GM-1000, Karbon 700, CompuLab Airtop PCs

Tests for a future article by Michael Larabel.

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AV1 3 Tests
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Timed Code Compilation 5 Tests
C/C++ Compiler Tests 21 Tests
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CPU Massive 30 Tests
Creator Workloads 24 Tests
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Database Test Suite 5 Tests
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HPC - High Performance Computing 24 Tests
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Java 2 Tests
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Machine Learning 12 Tests
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Multi-Core 27 Tests
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Scientific Computing 11 Tests
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Common Workstation Benchmarks 3 Tests

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Karbon 700
October 30 2020
  22 Hours, 2 Minutes
CompuLab Airtop
October 31 2020
  19 Hours, 53 Minutes
CompuLab Airtop3
October 29 2020
  12 Hours, 25 Minutes
GM-1000
October 28 2020
  18 Hours
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  18 Hours, 5 Minutes

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GM-1000, Karbon 700, CompuLab Airtop PCs Suite 1.0.0 System Test suite extracted from GM-1000, Karbon 700, CompuLab Airtop PCs. pts/kripke-1.0.0 pts/build-llvm-1.2.1 Time To Compile pts/realsr-ncnn-1.0.0 -s 4 -x Scale: 4x - TAA: Yes pts/incompact3d-1.0.0 examples/Cylinder/input.i3d Input: Cylinder pts/java-gradle-perf-1.1.0 TEST_REACTOR Gradle Build: Reactor pts/astcenc-1.0.0 -exhaustive Preset: Exhaustive pts/ai-benchmark-1.0.0 Device AI Score pts/ai-benchmark-1.0.0 Device Training Score pts/ai-benchmark-1.0.0 Device Inference Score pts/mlpack-1.0.2 SCIKIT_QDA Benchmark: scikit_qda pts/lczero-1.5.1 -b eigen Backend: Eigen pts/lczero-1.5.1 -b blas Backend: BLAS pts/gromacs-1.4.0 Water Benchmark pts/yafaray-1.0.0 Total Time For Sample Scene pts/mocassin-1.0.0 Input: Dust 2D tau100.0 pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -iterations 200 Model: GoogleNet - Acceleration: CPU - Iterations: 200 pts/mlpack-1.0.2 SCIKIT_LINEARRIDGEREGRESSION Benchmark: scikit_linearridgeregression pts/brl-cad-1.1.0 VGR Performance Metric pts/hint-1.0.3 FLOAT Test: FLOAT pts/numpy-1.2.0 pts/kvazaar-1.0.0 -i Bosphorus_3840x2160.y4m --preset medium Video Input: Bosphorus 4K - Video Preset: Medium pts/svt-av1-2.2.1 -enc-mode 0 -n 20 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Enc Mode 0 - Input: 1080p pts/numenta-nab-1.1.0 -d earthgeckoSkyline Detector: Earthgecko Skyline system/wireguard-1.0.1 pts/openvkl-1.0.0 vklBenchmark Benchmark: vklBenchmark pts/cassandra-1.0.3 WRITE Test: Writes pts/hpcg-1.2.1 pts/dav1d-1.6.0 -i chimera_10b_1080p.ivf Video Input: Chimera 1080p 10-bit pts/build-linux-kernel-1.10.2 Time To Compile pts/namd-1.2.1 ATPase Simulation - 327,506 Atoms pts/tensorflow-lite-1.0.0 --graph=inception_v4.tflite Model: Inception V4 pts/avifenc-1.0.0 -s 0 Encoder Speed: 0 pts/tensorflow-lite-1.0.0 --graph=inception_resnet_v2.tflite Model: Inception ResNet V2 pts/luxcorerender-1.2.3 DLSC/LuxCoreScene/render.cfg Scene: DLSC pts/mnn-1.0.1 Model: inception-v3 pts/mnn-1.0.1 Model: resnet-v2-50 pts/mnn-1.0.1 Model: SqueezeNetV1.0 pts/john-the-ripper-1.7.2 --format=md5crypt Test: MD5 pts/build-gdb-1.0.1 Time To Compile pts/caffe-1.5.0 --model=../models/bvlc_googlenet/deploy.prototxt -iterations 100 