ff

Tests for a future article. 2 x Intel Xeon Max 9480 testing with a Supermicro X13DEM v1.10 (1.3 BIOS) and ASPEED on Fedora Linux 38 via the Phoronix Test Suite.

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ff Tests for a future article. 2 x Intel Xeon Max 9480 testing with a Supermicro X13DEM v1.10 (1.3 BIOS) and ASPEED on Fedora Linux 38 via the Phoronix Test Suite. a: Processor: 2 x Intel Xeon Max 9480 @ 3.50GHz (112 Cores / 224 Threads), Motherboard: Supermicro X13DEM v1.10 (1.3 BIOS), Chipset: Intel Device 1bce, Memory: 512GB, Disk: 2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007, Graphics: ASPEED, Monitor: VE228, Network: 2 x Broadcom BCM57508 NetXtreme-E 10Gb/25Gb/40Gb/50Gb/100Gb/200Gb OS: Fedora Linux 38, Kernel: 6.2.15-300.fc38.x86_64 (x86_64), Compiler: GCC 13.1.1 20230511 + Clang 16.0.3 + LLVM 16.0.3, File-System: xfs, Screen Resolution: 1920x1080 b: Processor: 2 x Intel Xeon Max 9480 @ 3.50GHz (112 Cores / 224 Threads), Motherboard: Supermicro X13DEM v1.10 (1.3 BIOS), Chipset: Intel Device 1bce, Memory: 512GB, Disk: 2 x 1920GB SAMSUNG MZWLJ1T9HBJR-00007, Graphics: ASPEED, Monitor: VE228, Network: 2 x Broadcom BCM57508 NetXtreme-E 10Gb/25Gb/40Gb/50Gb/100Gb/200Gb OS: Fedora Linux 38, Kernel: 6.2.15-300.fc38.x86_64 (x86_64), Compiler: GCC 13.1.1 20230511 + Clang 16.0.3 + LLVM 16.0.3, File-System: xfs, Screen Resolution: 1920x1080 Cpuminer-Opt 23.5 Algorithm: Ringcoin kH/s > Higher Is Better a . 1521.29 |====== b . 17510.00 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 160.38 |===================================================== b . 201.74 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 156.61 |=================================================================== b . 125.23 |====================================================== OpenVINO 2023.2.dev Model: Vehicle Detection FP16 - Device: CPU FPS > Higher Is Better a . 2528.20 |================================================================== b . 2154.43 |======================================================== OpenVINO 2023.2.dev Model: Vehicle Detection FP16 - Device: CPU ms < Lower Is Better a . 14.59 |========================================================== b . 17.12 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 69.57 |=========================================================== b . 79.94 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 125.63 |========================================================== b . 143.95 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 295.49 |=========================================================== b . 336.54 |=================================================================== OSPRay Studio 0.13 Camera: 2 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 66307 |==================================================================== b . 58605 |============================================================ CloverLeaf 1.3 Input: clover_bm64_short Seconds < Lower Is Better a . 69.07 |==================================================================== b . 61.86 |============================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 143.89 |============================================================ b . 159.64 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 72.13 |============================================================= b . 79.77 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 80.66 |==================================================================== b . 72.99 |============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 66.99 |============================================================== b . 73.97 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 189.42 |=================================================================== b . 173.05 |============================================================= OSPRay Studio 0.13 Camera: 2 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 1856 |===================================================================== b . 1697 |=============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 74.45 |============================================================== b . 81.43 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 333.31 |=================================================================== b . 306.55 |============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 362.60 |=================================================================== b . 333.95 |============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 318.07 |============================================================== b . 345.08 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 178.39 |=================================================================== b . 165.20 |============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 156.91 |============================================================== b . 168.99 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 118.07 |============================================================== b . 127.05 |=================================================================== OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU ms < Lower Is Better a . 0.58 |===================================================================== b . 0.54 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 113.21 |=================================================================== b . 105.72 |=============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 131.84 |=============================================================== b . 140.67 |=================================================================== OSPRay Studio 0.13 Camera: 2 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 32908 |================================================================ b . 35051 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 162.59 |=================================================================== b . 152.70 |=============================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 152.23 |=================================================================== b . 143.88 |=============================================================== OSPRay Studio 0.13 Camera: 1 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 13423 |==================================================================== b . 12752 |================================================================= OpenVINO 2023.2.dev Model: Person Detection FP16 - Device: CPU FPS > Higher Is Better a . 461.84 |================================================================ b . 485.89 |=================================================================== OpenVINO 2023.2.dev Model: Person Detection FP16 - Device: CPU ms < Lower Is Better a . 79.98 |==================================================================== b . 