Keyword Analysis & Research: tensorrt

nvidia.com

https://developer.nvidia.com/tensorrt

TensorRT Features 1. Reduced Precision Maximizes throughput with FP16 or INT8 by quantizing models while preserving accuracy 2. Layer and Tensor Fusion Optimizes use of GPU memory and bandwidth by fusing nodes in a kernel 3. Kernel Auto-Tuning Selects best data layers and algorithms based on the target GPU platform 4. Dynamic Tensor Memory

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github.com

https://github.com/nvidia/TensorRT

This repository contains the Open Source Software (OSS) components of NVIDIA TensorRT. Included are the sources for TensorRT plugins and parsers (Caffe and ONNX), as well as sample applications demonstrating usage and capabilities of the TensorRT platform. These open source software components are a subset of the TensorRT General Availability (GA) ...

This repository contains the Open Source Software (OSS) components of NVIDIA TensorRT. Included are the sources for TensorRT plugins and parsers (Caffe and ONNX), as well as sample applications demonstrating usage and capabilities of the TensorRT platform. These open source software components are a subset of the TensorRT General Availability (GA) ...

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roboflow.com

https://blog.roboflow.com/what-is-tensorrt/

Sep 09, 2021 · TensorRT is a machine learning framework that is published by Nvidia to run inference that is machine learning inference on their hardware. TensorRT is highly optimized to run on NVIDIA GPUs. It's likely the fastest way to run a model at the moment. If you Want to Convert your Model to TensorRT, How Do You Do that?

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ibm.com

https://www.ibm.com/docs/en/wmlce/1.6.2?topic=frameworks-getting-started-tensorrt

Mar 14, 2019 · TensorRT is a C++ library provided by NVIDIA which focuses on running pre-trained networks quickly and efficiently for inferencing. Full technical details on TensorRT can be found in the NVIDIA TensorRT Developers Guide. Installing TensorRT Support for TensorRT in PyTorch is enabled by default in WML CE.

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nvidia.com

https://catalog.ngc.nvidia.com/orgs/nvidia/containers/tensorrt

May 03, 2022 · What Is TensorRT? The core of NVIDIA TensorRT is a C++ library that facilitates high-performance inference on NVIDIA graphics processing units (GPUs). TensorRT takes a trained network, which consists of a network definition and a set of trained parameters, and produces a highly optimized runtime engine that performs inference for that network.

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nvidia.com

https://docs.nvidia.com/deeplearning/tensorrt/index.html

Apr 28, 2022 · NVIDIA TensorRT is a C++ library that facilitates high performance inference on NVIDIA GPUs. It is designed to work in connection with deep learning frameworks that are commonly used for training.

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nvidia.com

https://docs.nvidia.com/deeplearning/tensorrt/install-guide/index.html

Mar 15, 2022 · The core of NVIDIA® TensorRT™ is a C++ library that facilitates high-performance inference on NVIDIA graphics processing units (GPUs). TensorRT takes a trained network, which consists of a network definition and a set of trained parameters, and produces a highly optimized runtime engine that performs inference for that network.

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github.com

https://github.com/NVIDIA/TensorRT/releases

TensorRT OSS release corresponding to TensorRT 8.2.1.8 GA release. Updates since TensorRT 8.2.0 EA release. Please refer to the TensorRT 8.2.1 GA release notes for more information. ONNX parser v8.2.1 Removed duplicate constant layer checks that caused some performance regressions Fixed expand dynamic shape calculations

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github.io

https://nvidia.github.io/Torch-TensorRT/

Torch-TensorRT operates as a PyTorch extention and compiles modules that integrate into the JIT runtime seamlessly. After compilation using the optimized graph should feel no different than running a TorchScript module.

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