efficient inferenceCUDATensorRTIn the recent years, there has been a significant growth of interest in real-world systems based on deep neural networks (DNNs). These systems typically incorporate multiple DNNs running simultaneously. In this paper we propose a novel approach of multi-DNN execution ...
TensorRT工具箱使用KL散度来最小化量化前模型的数据编码分布和量化后模型的数据编码分布的差异,通过最小化两种数据分布的差异,即找到使得KL散度最小的点其实就能找到一个比较好裁剪范围 以resnet-152为例,通过KL散度可以估计出裁剪范围如下图竖线表示 8-bit-Inference-with-TensorRT 现在常用的做法是使用MSE去找到裁剪...
简介:量化理解(Google量化白皮书《Quantizing deep convolutional networks for efficient inference: A whitepaper》) 简介:量化理解(Google量化白皮书《Quantizing deep convolutional networks for efficient inference: A whitepaper》) 可以说这篇博客是对Google量化白皮书的完整解读,篇幅较长,可以收藏慢慢阅读。笔者在翻译...
vLLM is a fast and easy-to-use library for LLM inference and serving. Originally developed in theSky Computing Labat UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry. vLLM is fast with: ...
vLLM is a fast and easy-to-use library for LLM inference and serving. Originally developed in theSky Computing Labat UC Berkeley, vLLM has evolved into a community-driven project with contributions from both academia and industry. vLLM is fast with: ...
8-bit Inference with TensorRT [Szymon Migacz, 2017] Optimal Clipping and Magnitude-aware Differentiation for Improved Quantization-aware Training [Sakr et al., ICML 2022] XNOR-Net: ImageNet Classification using Binary Convolutional Neural Networks [Rastegari et al., ECCV 2016] ...
2 Extreme compression of sentence-transformerranker models: faster inference, longer battery life, and less storage on edge devices 标题:句子transformer排序器模型的极端压缩:更快的推理、更长的电池寿命和更少的边缘设备存储 文章链接:https://arxiv.org/abs/2207.12852 ...
The native visual attention model as the backbone network is not well suited for common dense prediction tasks such as object detection and semantic segmentation. In addition, compared with convolutional neural networks, ViT usually requires more computation and slower inference speed, which is not con...
Graph optimization plays an important role in reducing time and resources for training and inference of AI models. One of the most important functionalities of
This post is part of Model Mondays, a program focused on enabling easy access to state-of-the-art community and NVIDIA-built models. These models are optimized by NVIDIA using TensorRT-LLM and offered as .nemo files for easy customization and deployment. ...