xeon auggy 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 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 |=================================================================== 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 |=================================================================== Remhos 1.0 Test: Sample Remap Example Seconds < Lower Is Better a . 12.20 |=================================================================== b . 12.37 |==================================================================== 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 |==================================================================== 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 |==================================================================== 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 |==================================================================== 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 |=============================================================== 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 |================================================================== 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 QuantLib 1.30 MFLOPS > Higher Is Better a . 2622.9 |=================================================================== b . 2607.6 |=================================================================== 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 |=================================================================== 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 |=================================================================== 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 |==================================================================== 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 |==================================================================== 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 |=============================================================== 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 |=============================================================== GPAW 23.6 Input: Carbon Nanotube Seconds < Lower Is Better a . 45.82 |==================================================================== b . 45.64 |==================================================================== 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 |==================================================================== 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 |=================================================================== Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200 point/sec > Higher Is Better b . 628202.55 |=============================================================== a . 638644.35 |================================================================ Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200 Average Latency < Lower Is Better b . 18.04 |==================================================================== a . 17.54 |================================================================== Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 point/sec > Higher Is Better b . 992909.69 |================================================================ a . 995259.68 |================================================================ Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500 Average Latency < Lower Is Better b . 36.16 |==================================================================== a . 35.99 |==================================================================== Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200 point/sec > Higher Is Better b . 920435.77 |================================================================ a . 904320.60 |=============================================================== Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200 Average Latency < Lower Is Better b . 14.42 |================================================================== a . 14.84 |==================================================================== Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500 point/sec > Higher Is Better b . 1137612.61 |=============================================================== a . 1134736.54 |=============================================================== Apache IoTDB 1.1.2 Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500 Average Latency < Lower Is Better b . 36.82 |==================================================================== a . 36.74 |==================================================================== Apache IoTDB 1.1.2 Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200 point/sec > Higher Is Better b . 1141859.25 |============================================================ a . 1199743.22 |=============================================================== Apache IoTDB 1.1.2 Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200 Average Latency < Lower Is Better b . 14.12 |==================================================================== a . 13.25 |================================================================ Apache IoTDB 1.1.2 Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500 point/sec > Higher Is Better b . 1372429.58 |=============================================================== a . 1343156.56 |============================================================== Apache IoTDB 1.1.2 Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500 Average Latency < Lower Is Better b . 32.75 |=================================================================== a . 33.38 |==================================================================== Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200 point/sec > Higher Is Better b . 34807016.85 |============================================================== a . 34266143.85 |============================================================= Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200 Average Latency < Lower Is Better b . 42.19 |=================================================================== a . 42.79 |==================================================================== Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500 point/sec > Higher Is Better b . 43021501.40 |============================================================== a . 39562245.22 |========================================================= Apache IoTDB 1.1.2 Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500 Average Latency < Lower Is Better b . 96.18 |=========================================================== a . 109.40 |===================================================================