xeon auggy

Tests for a future article. 2 x Intel Xeon Platinum 8380 testing with a Intel M50CYP2SB2U (SE5C6200.86B.0022.D08.2103221623 BIOS) and ASPEED on Ubuntu 22.10 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 2308065-NE-XEONAUGGY78
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August 06 2023
  3 Hours, 24 Minutes
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xeon auggy Tests for a future article. 2 x Intel Xeon Platinum 8380 testing with a Intel M50CYP2SB2U (SE5C6200.86B.0022.D08.2103221623 BIOS) and ASPEED on Ubuntu 22.10 via the Phoronix Test Suite. a: Processor: 2 x Intel Xeon Platinum 8380 @ 3.40GHz (80 Cores / 160 Threads), Motherboard: Intel M50CYP2SB2U (SE5C6200.86B.0022.D08.2103221623 BIOS), Chipset: Intel Ice Lake IEH, Memory: 512GB, Disk: 7682GB INTEL SSDPF2KX076TZ, Graphics: ASPEED, Monitor: VE228, Network: 2 x Intel X710 for 10GBASE-T + 2 x Intel E810-C for QSFP OS: Ubuntu 22.10, Kernel: 6.2.0-rc5-phx-dodt (x86_64), Desktop: GNOME Shell 43.0, Display Server: X Server 1.21.1.3, Vulkan: 1.3.224, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1920x1080 b: Processor: 2 x Intel Xeon Platinum 8380 @ 3.40GHz (80 Cores / 160 Threads), Motherboard: Intel M50CYP2SB2U (SE5C6200.86B.0022.D08.2103221623 BIOS), Chipset: Intel Ice Lake IEH, Memory: 512GB, Disk: 7682GB INTEL SSDPF2KX076TZ, Graphics: ASPEED, Monitor: VE228, Network: 2 x Intel X710 for 10GBASE-T + 2 x Intel E810-C for QSFP OS: Ubuntu 22.10, Kernel: 6.2.0-rc5-phx-dodt (x86_64), Desktop: GNOME Shell 43.0, Display Server: X Server 1.21.1.3, Vulkan: 1.3.224, Compiler: GCC 12.2.0, File-System: ext4, Screen Resolution: 1920x1080 Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200 Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200 Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500 Apache IoTDB 1.1.2 Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200 Apache IoTDB 1.1.2 Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500 Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200 Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500 Dragonflydb 1.6.2 Clients Per Thread: 10 - Set To Get Ratio: 1:5 Dragonflydb 1.6.2 Clients Per Thread: 20 - Set To Get Ratio: 1:5 Dragonflydb 1.6.2 Clients Per Thread: 50 - Set To Get Ratio: 1:5 Dragonflydb 1.6.2 Clients Per Thread: 60 - Set To Get Ratio: 1:5 Dragonflydb 1.6.2 Clients Per Thread: 10 - Set To Get Ratio: 1:10 Dragonflydb 1.6.2 Clients Per Thread: 20 - Set To Get Ratio: 1:10 Dragonflydb 1.6.2 Clients Per Thread: 50 - Set To Get Ratio: 1:10 Dragonflydb 1.6.2 Clients Per Thread: 60 - Set To Get Ratio: 1:10 Dragonflydb 1.6.2 Clients Per Thread: 10 - Set To Get Ratio: 1:100 Dragonflydb 1.6.2 Clients Per Thread: 20 - Set To Get Ratio: 1:100 Dragonflydb 1.6.2 Clients Per Thread: 50 - Set To Get Ratio: 1:100 Dragonflydb 1.6.2 Clients Per Thread: 60 - Set To Get Ratio: 1:100 Stress-NG 0.15.10 Test: Pipe Bogo Ops/s > Higher Is Better a . 40500166.81 |=================================================== b . 49325396.97 |============================================================== Stress-NG 0.15.10 Test: Zlib Bogo Ops/s > Higher Is Better a . 6879.86 |================================================================== b . 6880.22 |================================================================== Stress-NG 0.15.10 Test: Cloning Bogo Ops/s > Higher Is Better a . 16195.03 |================================================================= b . 13172.81 |===================================================== Stress-NG 0.15.10 Test: Pthread Bogo Ops/s > Higher Is Better a . 92131.54 |================================================================= b . 90361.70 |================================================================ Stress-NG 0.15.10 Test: AVL Tree Bogo Ops/s > Higher Is Better a . 610.69 |=================================================================== b . 610.83 |=================================================================== Stress-NG 0.15.10 Test: Floating Point Bogo Ops/s > Higher Is Better a . 21134.81 |================================================================= b . 21133.02 |================================================================= Stress-NG 0.15.10 Test: Matrix 3D Math Bogo Ops/s > Higher Is Better a . 12743.81 |================================================================= b . 12742.70 |================================================================= Stress-NG 0.15.10 Test: Vector Shuffle Bogo Ops/s > Higher Is Better a . 48054.48 |================================================================= b . 48076.78 |================================================================= Stress-NG 0.15.10 Test: Wide Vector Math Bogo Ops/s > Higher Is Better a . 2195391.41 |=============================================================== b . 2196242.21 |=============================================================== Stress-NG 0.15.10 Test: Fused Multiply-Add Bogo Ops/s > Higher Is Better a . 181083180.47 |============================================================= b . 181314757.42 |============================================================= Stress-NG 0.15.10 Test: Vector Floating Point Bogo Ops/s > Higher Is Better a . 132479.08 |================================================================ b . 131100.25 |=============================================================== dav1d 1.2.1 Video Input: Chimera 1080p FPS > Higher Is Better a . 516.17 |=================================================================== b . 516.50 |=================================================================== dav1d 1.2.1 Video Input: Summer Nature 4K FPS > Higher Is Better a . 282.53 |=================================================================== b . 282.65 |=================================================================== dav1d 1.2.1 Video Input: Summer Nature 1080p FPS > Higher Is Better a . 699.97 |=================================================================== b . 699.09 |=================================================================== dav1d 1.2.1 Video Input: Chimera 1080p 10-bit FPS > Higher Is Better a . 476.82 |=================================================================== b . 476.77 |=================================================================== Embree 4.1 Binary: Pathtracer - Model: Crown Frames Per Second > Higher Is Better a . 72.04 |==================================================================== b . 