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Benchmarking TorchVision ResNet18 on EC2 NVIDIA GPU with TensorRT and Amazon SageMaker Neo

francescopochetti.com · published 30 November 2022

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https://github.com/FraPochetti/KagglePlaygrounds/tree/master/aws_latency_benchmarks/pytorch
github.com
https://github.com/pytorch/TensorRT/tree/master/notebooks
github.com
https://catalog.ngc.nvidia.com/orgs/nvidia/containers/pytorch
catalog.ngc.nvidia.com
https://developer.nvidia.com/cuda-11-6-0-download-archive?target_os=Linux&target_arch=x86_64&Distribution=Ubuntu&target_version=18.04&target_type=runfile_local
developer.nvidia.com
https://developer.nvidia.com/cuda-10.2-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=1804&target_type=runfilelocal
developer.nvidia.com
https://towardsdatascience.com/installing-multiple-cuda-cudnn-versions-in-ubuntu-fcb6aa5194e2
towardsdatascience.com
https://neo-ai-dlr.readthedocs.io/en/latest/install.html
neo-ai-dlr.readthedocs.io
https://docs.aws.amazon.com/sagemaker/latest/dg/neo-getting-started-edge-step3.html
docs.aws.amazon.com
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