========================== 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 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 |========================== 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 |====================================================== 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 |=================================================================== 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 |=================================================================== 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 |===================================================================== 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 |================================================================== Kripke 1.2.6 Throughput FoM > Higher Is Better d . 240994500 |================================================================ e . 236243900 |=============================================================== f . 236591000 |=============================================================== g . 237175700 |=============================================================== 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 4.3 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 |==================================================================== 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 |====================================================================== 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 |=================================================================== 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 |=====================================================================

extra tests2