Accelerate Non-unit Stride Convolutions with Winograd Algorithms

Junhao Pan, Deming Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

While computer vision tasks target increasingly challenging scenarios, the need for real-time processing of images rises as well, requiring more efficient methods to accelerate convolutional neural networks. For unit stride convolutions, we use FFT-based methods and Winograd algorithms to compute matrix convolutions, which effectively lower the computing complexity by reducing the number of multiplications. For non-unit stride convolutions, we usually cannot directly apply those algorithms to accelerate the computations. In this work, we propose a novel universal approach to construct the non-unit stride convolution algorithms for any given stride and filter sizes from Winograd algorithms. Specifically, we first demonstrate the steps to decompose an arbitrary convolutional kernel and apply the Winograd algorithms separately to compute non-unit stride convolutions.We then present the derivation of this method and proof by construction to confirm the validity of this approach. Finally, we discuss the minimum number of multiplications and additions necessary for the non-unit stride convolutions and evaluate the performance of the decomposed Winograd algorithms. From our analysis of the computational complexity, the new approach can benefit from 1.5x to 3x fewer multiplications. In our experiments in real DNN layers, we have acquired around 1.3x speedup (Told / Tnew) of the Winograd algorithms against the conventional convolution algorithm in various experiment settings.

Original languageEnglish (US)
Title of host publicationProceedings of the 26th Asia and South Pacific Design Automation Conference, ASP-DAC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages358-364
Number of pages7
ISBN (Electronic)9781450379991
DOIs
StatePublished - Jan 18 2021
Event26th Asia and South Pacific Design Automation Conference, ASP-DAC 2021 - Virtual, Online, Japan
Duration: Jan 18 2021Jan 21 2021

Publication series

NameProceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC

Conference

Conference26th Asia and South Pacific Design Automation Conference, ASP-DAC 2021
CountryJapan
CityVirtual, Online
Period1/18/211/21/21

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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