Tamp: A Library for Compact Deep Neural Networks with Structured Matrices

Bingchen Gong, Brendan Jou, Felix X. Yu, Shih-Fu Chang
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引用次数: 1

Abstract

We introduce Tamp, an open source C++ library for reducing the space and time costs of deep neural network models. In particular, Tamp implements several recent works which use structured matrices to replace unstructured matrices which are often bottlenecks in neural networks. Tamp is also designed to serve as a unified development platform with several supported optimization back-ends and abstracted data types. This paper introduces the design and API and also demonstrates the effectiveness with experiments on public datasets.
一个具有结构化矩阵的紧凑深度神经网络库
我们介绍了一个开源的c++库,用于减少深度神经网络模型的空间和时间成本。特别是,Tamp实现了一些最近的工作,这些工作使用结构化矩阵来取代非结构化矩阵,而非结构化矩阵通常是神经网络的瓶颈。Tamp还被设计成一个统一的开发平台,具有几个支持的优化后端和抽象数据类型。本文介绍了该方法的设计和API,并在公共数据集上进行了实验验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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