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[D] GPU benchmarks for deep learning tasks

There is a benchmark of desktop and laptop GPU cards for deep learning: AI Benchmark. You can run these tests yourself, see https://pypi.org/project/ai-benchmark/.

More detailed results here: http://ai-benchmark.com/ranking_cpus_and_gpus_detailed.html (TensorFlow training and inference times for: MobileNet-V2, Inception-V3, Inception-V4, Inc-ResNet-V2, ResNet-V2-50, ResNet-V2-152, VGG-16, SRCNN 9-5-5, VGG-19 Super-Res, ResNet-SRGAN, ResNet-DPED, U-Net, Nvidia-SPADE, ICNet, PSPNet, DeepLab, Pixel-RNN, LSTM, GNMT).

I found other useful benchmarks and tests:

Take note that some GPUs are good for games but not for deep learning (for games 1660 Ti would be good enough and much, much cheaper, vide this and that). For general benchmarks, I recommend UserBenchmark (my Lenovo Y740 with Nvidia RTX 2080 Max-Q here.)

For comparison of different cards between frameworks, see Performance in: Keras or PyTorch as your first deep learning framework (June 2018), based on Comparing Deep Learning Frameworks: A Rosetta Stone Approach.

Do you know any other good rankings, benchmarks, and tests? (There is MLPerf, but I guess due to the complication of the procedure, the amount of data is very small.)

submitted by /u/pmigdal
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.