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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C++ Boost Tests 2 Tests
CPU Massive 4 Tests
Creator Workloads 7 Tests
Database Test Suite 3 Tests
Encoding 3 Tests
Game Development 2 Tests
HPC - High Performance Computing 2 Tests
Multi-Core 7 Tests
NVIDIA GPU Compute 2 Tests
Intel oneAPI 3 Tests
OpenMPI Tests 3 Tests
Python Tests 2 Tests
Renderers 2 Tests
Software Defined Radio 2 Tests
Server 3 Tests
Server CPU Tests 4 Tests
Video Encoding 2 Tests

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  Test
  Duration
a
August 06 2023
  3 Hours, 24 Minutes
b
August 06 2023
  3 Hours, 43 Minutes
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  3 Hours, 33 Minutes
Only show results matching title/arguments (delimit multiple options with a comma):
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xeon auggy, "Timed GCC Compilation 13.2 - Time To Compile", Lower Results Are Better "a", "b",958.093,954.16 "Apache CouchDB 3.3.2 - Bulk Size: 500 - Inserts: 1000 - Rounds: 30", Lower Results Are Better "a", "libxsmm 2-1.17-3645 - M N K: 128", Higher Results Are Better "a", "b",2001.2,1892.1 "Blender 3.6 - Blend File: Barbershop - Compute: CPU-Only", Lower Results Are Better "a",239.86,239.23 "b",240.34,237.71 "libxsmm 2-1.17-3645 - M N K: 256", Higher Results Are Better "a", "b",589.8,595.1 "OSPRay 2.12 - Benchmark: particle_volume/pathtracer/real_time", Higher Results Are Better "a", "b",151.905,150.641 "NCNN 20230517 - Target: CPU - Model: FastestDet", Lower Results Are Better "a",9.57,9.67 "b",10.29,9.72 "NCNN 20230517 - Target: CPU - Model: vision_transformer", Lower Results Are Better "a",44.04,48.95 "b",46.75,44.37 "NCNN 20230517 - Target: CPU - Model: regnety_400m", Lower Results Are Better "a",39.06,37.34 "b",38.27,40.46 "NCNN 20230517 - Target: CPU - Model: squeezenet_ssd", Lower Results Are Better "a",15.71,15.85 "b",16.54,15.72 "NCNN 20230517 - Target: CPU - Model: yolov4-tiny", Lower Results Are Better "a",24.12,25.41 "b",25.11,23.84 "NCNN 20230517 - Target: CPU - Model: resnet50", Lower Results Are Better "a",17.21,17.93 "b",18.98,17.32 "NCNN 20230517 - Target: CPU - Model: alexnet", Lower Results Are Better "a",5.22,6.08 "b",5.65,5.22 "NCNN 20230517 - Target: CPU - Model: resnet18", Lower Results Are Better "a",9.27,11.34 "b",9.93,9.32 "NCNN 20230517 - Target: CPU - Model: vgg16", Lower Results Are Better "a",25.43,27.1 "b",26.53,25.85 "NCNN 20230517 - Target: CPU - Model: googlenet", Lower Results Are Better "a",16.01,18.1 "b",17.09,16.35 "NCNN 20230517 - Target: CPU - Model: blazeface", Lower Results Are Better "a",4.57,4.4 "b",4.61,4.6 "NCNN 20230517 - Target: CPU - Model: efficientnet-b0", Lower Results Are Better "a",11.7,11.25 "b",11.38,11.9 "NCNN 20230517 - Target: CPU - Model: mnasnet", Lower Results Are Better "a",7.54,7.67 "b",7.44,7.42 "NCNN 20230517 - Target: CPU - Model: shufflenet-v2", Lower Results Are Better "a",9.85,9.79 "b",9.69,9.81 "NCNN 20230517 - Target: CPU-v3-v3 - Model: mobilenet-v3", Lower Results Are Better "a",8.85,8.57 "b",8.8,8.74 "NCNN 20230517 - Target: CPU-v2-v2 - Model: mobilenet-v2", Lower Results Are Better "a",8.04,7.78 "b",7.92,7.96 "NCNN 20230517 - Target: CPU - Model: mobilenet", Lower Results Are Better "a",15.24,16.88 "b",16.18,15.62 "VVenC 1.9 - Video Input: Bosphorus 4K - Video Preset: Fast", Higher Results Are Better "a",5.691,5.653 "b",5.78,5.654 "OSPRay 2.12 - Benchmark: particle_volume/scivis/real_time", Higher Results Are Better "a", "b",24.748,24.8174 "Z3 Theorem Prover 4.12.1 - SMT File: 2.smt2", Lower Results Are Better "a",87.978,88.018 "b",87.23,87.126 "Apache CouchDB 3.3.2 - Bulk Size: 300 - Inserts: 1000 - Rounds: 30", Lower Results Are Better "a", "OSPRay 2.12 - Benchmark: particle_volume/ao/real_time", Higher Results Are Better "a", "b",24.7073,24.5341 "Blender 3.6 - Blend File: Classroom - Compute: CPU-Only", Lower Results Are Better "a",62.31,62.38 "b",62.7,62.32 "VVenC 1.9 - Video Input: Bosphorus 4K - Video Preset: Faster", Higher Results Are Better "a",10.255,10.312 "b",10.533,10.326 "srsRAN Project 23.5 - Test: PUSCH Processor Benchmark, Throughput Total", Higher Results Are Better "a",9847.8,9753.1 "b",9790.6,9722.7 "Apache CouchDB 3.3.2 - Bulk Size: 100 - Inserts: 1000 - Rounds: 30", Lower Results Are Better "a", "GPAW 23.6 - Input: Carbon Nanotube", Lower Results Are Better "a",45.839,45.809 "b",45.664,45.607 "VVenC 1.9 - Video Input: Bosphorus 1080p - Video Preset: Fast", Higher Results Are Better "a",15.652,15.763 "b",15.682,15.763 "OSPRay 2.12 - Benchmark: gravity_spheres_volume/dim_512/scivis/real_time", Higher Results Are Better "a", "b",20.5324,20.4311 "OSPRay 2.12 - Benchmark: gravity_spheres_volume/dim_512/ao/real_time", Higher Results Are Better "a", "b",21.1648,20.727 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: Stock - Precision: double - X Y Z: 512", Higher Results Are Better "a",47.1372,47.4229 "b",47.3122,47.4589 "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500", Lower Results Are Better "b", "a", "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500", Higher Results Are Better "b", "a", "OSPRay 2.12 - Benchmark: gravity_spheres_volume/dim_512/pathtracer/real_time", Higher Results Are Better "a", "b",22.5793,22.5711 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 512", Higher Results Are Better "a",49.725,49.1475 "b",48.3319,49.11 "Blender 3.6 - Blend File: Fishy Cat - Compute: CPU-Only", Lower Results Are Better "a",30.59,30.58 "b",30.79,30.75 "QuantLib 1.30 - ", Higher Results Are Better "a",2620.9,2624.9 "b",2609.4,2605.8 "Stress-NG 0.15.10 - Test: Cloning", Higher Results Are Better "a",12924.33,19465.73 "b",12518.15,13827.47 "Stress-NG 0.15.10 - Test: Pthread", Higher Results Are Better "a",91852.39,92410.69 "b",91256.6,89466.8 "Stress-NG 0.15.10 - Test: Zlib", Higher Results Are Better "a",6888.69,6871.03 "b",6875.83,6884.61 "Stress-NG 0.15.10 - Test: Vector Floating Point", Higher Results Are Better "a",133351.3,131606.86 "b",131335.25,130865.24 "Stress-NG 0.15.10 - Test: Fused Multiply-Add", Higher Results Are Better "a",181201866.95,180964493.98 "b",181222747.17,181406767.67 "Stress-NG 0.15.10 - Test: Matrix 3D Math", Higher Results Are Better "a",12734.01,12753.6 "b",12737.64,12747.76 "Stress-NG 0.15.10 - Test: Pipe", Higher Results Are Better "a",43023909.54,37976424.07 "b",42955824.26,55694969.67 "Stress-NG 0.15.10 - Test: Wide Vector Math", Higher Results Are Better "a",2194191.25,2196591.57 "b",2196739.89,2195744.52 "Stress-NG 0.15.10 - Test: Floating Point", Higher Results Are Better "a",21141.67,21127.95 "b",21142.15,21123.88 "Stress-NG 0.15.10 - Test: AVL Tree", Higher Results Are Better "a",610.77,610.6 "b",611.26,610.39 "Stress-NG 0.15.10 - Test: Vector Shuffle", Higher Results Are Better "a",48053.21,48055.74 "b",48118.99,48034.56 "Liquid-DSP 1.6 - Threads: 16 - Buffer Length: 256 - Filter Length: 512", Higher Results Are Better "a",202410000,200820000 "b",199440000,198140000 "Liquid-DSP 1.6 - Threads: 16 - Buffer Length: 256 - Filter Length: 57", Higher Results Are Better "a",618260000,611950000 "b",634840000,612230000 "Liquid-DSP 1.6 - Threads: 16 - Buffer Length: 256 - Filter Length: 32", Higher Results Are Better "a",492160000,495160000 "b",497580000,499240000 "Liquid-DSP 1.6 - Threads: 1 - Buffer Length: 256 - Filter Length: 512", Higher Results Are Better "a",13324000,13322000 "b",13257000,13325000 "Liquid-DSP 1.6 - Threads: 1 - Buffer Length: 256 - Filter Length: 57", Higher Results Are Better "a",53918000,53919000 "b",53925000,53928000 "Liquid-DSP 1.6 - Threads: 1 - Buffer Length: 256 - Filter Length: 32", Higher Results Are Better "a",32338000,32338000 "b",32267000,32267000 "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500", Lower Results Are Better "b", "a", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500", Higher Results Are Better "b", "a", "Opus Codec Encoding 1.4 - WAV To Opus Encode", Lower Results Are Better "a", "b",36.739,36.713 "Z3 Theorem Prover 4.12.1 - SMT File: 1.smt2", Lower Results Are Better "a",25.741,25.685 "b",25.18,25.322 "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500", Lower Results Are Better "b", "a", "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500", Higher Results Are Better "b", "a", "srsRAN Project 23.5 - Test: Downlink Processor Benchmark", Higher Results Are Better "a",555.8,557.2 "b",558,555.5 "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200", Lower Results Are Better "b", "a", "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200", Higher Results Are Better "b", "a", "Blender 3.6 - Blend File: BMW27 - Compute: CPU-Only", Lower Results Are Better "a",23.6,23.78 "b",23.56,23.68 "VVenC 1.9 - Video Input: Bosphorus 1080p - Video Preset: Faster", Higher Results Are Better "a",29.444,28.71 "b",28.949,29.402 "Liquid-DSP 1.6 - Threads: 160 - Buffer Length: 256 - Filter Length: 512", Higher Results Are Better "a", "b",1013000000,1009400000 "Liquid-DSP 1.6 - Threads: 128 - Buffer Length: 256 - Filter Length: 512", Higher Results Are Better "a", "b",947370000,943010000 "Liquid-DSP 1.6 - Threads: 64 - Buffer Length: 256 - Filter Length: 512", Higher Results Are Better "a", "b",731560000,729060000 "Liquid-DSP 1.6 - Threads: 32 - Buffer Length: 256 - Filter Length: 512", Higher Results Are Better "a", "b",399040000,393490000 "Liquid-DSP 1.6 - Threads: 160 - Buffer Length: 256 - Filter Length: 57", Higher Results Are Better "a", "b",2653700000,2619200000 "Liquid-DSP 1.6 - Threads: 128 - Buffer Length: 256 - Filter Length: 57", Higher Results Are Better "a", "b",2439700000,2413000000 "Liquid-DSP 1.6 - Threads: 160 - Buffer Length: 256 - Filter Length: 32", Higher Results Are Better "a", "b",3391100000,3372800000 "Liquid-DSP 1.6 - Threads: 128 - Buffer Length: 256 - Filter Length: 32", Higher Results Are Better "a", "b",2951500000,2938800000 "Liquid-DSP 1.6 - Threads: 64 - Buffer Length: 256 - Filter Length: 57", Higher Results Are Better "a", "b",2063000000,2090300000 "Liquid-DSP 1.6 - Threads: 64 - Buffer Length: 256 - Filter Length: 32", Higher Results Are Better "a", "b",1822700000,1828200000 "Liquid-DSP 1.6 - Threads: 32 - Buffer Length: 256 - Filter Length: 57", Higher Results Are Better "a", "b",1206100000,1164900000 "Liquid-DSP 1.6 - Threads: 32 - Buffer Length: 256 - Filter Length: 32", Higher Results Are Better "a", "b",991360000,995530000 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 512", Higher Results Are Better "a",91.6573,89.4917 "b",91.4048,89.0728 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: Stock - Precision: float - X Y Z: 512", Higher Results Are Better "a",92.932,93.7378 "b",92.0151,92.4984 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: Stock - Precision: double - X Y Z: 512", Higher Results Are Better "a",94.3888,94.1386 "b",93.4506,91.9839 "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 500", "a", "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 512", Higher Results Are Better "a",93.7231,95.9464 "b",95.2981,93.3902 "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200", Lower Results Are Better "b", "a", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200", Higher Results Are Better "b", "a", "Embree 4.1 - Binary: Pathtracer - Model: Asian Dragon Obj", Higher Results Are Better "a",76.9356,76.9859 "b",77.2924,77.2341 "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500", Lower Results Are Better "b", "a", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500", Higher Results Are Better "b", "a", "Embree 4.1 - Binary: Pathtracer ISPC - Model: Asian Dragon Obj", Higher Results Are Better "a",89.9055,89.7838 "b",89.9608,90.0656 "srsRAN Project 23.5 - Test: PUSCH Processor Benchmark, Throughput Thread", Higher Results Are Better "a",166.5,163.1 "b",163.8,165.6 "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200", Lower Results Are Better "b", "a", "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200", Higher Results Are Better "b", "a", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200", Lower Results Are Better "b", "a", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200", Higher Results Are Better "b", "a", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 500", "a", "dav1d 1.2.1 - Video Input: Chimera 1080p 10-bit", Higher Results Are Better "a", "b",476.36,477.18 "dav1d 1.2.1 - Video Input: Chimera 1080p", Higher Results Are Better "a", "b",516.56,516.44 "Apache IoTDB 1.1.2 - Device Count: 500 - Batch Size Per Write: 1 - Sensor Count: 200", "a", "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 500", "a", "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 512", Higher Results Are Better "a",169.655,172.157 "b",169.744,172.524 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: Stock - Precision: float - X Y Z: 512", Higher Results Are Better "a",175.949,177.311 "b",173.991,174.236 "Intel Open Image Denoise 2.0 - Run: RTLightmap.hdr.4096x4096 - Device: CPU-Only", Higher Results Are Better "a",1.4709624654508 "b",1.4549666012417,1.4607688610823 "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 100 - Sensor Count: 200", "a", "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 500", "a", "dav1d 1.2.1 - Video Input: Summer Nature 4K", Higher Results Are Better "a", "b",282.73,282.57 "Apache IoTDB 1.1.2 - Device Count: 200 - Batch Size Per Write: 1 - Sensor Count: 200", "a", "Remhos 1.0 - Test: Sample Remap Example", Lower Results Are Better "a", "b",12.264,12.466 "Apache IoTDB 1.1.2 - Device Count: 100 - Batch Size Per Write: 1 - Sensor Count: 200", "a", "Embree 4.1 - Binary: Pathtracer - Model: Asian Dragon", Higher Results Are Better "a",85.2856,85.1989 "b",85.2745,84.9884 "libxsmm 2-1.17-3645 - M N K: 64", Higher Results Are Better "a", "b",1214.7,1217.2 "libxsmm 2-1.17-3645 - M N K: 32", Higher Results Are Better "a", "b",636.9,641.6 "Embree 4.1 - Binary: Pathtracer - Model: Crown", Higher Results Are Better "a", "b",70.9077,70.6732 "Dragonflydb 1.6.2 - Clients Per Thread: 10 - Set To Get Ratio: 1:10", "b", "a", "Dragonflydb 1.6.2 - Clients Per Thread: 10 - Set To Get Ratio: 1:100", "b", "a", "Dragonflydb 1.6.2 - Clients Per Thread: 10 - Set To Get Ratio: 1:5", "b", "a", "Embree 4.1 - Binary: