Sagar Shelke – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2023-06-09T20:26:40Z http://www.open-lab.net/blog/feed/ Sagar Shelke <![CDATA[Sparsity in INT8: Training Workflow and Best Practices for NVIDIA TensorRT Acceleration]]> http://www.open-lab.net/blog/?p=64658 2023-06-09T20:26:40Z 2023-05-16T16:00:00Z The training stage of deep learning (DL) models consists of learning numerous dense floating-point weight matrices, which results in a massive amount of...]]>

The training stage of deep learning (DL) models consists of learning numerous dense floating-point weight matrices, which results in a massive amount of floating-point computations during inference. Research has shown that many of those computations can be skipped by forcing some weights to be zero, with little impact on the final accuracy. In parallel to that, previous posts have shown that…

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Sagar Shelke <![CDATA[Accelerating Quantized Networks with the NVIDIA QAT Toolkit for TensorFlow and NVIDIA TensorRT]]> http://www.open-lab.net/blog/?p=48838 2023-04-04T17:00:05Z 2022-06-16T17:28:18Z We��re excited to announce the NVIDIA Quantization-Aware Training (QAT) Toolkit for TensorFlow 2 with the goal of accelerating the quantized networks with...]]>

Join the NVIDIA Triton and NVIDIA TensorRT community to stay current on the latest product updates, bug fixes, content, best practices, and more. We’re excited to announce the NVIDIA Quantization-Aware Training (QAT) Toolkit for TensorFlow 2 with the goal of accelerating the quantized networks with NVIDIA TensorRT on NVIDIA GPUs. This toolkit provides you with an easy-to-use API to quantize…

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