76.05 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 85.71 |================================================================= b . 90.12 |==================================================================== OpenVINO 2023.2.dev Model: Machine Translation EN To DE FP16 - Device: CPU ms < Lower Is Better a . 134.38 |================================================================ b . 141.13 |=================================================================== OpenVINO 2023.2.dev Model: Machine Translation EN To DE FP16 - Device: CPU FPS > Higher Is Better a . 275.10 |=================================================================== b . 261.98 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 108.79 |=================================================================== b . 103.74 |================================================================ OSPRay Studio 0.13 Camera: 1 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 1672 |================================================================== b . 1753 |===================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 81.61 |==================================================================== b . 77.94 |================================================================= OSPRay Studio 0.13 Camera: 3 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 16130 |================================================================= b . 16884 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 153.01 |================================================================ b . 160.13 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 77.54 |==================================================================== b . 74.12 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 281.35 |=================================================================== b . 268.92 |================================================================ Cpuminer-Opt 23.5 Algorithm: Deepcoin kH/s > Higher Is Better a . 24960 |==================================================================== b . 23870 |================================================================= Cpuminer-Opt 23.5 Algorithm: scrypt kH/s > Higher Is Better a . 864.21 |=================================================================== b . 826.56 |================================================================ QMCPACK 3.17.1 Input: O_ae_pyscf_UHF Total Execution Time - Seconds < Lower Is Better a . 313.48 |=================================================================== b . 300.34 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 112.18 |=================================================================== b . 107.58 |================================================================ OSPRay Studio 0.13 Camera: 3 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 539 |=================================================================== b . 562 |====================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 344.02 |================================================================ b . 358.69 |=================================================================== OSPRay Studio 0.13 Camera: 3 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 7954 |================================================================== b . 8287 |===================================================================== QMCPACK 3.17.1 Input: FeCO6_b3lyp_gms Total Execution Time - Seconds < Lower Is Better a . 150.81 |================================================================ b . 157.11 |=================================================================== CloverLeaf 1.3 Input: clover_bm Seconds < Lower Is Better a . 38.11 |==================================================================== b . 36.59 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 166.29 |=================================================================== b . 159.72 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 127.50 |================================================================ b . 132.46 |=================================================================== OSPRay Studio 0.13 Camera: 1 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 59552 |==================================================================== b . 57371 |================================================================== OSPRay Studio 0.13 Camera: 1 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 6558 |=================================================================== b . 6797 |===================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 139.87 |================================================================= b . 144.93 |=================================================================== QMCPACK 3.17.1 Input: H4_ae Total Execution Time - Seconds < Lower Is Better a . 17.03 |================================================================== b . 17.62 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 180.52 |=================================================================== b . 174.89 |================================================================= OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16 - Device: CPU ms < Lower Is Better a . 32.21 |================================================================== b . 33.15 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: float-long - X Y Z: 256 GFLOP/s > Higher Is Better a . 172.22 |================================================================= b . 177.20 |=================================================================== OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16 - Device: CPU FPS > Higher Is Better a . 1146.17 |================================================================== b . 1114.41 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 314.76 |=================================================================== b . 307.20 |================================================================= CloverLeaf 1.3 Input: clover_bm16 Seconds < Lower Is Better a . 540.77 |================================================================= b . 553.98 |=================================================================== OSPRay Studio 0.13 Camera: 3 - Resolution: 4K - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 1995 |=================================================================== b . 2043 |===================================================================== OSPRay Studio 0.13 Camera: 2 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 461 |==================================================================== b . 472 |====================================================================== QMCPACK 3.17.1 Input: LiH_ae_MSD Total Execution Time - Seconds < Lower Is Better a . 