70.79 |=================================================================== Embree 4.1 Binary: Pathtracer ISPC - Model: Crown Frames Per Second > Higher Is Better a . 87.93 |==================================================================== b . 87.93 |==================================================================== Embree 4.1 Binary: Pathtracer - Model: Asian Dragon Frames Per Second > Higher Is Better a . 85.24 |==================================================================== b . 85.13 |==================================================================== Embree 4.1 Binary: Pathtracer - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 76.96 |==================================================================== b . 77.26 |==================================================================== Embree 4.1 Binary: Pathtracer ISPC - Model: Asian Dragon Frames Per Second > Higher Is Better a . 104.41 |=================================================================== b . 104.55 |=================================================================== Embree 4.1 Binary: Pathtracer ISPC - Model: Asian Dragon Obj Frames Per Second > Higher Is Better a . 89.84 |==================================================================== b . 90.01 |==================================================================== VVenC 1.9 Video Input: Bosphorus 4K - Video Preset: Fast Frames Per Second > Higher Is Better a . 5.672 |=================================================================== b . 5.717 |==================================================================== VVenC 1.9 Video Input: Bosphorus 4K - Video Preset: Faster Frames Per Second > Higher Is Better a . 10.28 |=================================================================== b . 10.43 |==================================================================== VVenC 1.9 Video Input: Bosphorus 1080p - Video Preset: Fast Frames Per Second > Higher Is Better a . 15.71 |==================================================================== b . 15.72 |==================================================================== VVenC 1.9 Video Input: Bosphorus 1080p - Video Preset: Faster Frames Per Second > Higher Is Better a . 29.08 |==================================================================== b . 29.18 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 159.34 |=================================================================== b . 158.71 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 102.28 |=================================================================== b . 98.83 |================================================================= HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 199.10 |=================================================================== b . 199.33 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 222.22 |================================================================= b . 230.54 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 94.45 |==================================================================== b . 91.90 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 45.85 |=================================================================== b . 46.46 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 107.45 |=================================================================== b . 107.95 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 101.80 |================================================================= b . 104.35 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 156.22 |=================================================================== b . 148.18 |================================================================ HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 93.01 |==================================================================== b . 92.82 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: float - X Y Z: 128 GFLOP/s > Higher Is Better a . 185.45 |=================================================================== b . 182.03 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: float - X Y Z: 256 GFLOP/s > Higher Is Better a . 236.67 |=================================================================== b . 236.12 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 69.48 |==================================================================== b . 67.95 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 46.66 |==================================================================== b . 46.51 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: double - X Y Z: 128 GFLOP/s > Higher Is Better a . 117.01 |=================================================================== b . 116.84 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: double - X Y Z: 256 GFLOP/s > Higher Is Better a . 101.94 |=================================================================== b . 102.43 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 94.83 |==================================================================== b . 94.34 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 170.91 |=================================================================== b . 171.13 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: FFTW - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 49.44 |==================================================================== b . 48.72 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 93.33 |==================================================================== b . 92.26 |=================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: FFTW - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 90.57 |==================================================================== b . 90.24 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: float - X Y Z: 512 GFLOP/s > Higher Is Better a . 176.63 |=================================================================== b . 174.11 |================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: c2c - Backend: Stock - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 47.28 |==================================================================== b . 47.39 |==================================================================== HeFFTe - Highly Efficient FFT for Exascale 2.3 Test: r2c - Backend: Stock - Precision: double - X Y Z: 512 GFLOP/s > Higher Is Better a . 94.26 |==================================================================== b . 