Linux Laptop

Intel Core i7-5600U testing with a LENOVO 20BSCTO1WW (N14ET49W 1.27 BIOS) and Intel HD 5500 3GB on Ubuntu 20.04 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 2007150-NE-LINUXLAPT36
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Result
Identifier
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Performance Per
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Date
Run
  Test
  Duration
Intel I218-LM - Intel Core i7-5600U
July 14 2020
  6 Hours, 44 Minutes
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Linux Laptop Suite 1.0.0 System Test suite extracted from Linux Laptop. system/tesseract-ocr-1.0.1 Time To OCR 7 Images pts/brl-cad-1.1.0 VGR Performance Metric system/hugin-1.0.0 Panorama Photo Assistant + Stitching Time pts/montage-1.0.0 Mosaic of M17, K band, 1.5 deg x 1.5 deg system/ocrmypdf-1.0.0 Processing 60 Page PDF Document pts/daphne-1.0.0 OpenMP ndt_mapping Backend: OpenMP - Kernel: NDT Mapping pts/daphne-1.0.0 OpenMP points2image Backend: OpenMP - Kernel: Points2Image pts/daphne-1.0.0 OpenMP euclidean_cluster Backend: OpenMP - Kernel: Euclidean Cluster system/octave-benchmark-1.0.1 pts/rodinia-1.3.1 OMP_LAVAMD Test: OpenMP LavaMD pts/rodinia-1.3.1 OCL_MYOCYTE Test: OpenCL Myocyte pts/rodinia-1.3.1 OMP_HOTSPOT3D Test: OpenMP HotSpot3D pts/rodinia-1.3.1 OMP_LEUKOCYTE Test: OpenMP Leukocyte pts/rodinia-1.3.1 OMP_CFD Test: OpenMP CFD Solver pts/rodinia-1.3.1 OMP_STREAMCLUSTER Test: OpenMP Streamcluster 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/onednn-1.5.0 --ip --batch=inputs/ip/ip_all --cfg=f32 --engine=cpu Harness: IP Batch All - Data Type: f32 - Engine: CPU 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/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 --conv --batch=inputs/conv/shapes_auto --cfg=f32 --engine=cpu Harness: Convolution Batch Shapes Auto - Data Type: f32 - Engine: CPU 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/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/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/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/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/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/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/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/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 system/wireguard-1.0.1 pts/build-apache-1.6.1 Time To Compile pts/compress-zstd-1.2.0 -b3 Compression Level: 3 pts/compress-zstd-1.2.0 -b19 Compression Level: 19 pts/aom-av1-2.1.1 --cpu-used=0 --limit=10 Encoder Mode: Speed 0 Two-Pass pts/aom-av1-2.1.1 --cpu-used=4 --limit=40 Encoder Mode: Speed 4 Two-Pass pts/aom-av1-2.1.1 --cpu-used=6 --rt Encoder Mode: Speed 6 Realtime pts/aom-av1-2.1.1 --cpu-used=6 --limit=80 Encoder Mode: Speed 6 Two-Pass pts/aom-av1-2.1.1 --cpu-used=8 --rt Encoder Mode: Speed 8 Realtime pts/dav1d-1.6.0 -i chimera_8b_1080p.ivf Video Input: Chimera 1080p pts/dav1d-1.6.0 -i summer_nature_4k.ivf Video Input: Summer Nature 4K pts/dav1d-1.6.0 -i summer_nature_1080p.ivf Video Input: Summer Nature 1080p pts/dav1d-1.6.0 -i chimera_10b_1080p.ivf Video Input: Chimera 1080p 10-bit pts/v-ray-1.2.1 -m vray Mode: CPU pts/avifenc-1.0.0 -s 0 Encoder Speed: 0 pts/avifenc-1.0.0 -s 2 Encoder Speed: 2 pts/avifenc-1.0.0 -s 8 Encoder Speed: 8 pts/avifenc-1.0.0 -s 10 Encoder Speed: 10 pts/luxcorerender-1.2.3 DLSC/LuxCoreScene/render.cfg Scene: DLSC pts/luxcorerender-1.2.3 RainbowColorsAndPrism/LuxCoreScene/render.cfg Scene: Rainbow Colors and Prism pts/pyperformance-1.0.2 go Benchmark: go pts/pyperformance-1.0.2 2to3 Benchmark: 2to3 pts/pyperformance-1.0.2 chaos Benchmark: chaos pts/pyperformance-1.0.2 float Benchmark: float pts/pyperformance-1.0.2 nbody Benchmark: nbody pts/pyperformance-1.0.2 pathlib Benchmark: pathlib pts/pyperformance-1.0.2 raytrace Benchmark: raytrace 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 regex_compile Benchmark: regex_compile pts/pyperformance-1.0.2 python_startup Benchmark: python_startup pts/pyperformance-1.0.2 django_template Benchmark: django_template pts/pyperformance-1.0.2 pickle_pure_python Benchmark: pickle_pure_python