118.27 |================================================================= b . 121.00 |=================================================================== Cpuminer-Opt 23.5 Algorithm: Garlicoin kH/s > Higher Is Better a . 21770 |==================================================================== b . 21290 |=================================================================== OSPRay Studio 0.13 Camera: 1 - Resolution: 1080p - Samples Per Pixel: 1 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 435 |===================================================================== b . 444 |====================================================================== OSPRay Studio 0.13 Camera: 1 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 32679 |==================================================================== b . 32018 |=================================================================== OpenVINO 2023.2.dev Model: Person Detection FP32 - Device: CPU FPS > Higher Is Better a . 432.58 |================================================================== b . 441.39 |=================================================================== OpenVINO 2023.2.dev Model: Person Detection FP32 - Device: CPU ms < Lower Is Better a . 85.38 |==================================================================== b . 83.70 |=================================================================== OpenVINO 2023.2.dev Model: Vehicle Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 5009.99 |================================================================== b . 4915.16 |================================================================= Cpuminer-Opt 23.5 Algorithm: LBC, LBRY Credits kH/s > Higher Is Better a . 44560 |=================================================================== b . 45400 |==================================================================== OpenVINO 2023.2.dev Model: Vehicle Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 22.32 |=================================================================== b . 22.74 |==================================================================== OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16 - Device: CPU FPS > Higher Is Better a . 76079.37 |================================================================ b . 77488.89 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 81.86 |=================================================================== b . 83.29 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 144.99 |=================================================================== b . 142.49 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 82.77 |=================================================================== b . 84.17 |==================================================================== OpenVINO 2023.2.dev Model: Face Detection Retail FP16-INT8 - Device: CPU FPS > Higher Is Better a . 16074.67 |================================================================= b . 15816.99 |================================================================ Cpuminer-Opt 23.5 Algorithm: Quad SHA-256, Pyrite kH/s > Higher Is Better a . 205870 |=================================================================== b . 202620 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 108.82 |=================================================================== b . 107.15 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 178.87 |================================================================== b . 181.55 |=================================================================== Cpuminer-Opt 23.5 Algorithm: Triple SHA-256, Onecoin kH/s > Higher Is Better a . 293830 |=================================================================== b . 289590 |================================================================== OpenVINO 2023.2.dev Model: Face Detection Retail FP16 - Device: CPU FPS > Higher Is Better a . 11244.03 |================================================================= b . 11084.65 |================================================================ OpenVINO 2023.2.dev Model: Face Detection Retail FP16 - Device: CPU ms < Lower Is Better a . 9.94 |=================================================================== b . 10.08 |==================================================================== OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU FPS > Higher Is Better a . 113019.68 |================================================================ b . 111459.35 |=============================================================== OpenVINO 2023.2.dev Model: Face Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 324.39 |=================================================================== b . 320.18 |================================================================== OpenVINO 2023.2.dev Model: Face Detection Retail FP16-INT8 - Device: CPU ms < Lower Is Better a . 6.93 |==================================================================== b . 7.02 |===================================================================== OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16 - Device: CPU FPS > Higher Is Better a . 16277.65 |================================================================= b . 16076.48 |================================================================ QuantLib 1.32 Configuration: Multi-Threaded MFLOPS > Higher Is Better a . 254351.8 |================================================================= b . 251353.6 |================================================================ OpenVINO 2023.2.dev Model: Face Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 344.53 |================================================================== b . 348.63 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 107.22 |=================================================================== b . 105.96 |================================================================== OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16 - Device: CPU ms < Lower Is Better a . 6.77 |==================================================================== b . 6.85 |===================================================================== Cpuminer-Opt 23.5 Algorithm: Blake-2 S kH/s > Higher Is Better a . 385610 |=================================================================== b . 381310 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 93.10 |==================================================================== b . 92.14 |=================================================================== OSPRay Studio 0.13 Camera: 3 - Resolution: 4K - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 36981 |=================================================================== b . 37359 |==================================================================== Timed Gem5 Compilation 23.0.1 Time To Compile Seconds < Lower Is Better a . 