92.72 |=================================================================== libxsmm 2-1.17-3645 M N K: 128 GFLOPS/s > Higher Is Better a . 1055.3 |==================================== b . 1946.7 |=================================================================== libxsmm 2-1.17-3645 M N K: 256 GFLOPS/s > Higher Is Better a . 599.8 |==================================================================== b . 592.5 |=================================================================== libxsmm 2-1.17-3645 M N K: 32 GFLOPS/s > Higher Is Better a . 633.2 |=================================================================== b . 639.3 |==================================================================== libxsmm 2-1.17-3645 M N K: 64 GFLOPS/s > Higher Is Better a . 1219.9 |=================================================================== b . 1216.0 |=================================================================== Intel Open Image Denoise 2.0 Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 3.04 |===================================================================== b . 3.01 |==================================================================== Intel Open Image Denoise 2.0 Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only Images / Sec > Higher Is Better a . 3.05 |===================================================================== b . 3.03 |===================================================================== Intel Open Image Denoise 2.0 Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only Images / Sec > Higher Is Better a . 1.47 |===================================================================== b . 1.46 |===================================================================== OSPRay 2.12 Benchmark: particle_volume/ao/real_time Items Per Second > Higher Is Better a . 24.64 |==================================================================== b . 24.62 |==================================================================== OSPRay 2.12 Benchmark: particle_volume/scivis/real_time Items Per Second > Higher Is Better a . 24.36 |=================================================================== b . 24.78 |==================================================================== OSPRay 2.12 Benchmark: particle_volume/pathtracer/real_time Items Per Second > Higher Is Better a . 151.14 |=================================================================== b . 151.27 |=================================================================== OSPRay 2.12 Benchmark: gravity_spheres_volume/dim_512/ao/real_time Items Per Second > Higher Is Better a . 21.21 |==================================================================== b . 20.95 |=================================================================== OSPRay 2.12 Benchmark: gravity_spheres_volume/dim_512/scivis/real_time Items Per Second > Higher Is Better a . 20.81 |==================================================================== b . 20.48 |=================================================================== OSPRay 2.12 Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time Items Per Second > Higher Is Better a . 22.70 |==================================================================== b . 22.58 |==================================================================== srsRAN Project 23.5 Test: Downlink Processor Benchmark Mbps > Higher Is Better a . 556.5 |==================================================================== b . 556.8 |==================================================================== srsRAN Project 23.5 Test: PUSCH Processor Benchmark, Throughput Total Mbps > Higher Is Better a . 9800.5 |=================================================================== b . 9756.7 |=================================================================== srsRAN Project 23.5 Test: PUSCH Processor Benchmark, Throughput Thread Mbps > Higher Is Better a . 164.8 |==================================================================== b . 164.7 |==================================================================== QuantLib 1.30 MFLOPS > Higher Is Better a . 2622.9 |=================================================================== b . 2607.6 |=================================================================== Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200 point/sec > Higher Is Better a . 638644.35 |================================================================ b . 628202.55 |=============================================================== Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 point/sec > Higher Is Better a . 995259.68 |================================================================ b . 992909.69 |================================================================ Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200 point/sec > Higher Is Better a . 904320.60 |=============================================================== b . 920435.77 |================================================================ Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500 point/sec > Higher Is Better a . 1134736.54 |=============================================================== b . 1137612.61 |=============================================================== Apache IoTDB 1.1.2 Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200 point/sec > Higher Is Better a . 1199743.22 |=============================================================== b . 1141859.25 |============================================================ Apache IoTDB 1.1.2 Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500 point/sec > Higher Is Better a . 1343156.56 |============================================================== b . 1372429.58 |=============================================================== Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200 point/sec > Higher Is Better a . 34266143.85 |============================================================= b . 34807016.85 |============================================================== Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500 point/sec > Higher Is Better a . 39562245.22 |========================================================= b . 43021501.40 |============================================================== Liquid-DSP 1.6 Threads: 32 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 992540000 |================================================================ b . 