Pathtracer ISPC - Model: Asian Dragon", Higher Results Are Better "a",104.7303,104.0992 "b",104.3132,104.7945 "Dragonflydb 1.6.2 - Clients Per Thread: 20 - Set To Get Ratio: 1:5", "b", "a", "Dragonflydb 1.6.2 - Clients Per Thread: 60 - Set To Get Ratio: 1:5", "b", "a", "Dragonflydb 1.6.2 - Clients Per Thread: 60 - Set To Get Ratio: 1:100", "b", "a", "Dragonflydb 1.6.2 - Clients Per Thread: 60 - Set To Get Ratio: 1:10", "b", "a", "Dragonflydb 1.6.2 - Clients Per Thread: 50 - Set To Get Ratio: 1:100", "b", "a", "Dragonflydb 1.6.2 - Clients Per Thread: 50 - Set To Get Ratio: 1:10", "b", "a", "Dragonflydb 1.6.2 - Clients Per Thread: 50 - Set To Get Ratio: 1:5", "b", "a", "Dragonflydb 1.6.2 - Clients Per Thread: 20 - Set To Get Ratio: 1:10", "b", "a", "Dragonflydb 1.6.2 - Clients Per Thread: 20 - Set To Get Ratio: 1:100", "b", "a", "Embree 4.1 - Binary: Pathtracer ISPC - Model: Crown", Higher Results Are Better "a", "b",88.0346,87.8292 "Intel Open Image Denoise 2.0 - Run: RT.hdr_alb_nrm.3840x2160 - Device: CPU-Only", Higher Results Are Better "a",3.0421027013872 "b",3.0118758263834,3.0036885295142 "Intel Open Image Denoise 2.0 - Run: RT.ldr_alb_nrm.3840x2160 - Device: CPU-Only", Higher Results Are Better "a",3.0458924617208 "b",3.0183940936064,3.0467090971687 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 256", Higher Results Are Better "a", "b",45.9108,47.0105 "dav1d 1.2.1 - Video Input: Summer Nature 1080p", Higher Results Are Better "a", "b",698.59,699.59 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: Stock - Precision: double - X Y Z: 256", Higher Results Are Better "a", "b",46.5867,46.4237 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 256", Higher Results Are Better "a", "b",94.3373,91.2948 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 256", Higher Results Are Better "a", "b",98.8305,98.8325 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: Stock - Precision: double - X Y Z: 256", Higher Results Are Better "a", "b",101.704,103.148 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: Stock - Precision: float - X Y Z: 256", Higher Results Are Better "a", "b",104.688,104.001 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 256", Higher Results Are Better "a", "b",233.851,227.231 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: Stock - Precision: float - X Y Z: 256", Higher Results Are Better "a", "b",238.87,233.367 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: Stock - Precision: double - X Y Z: 128", Higher Results Are Better "a", "b",66.9429,68.9536 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: double - X Y Z: 128", Higher Results Are Better "a", "b",90.4456,93.3622 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: Stock - Precision: float - X Y Z: 128", Higher Results Are Better "a", "b",109.493,106.411 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: Stock - Precision: double - X Y Z: 128", Higher Results Are Better "a", "b",120.879,112.798 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: double - X Y Z: 128", Higher Results Are Better "a", "b",150.623,145.73 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: c2c - Backend: FFTW - Precision: float - X Y Z: 128", Higher Results Are Better "a", "b",158.503,158.918 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: Stock - Precision: float - X Y Z: 128", Higher Results Are Better "a", "b",182.89,181.17 "HeFFTe - Highly Efficient FFT for Exascale 2.3 - Test: r2c - Backend: FFTW - Precision: float - X Y Z: 128", Higher Results Are Better "a", "b",199.724,198.942