Model: GoogleNet - Acceleration: CPU - Iterations: 100 pts/numenta-nab-1.1.0 -d relativeEntropy Detector: Relative Entropy pts/rocksdb-1.0.2 --benchmarks="fillrandom" Test: Random Fill pts/compress-zstd-1.2.1 -b19 Compression Level: 19 pts/rocksdb-1.0.2 --benchmarks="fillsync" Test: Random Fill Sync pts/byte-1.2.2 TEST_DHRY2 Computational Test: Dhrystone 2 pts/hmmer-1.2.0 Pfam Database Search pts/numenta-nab-1.1.0 -d bayesChangePt Detector: Bayesian Changepoint pts/rocksdb-1.0.2 --benchmarks="readwhilewriting" Test: Read While Writing pts/luxcorerender-1.2.3 RainbowColorsAndPrism/LuxCoreScene/render.cfg Scene: Rainbow Colors and Prism pts/glmark2-1.2.0 -s 1920x1080 Resolution: 1920 x 1080 pts/vpxenc-3.0.0 --cpu-used=0 Speed: Speed 0 pts/espeak-1.6.0 Text-To-Speech Synthesis pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -iterations 200 Model: AlexNet - Acceleration: CPU - Iterations: 200 pts/build-php-1.5.1 Time To Compile pts/avifenc-1.0.0 -s 2 Encoder Speed: 2 pts/ncnn-1.0.3 -1 Target: CPU - Model: yolov4-tiny pts/ncnn-1.0.3 -1 Target: CPU - Model: resnet50 pts/ncnn-1.0.3 -1 Target: CPU - Model: alexnet pts/ncnn-1.0.3 -1 Target: CPU - Model: resnet18 pts/ncnn-1.0.3 -1 Target: CPU - Model: vgg16 pts/ncnn-1.0.3 -1 Target: CPU - Model: googlenet pts/ncnn-1.0.3 -1 Target: CPU-v2-v2 - Model: mobilenet-v2 pts/ncnn-1.0.3 -1 Target: CPU - Model: mobilenet pts/ncnn-1.0.3 -1 Target: CPU - Model: squeezenet system/rawtherapee-1.0.1 Total Benchmark Time pts/kvazaar-1.0.0 -i Bosphorus_3840x2160.y4m --preset veryfast Video Input: Bosphorus 4K - Video Preset: Very Fast pts/realsr-ncnn-1.0.0 -s 4 Scale: 4x - TAA: No pts/pyperformance-1.0.2 raytrace Benchmark: raytrace pts/openssl-1.11.0 RSA 4096-bit Performance pts/pgbench-1.10.1 -s 1 -c 1 Scaling Factor: 1 - Clients: 1 - Mode: Read Write - Average Latency pts/pgbench-1.10.1 -s 1 -c 1 Scaling Factor: 1 - Clients: 1 - Mode: Read Write pts/x265-1.3.0 Bosphorus_3840x2160.y4m Video Input: Bosphorus 4K pts/john-the-ripper-1.7.2 --format=bcrypt Test: Blowfish pts/pyperformance-1.0.2 python_startup Benchmark: python_startup pts/keydb-1.2.0 pts/caffe-1.5.0 --model=../models/bvlc_alexnet/deploy.prototxt -iterations 100 Model: AlexNet - Acceleration: CPU - Iterations: 100 pts/tensorflow-lite-1.0.0 --graph=nasnet_mobile.tflite Model: NASNet Mobile pts/numenta-nab-1.1.0 -d windowedGaussian Detector: Windowed Gaussian pts/tensorflow-lite-1.0.0 --graph=squeezenet.tflite Model: SqueezeNet pts/rocksdb-1.0.2 --benchmarks="readrandom" Test: Random Read system/hugin-1.0.0 Panorama Photo Assistant + Stitching Time pts/astcenc-1.0.0 -thorough Preset: Thorough pts/onednn-1.5.0 --ip --batch=inputs/ip/ip_1d --cfg=f32 --engine=cpu Harness: IP Batch 1D - Data Type: f32 - Engine: CPU pts/kvazaar-1.0.0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset veryfast Video Input: Bosphorus 1080p - Video Preset: Very Fast pts/tensorflow-lite-1.0.0 --graph=mobilenet_v1_1.0_224_quant.tflite Model: Mobilenet Quant pts/tensorflow-lite-1.0.0 --graph=mobilenet_v1_1.0_224.tflite Model: Mobilenet Float pts/pyperformance-1.0.2 2to3 Benchmark: 2to3 pts/mlpack-1.0.2 SCIKIT_ICA Benchmark: scikit_ica pts/onednn-1.5.0 --ip --batch=inputs/ip/ip_all --cfg=u8s8f32 --engine=cpu Harness: IP Batch All - Data Type: u8s8f32 - Engine: CPU pts/onednn-1.5.0 --ip --batch=inputs/ip/ip_all --cfg=f32 --engine=cpu Harness: IP Batch All - Data Type: f32 - Engine: CPU pts/oidn-1.2.0 -hdr memorial.pfm Scene: Memorial pts/onednn-1.5.0 --rnn --batch=inputs/rnn/rnn_training --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Training - Data Type: f32 - Engine: CPU pts/ncnn-1.0.3 Target: Vulkan GPU - Model: yolov4-tiny pts/ncnn-1.0.3 Target: Vulkan GPU - Model: resnet50 pts/ncnn-1.0.3 Target: Vulkan GPU - Model: alexnet pts/ncnn-1.0.3 Target: Vulkan GPU - Model: resnet18 pts/ncnn-1.0.3 Target: Vulkan GPU - Model: vgg16 pts/ncnn-1.0.3 Target: Vulkan GPU - Model: googlenet pts/ncnn-1.0.3 Target: Vulkan GPU - Model: blazeface pts/ncnn-1.0.3 Target: Vulkan GPU - Model: efficientnet-b0 pts/ncnn-1.0.3 Target: Vulkan GPU - Model: mnasnet pts/ncnn-1.0.3 Target: Vulkan GPU - Model: shufflenet-v2 pts/ncnn-1.0.3 Target: Vulkan GPU-v3-v3 - Model: mobilenet-v3 pts/ncnn-1.0.3 Target: Vulkan GPU-v2-v2 - Model: mobilenet-v2 pts/ncnn-1.0.3 Target: Vulkan GPU - Model: mobilenet pts/ncnn-1.0.3 Target: Vulkan GPU - Model: squeezenet pts/onednn-1.5.0 --deconv --batch=inputs/deconv/deconv_1d --cfg=f32 --engine=cpu Harness: Deconvolution Batch deconv_1d - Data Type: f32 - Engine: CPU pts/git-1.1.0 Time To Complete Common Git Commands pts/rays1bench-1.0.0 Large Scene pts/kvazaar-1.0.0 -i Bosphorus_3840x2160.y4m --preset ultrafast Video Input: Bosphorus 4K - Video Preset: Ultra Fast pts/onednn-1.5.0 --deconv --batch=inputs/deconv/deconv_1d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch deconv_1d - Data Type: u8s8f32 - Engine: CPU pts/kvazaar-1.0.0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset medium Video Input: Bosphorus 1080p - Video Preset: Medium pts/pgbench-1.10.1 -s 1 -c 50 Scaling Factor: 1 - Clients: 50 - Mode: Read Write - Average Latency pts/pgbench-1.10.1 -s 1 -c 50 Scaling Factor: 1 - Clients: 50 - Mode: Read Write pts/pgbench-1.10.1 -s 1 -c 1 -S Scaling Factor: 1 - Clients: 1 - Mode: Read Only - Average Latency pts/pgbench-1.10.1 -s 1 -c 1 -S Scaling Factor: 1 - Clients: 1 - Mode: Read Only pts/pgbench-1.10.1 -s 1 -c 50 -S Scaling Factor: 1 - Clients: 50 - Mode: Read Only - Average Latency pts/pgbench-1.10.1 -s 1 -c 50 -S Scaling Factor: 1 - Clients: 50 - Mode: Read Only pts/pyperformance-1.0.2 go Benchmark: go system/ocrmypdf-1.0.0 Processing 60 Page PDF Document pts/dacapobench-1.0.1 h2 Java Test: H2 pts/onednn-1.5.0 --ip --batch=inputs/ip/ip_1d --cfg=u8s8f32 --engine=cpu Harness: IP Batch 1D - Data Type: u8s8f32 - Engine: CPU pts/svt-av1-2.2.1 -enc-mode 4 -n 80 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Encoder Mode: Enc Mode 4 - Input: 1080p pts/compress-7zip-1.7.1 Compress Speed Test pts/webp-1.0.0 -q 100 -lossless -m 6 Encode Settings: Quality 100, Lossless, Highest Compression pts/libraw-1.0.0 Post-Processing Benchmark pts/dav1d-1.6.0 -i summer_nature_4k.ivf Video Input: Summer Nature 4K pts/dacapobench-1.0.1 tradesoap Java Test: Tradesoap pts/vpxenc-3.0.0 --cpu-used=5 Speed: Speed 5 pts/x265-1.3.0 Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m Video Input: Bosphorus 1080p pts/build-apache-1.6.1 Time To Compile pts/leveldb-1.0.0 --benchmarks=seekrandom --num=1000000 Benchmark: Seek Random pts/postmark-1.1.2 Disk Transaction Performance pts/onednn-1.5.