993445000 |================================================================ Liquid-DSP 1.6 Threads: 32 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 1197700000 |=============================================================== b . 1185500000 |============================================================== Liquid-DSP 1.6 Threads: 64 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 1805000000 |============================================================== b . 1825450000 |=============================================================== Liquid-DSP 1.6 Threads: 64 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 2069200000 |=============================================================== b . 2076650000 |=============================================================== Liquid-DSP 1.6 Threads: 128 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 2961100000 |=============================================================== b . 2945150000 |=============================================================== Liquid-DSP 1.6 Threads: 128 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 2519200000 |=============================================================== b . 2426350000 |============================================================= Liquid-DSP 1.6 Threads: 160 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 3390700000 |=============================================================== b . 3381950000 |=============================================================== Liquid-DSP 1.6 Threads: 160 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 2602300000 |============================================================== b . 2636450000 |=============================================================== Liquid-DSP 1.6 Threads: 32 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 400730000 |================================================================ b . 396265000 |=============================================================== Liquid-DSP 1.6 Threads: 64 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 725840000 |================================================================ b . 730310000 |================================================================ Liquid-DSP 1.6 Threads: 128 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 949400000 |================================================================ b . 945190000 |================================================================ Liquid-DSP 1.6 Threads: 160 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 1013200000 |=============================================================== b . 1011200000 |=============================================================== Liquid-DSP 1.6 Threads: 1 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 32338000 |================================================================= b . 32267000 |================================================================= Liquid-DSP 1.6 Threads: 1 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 53918500 |================================================================= b . 53926500 |================================================================= Liquid-DSP 1.6 Threads: 1 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 13323000 |================================================================= b . 13291000 |================================================================= Liquid-DSP 1.6 Threads: 16 - Buffer Length: 256 - Filter Length: 32 samples/s > Higher Is Better a . 493660000 |=============================================================== b . 498410000 |================================================================ Liquid-DSP 1.6 Threads: 16 - Buffer Length: 256 - Filter Length: 57 samples/s > Higher Is Better a . 615105000 |=============================================================== b . 623535000 |================================================================ Liquid-DSP 1.6 Threads: 16 - Buffer Length: 256 - Filter Length: 512 samples/s > Higher Is Better a . 201615000 |================================================================ b . 198790000 |=============================================================== Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200 Average Latency < Lower Is Better a . 17.54 |================================================================== b . 18.04 |==================================================================== Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 Average Latency < Lower Is Better a . 35.99 |==================================================================== b . 36.16 |==================================================================== Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200 Average Latency < Lower Is Better a . 14.84 |==================================================================== b . 14.42 |================================================================== Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500 Average Latency < Lower Is Better a . 36.74 |==================================================================== b . 36.82 |==================================================================== Apache IoTDB 1.1.2 Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200 Average Latency < Lower Is Better a . 13.25 |================================================================ b . 14.12 |==================================================================== Apache IoTDB 1.1.2 Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500 Average Latency < Lower Is Better a . 33.38 |==================================================================== b . 32.75 |=================================================================== Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200 Average Latency < Lower Is Better a . 42.79 |==================================================================== b . 42.19 |=================================================================== Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500 Average Latency < Lower Is Better a . 109.40 |=================================================================== b . 96.18 |=========================================================== NCNN 20230517 Target: CPU - Model: mobilenet ms < Lower Is Better a . 16.06 |==================================================================== b . 15.90 |=================================================================== NCNN 20230517 Target: CPU-v2-v2 - Model: mobilenet-v2 ms < Lower Is Better a . 