271.37 |=================================================================== b . 268.69 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 164.45 |=================================================================== b . 162.93 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 139.00 |=================================================================== b . 137.71 |================================================================== OpenVINO 2023.2.dev Model: Face Detection FP16 - Device: CPU FPS > Higher Is Better a . 111.23 |=================================================================== b . 110.31 |================================================================== OpenVINO 2023.2.dev Model: Person Vehicle Bike Detection FP16 - Device: CPU ms < Lower Is Better a . 18.30 |=================================================================== b . 18.45 |==================================================================== OpenVINO 2023.2.dev Model: Face Detection FP16 - Device: CPU ms < Lower Is Better a . 331.96 |================================================================== b . 334.67 |=================================================================== OSPRay Studio 0.13 Camera: 3 - Resolution: 4K - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 68616 |=================================================================== b . 69170 |==================================================================== OpenVINO 2023.2.dev Model: Person Vehicle Bike Detection FP16 - Device: CPU FPS > Higher Is Better a . 6106.89 |================================================================== b . 6061.06 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 128 GFLOP/s > Higher Is Better a . 141.03 |=================================================================== b . 139.99 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: c2c - Backend: Stock - Precision: double-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 70.91 |==================================================================== b . 71.43 |==================================================================== Cpuminer-Opt 23.5 Algorithm: Myriad-Groestl kH/s > Higher Is Better a . 34040 |==================================================================== b . 33810 |==================================================================== OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16-INT8 - Device: CPU FPS > Higher Is Better a . 1497.11 |================================================================== b . 1487.31 |================================================================== OpenVINO 2023.2.dev Model: Road Segmentation ADAS FP16-INT8 - Device: CPU ms < Lower Is Better a . 74.75 |==================================================================== b . 75.20 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 107.37 |=================================================================== b . 106.78 |=================================================================== QMCPACK 3.17.1 Input: simple-H2O Total Execution Time - Seconds < Lower Is Better a . 36.37 |==================================================================== b . 36.56 |==================================================================== Cpuminer-Opt 23.5 Algorithm: Magi kH/s > Higher Is Better a . 1943.59 |================================================================== b . 1953.44 |================================================================== OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16-INT8 - Device: CPU FPS > Higher Is Better a . 25636.44 |================================================================= b . 25515.81 |================================================================= OSPRay Studio 0.13 Camera: 2 - Resolution: 1080p - Samples Per Pixel: 16 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 7000 |===================================================================== b . 6968 |===================================================================== OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16-INT8 - Device: CPU FPS > Higher Is Better a . 2378.91 |================================================================== b . 2387.67 |================================================================== OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16-INT8 - Device: CPU ms < Lower Is Better a . 47.04 |==================================================================== b . 46.87 |==================================================================== OpenVINO 2023.2.dev Model: Weld Porosity Detection FP16-INT8 - Device: CPU ms < Lower Is Better a . 4.24 |===================================================================== b . 4.25 |===================================================================== Cpuminer-Opt 23.5 Algorithm: Skeincoin kH/s > Higher Is Better a . 98770 |==================================================================== b . 98550 |==================================================================== OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16 - Device: CPU FPS > Higher Is Better a . 3570.40 |================================================================== b . 3563.39 |================================================================== OpenVINO 2023.2.dev Model: Handwritten English Recognition FP16 - Device: CPU ms < Lower Is Better a . 31.34 |==================================================================== b . 31.40 |==================================================================== QuantLib 1.32 Configuration: Single-Threaded MFLOPS > Higher Is Better a . 3374.9 |=================================================================== b . 3380.5 |=================================================================== QMCPACK 3.17.1 Input: Li2_STO_ae Total Execution Time - Seconds < Lower Is Better a . 135.63 |=================================================================== b . 135.73 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.4 Test: r2c - Backend: Stock - Precision: float-long - X Y Z: 512 GFLOP/s > Higher Is Better a . 282.97 |=================================================================== b . 283.08 |=================================================================== OpenVINO 2023.2.dev Model: Age Gender Recognition Retail 0013 FP16-INT8 - Device: CPU ms < Lower Is Better a . 0.34 |===================================================================== b . 0.34 |===================================================================== OSPRay Studio 0.13 Camera: 2 - Resolution: 1080p - Samples Per Pixel: 32 - Renderer: Path Tracer - Acceleration: CPU ms < Lower Is Better a . 14526 |==================================================================== b . 14526 |====================================================================