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=u8s8f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: u8s8f32 - Engine: CPU pts/kvazaar-1.0.0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.y4m --preset ultrafast Video Input: Bosphorus 1080p - Video Preset: Ultra Fast pts/rocksdb-1.0.2 --benchmarks="fillseq" Test: Sequential Fill pts/onednn-1.5.0 --rnn --batch=inputs/rnn/rnn_inference --cfg=f32 --engine=cpu Harness: Recurrent Neural Network Inference - Data Type: f32 - Engine: CPU pts/pyperformance-1.0.2 regex_compile Benchmark: regex_compile pts/dacapobench-1.0.1 tradebeans Java Test: Tradebeans pts/waifu2x-ncnn-1.0.0 -s 2 -n 3 -x Scale: 2x - Denoise: 3 - TAA: Yes pts/astcenc-1.0.0 -medium Preset: Medium pts/dav1d-1.6.0 -i chimera_8b_1080p.ivf Video Input: Chimera 1080p pts/pyperformance-1.0.2 pathlib Benchmark: pathlib pts/compress-zstd-1.2.1 -b3 Compression Level: 3 pts/mlpack-1.0.2 SCIKIT_SVM Benchmark: scikit_svm pts/pyperformance-1.0.2 django_template Benchmark: django_template pts/leveldb-1.0.0 --benchmarks=readrandom --num=1000000 Benchmark: Random Read pts/blosc-1.0.0 blosclz Compressor: blosclz pts/rnnoise-1.0.2 pts/pyperformance-1.0.2 pickle_pure_python Benchmark: pickle_pure_python pts/pyperformance-1.0.2 float Benchmark: float system/tesseract-ocr-1.0.1 Time To OCR 7 Images pts/pyperformance-1.0.2 chaos Benchmark: chaos pts/pyperformance-1.0.2 json_loads Benchmark: json_loads pts/pyperformance-1.0.2 crypto_pyaes Benchmark: crypto_pyaes pts/pyperformance-1.0.2 nbody Benchmark: nbody pts/tnn-1.0.0 -dt NAIVE -mp ../benchmark/benchmark-model/mobilenet_v2.tnnproto Target: CPU - Model: MobileNet v2 system/rsvg-1.0.0 Operation: SVG Files To PNG pts/tnn-1.0.0 -dt NAIVE -mp ../benchmark/benchmark-model/squeezenet_v1.1.tnnproto Target: CPU - Model: SqueezeNet v1.1 pts/mafft-1.6.1 Multiple Sequence Alignment - LSU RNA pts/webp-1.0.0 -q 100 -lossless Encode Settings: Quality 100, Lossless pts/leveldb-1.0.0 --benchmarks=fillseq --num=500000 Benchmark: Sequential Fill pts/lammps-1.2.1 in.rhodo Model: Rhodopsin Protein pts/dolfyn-1.0.3 Computational Fluid Dynamics pts/svt-vp9-1.2.2 -tune 0 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: Visual Quality Optimized - Input: Bosphorus 1080p pts/leveldb-1.0.0 --benchmarks=deleterandom --num=500000 Benchmark: Random Delete pts/leveldb-1.0.0 --benchmarks=overwrite --num=100000 Benchmark: Overwrite pts/leveldb-1.0.0 --benchmarks=fillrandom --num=100000 Benchmark: Random Fill pts/svt-vp9-1.2.2 -tune 1 -i Bosphorus_1920x1080_120fps_420_8bit_YUV.yuv -w 1920 -h 1080 Tuning: PSNR/SSIM Optimized - Input: Bosphorus 1080p pts/leveldb-1.0.0 --benchmarks=readhot --num=1000000 Benchmark: Hot Read pts/onednn-1.5.0 --matmul --batch=inputs/matmul/shapes_transformer --cfg=f32 --engine=cpu Harness: Matrix Multiply Batch Shapes Transformer - Data Type: f32 - Engine: CPU pts/webp-1.0.0 -q 100 -m 6 Encode Settings: Quality 100, Highest Compression pts/avifenc-1.0.0 -s 10 Encoder Speed: 10 pts/astcenc-1.0.0 -fast Preset: Fast system/octave-benchmark-1.0.1 pts/onednn-1.5.0 --conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU pts/dacapobench-1.0.1 jython Java Test: Jython pts/onednn-1.5.0 --conv --batch=inputs/conv/shapes_auto --cfg=u8s8f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: u8s8f32 - Engine: CPU pts/avifenc-1.0.0 -s 8 Encoder Speed: 8 pts/waifu2x-ncnn-1.0.0 -s 2 -n 3 Scale: 2x - Denoise: 3 - TAA: No pts/leveldb-1.0.0 --benchmarks=fillsync --num=1000000 Benchmark: Fill Sync pts/onednn-1.5.0 --deconv --batch=inputs/deconv/deconv_3d --cfg=f32 --engine=cpu Harness: Deconvolution Batch deconv_3d - Data Type: f32 - Engine: CPU pts/dav1d-1.6.0 -i summer_nature_1080p.ivf Video Input: Summer Nature 1080p pts/onednn-1.5.0 --deconv --batch=inputs/deconv/deconv_3d --cfg=u8s8f32 --engine=cpu Harness: Deconvolution Batch deconv_3d - Data Type: u8s8f32 - Engine: CPU pts/ffte-1.2.1 N=256, 3D Complex FFT Routine pts/webp-1.0.0 -q 100 Encode Settings: Quality 100 pts/webp-1.0.0 Encode Settings: Default pts/ior-1.0.0 Read Test pts/ior-1.0.0 Write Test