7.91 |===================================================================== b . 7.94 |===================================================================== NCNN 20230517 Target: CPU-v3-v3 - Model: mobilenet-v3 ms < Lower Is Better a . 8.71 |===================================================================== b . 8.77 |===================================================================== NCNN 20230517 Target: CPU - Model: shufflenet-v2 ms < Lower Is Better a . 9.82 |===================================================================== b . 9.75 |===================================================================== NCNN 20230517 Target: CPU - Model: mnasnet ms < Lower Is Better a . 7.61 |===================================================================== b . 7.43 |=================================================================== NCNN 20230517 Target: CPU - Model: efficientnet-b0 ms < Lower Is Better a . 11.48 |=================================================================== b . 11.64 |==================================================================== NCNN 20230517 Target: CPU - Model: blazeface ms < Lower Is Better a . 4.49 |=================================================================== b . 4.61 |===================================================================== NCNN 20230517 Target: CPU - Model: googlenet ms < Lower Is Better a . 17.06 |==================================================================== b . 16.72 |=================================================================== NCNN 20230517 Target: CPU - Model: vgg16 ms < Lower Is Better a . 26.27 |==================================================================== b . 26.19 |==================================================================== NCNN 20230517 Target: CPU - Model: resnet18 ms < Lower Is Better a . 10.31 |==================================================================== b . 9.63 |================================================================ NCNN 20230517 Target: CPU - Model: alexnet ms < Lower Is Better a . 5.65 |===================================================================== b . 5.44 |================================================================== NCNN 20230517 Target: CPU - Model: resnet50 ms < Lower Is Better a . 17.57 |================================================================== b . 18.15 |==================================================================== NCNN 20230517 Target: CPU - Model: yolov4-tiny ms < Lower Is Better a . 24.77 |==================================================================== b . 24.48 |=================================================================== NCNN 20230517 Target: CPU - Model: squeezenet_ssd ms < Lower Is Better a . 15.78 |=================================================================== b . 16.13 |==================================================================== NCNN 20230517 Target: CPU - Model: regnety_400m ms < Lower Is Better a . 38.20 |================================================================== b . 39.37 |==================================================================== NCNN 20230517 Target: CPU - Model: vision_transformer ms < Lower Is Better a . 46.50 |==================================================================== b . 45.56 |=================================================================== NCNN 20230517 Target: CPU - Model: FastestDet ms < Lower Is Better a . 9.62 |================================================================= b . 10.01 |==================================================================== Remhos 1.0 Test: Sample Remap Example Seconds < Lower Is Better a . 12.20 |=================================================================== b . 12.37 |==================================================================== Timed GCC Compilation 13.2 Time To Compile Seconds < Lower Is Better a . 957.95 |=================================================================== b . 956.13 |=================================================================== Opus Codec Encoding 1.4 WAV To Opus Encode Seconds < Lower Is Better a . 36.74 |==================================================================== b . 36.73 |==================================================================== Apache CouchDB 3.3.2 Bulk Size: 100 - Inserts: 1000 - Rounds: 30 Seconds < Lower Is Better a . 94.83 |==================================================================== Apache CouchDB 3.3.2 Bulk Size: 300 - Inserts: 1000 - Rounds: 30 Seconds < Lower Is Better a . 152.46 |=================================================================== Apache CouchDB 3.3.2 Bulk Size: 500 - Inserts: 1000 - Rounds: 30 Seconds < Lower Is Better a . 1090.42 |================================================================== Z3 Theorem Prover 4.12.1 SMT File: 1.smt2 Seconds < Lower Is Better a . 25.71 |==================================================================== b . 25.25 |=================================================================== Z3 Theorem Prover 4.12.1 SMT File: 2.smt2 Seconds < Lower Is Better a . 88.00 |==================================================================== b . 87.18 |=================================================================== GPAW 23.6 Input: Carbon Nanotube Seconds < Lower Is Better a . 45.82 |==================================================================== b . 45.64 |==================================================================== Blender 3.6 Blend File: BMW27 - Compute: CPU-Only Seconds < Lower Is Better a . 23.69 |==================================================================== b . 23.62 |==================================================================== Blender 3.6 Blend File: Classroom - Compute: CPU-Only Seconds < Lower Is Better a . 62.35 |==================================================================== b . 62.51 |==================================================================== Blender 3.6 Blend File: Fishy Cat - Compute: CPU-Only Seconds < Lower Is Better a . 30.59 |==================================================================== b . 30.77 |==================================================================== Blender 3.6 Blend File: Barbershop - Compute: CPU-Only Seconds < Lower Is Better a . 239.55 |=================================================================== b . 239.03 |===================================================================