NDLI: Image Perforation: Automatically Accelerating Image Pipelines by Intelligently Skipping Samples

Content Provider	ACM Digital Library
Author	Lou, Liming Lawrence, Jason Barnes, Connelly Nguyen, Paul
Copyright Year	2016
Description	Author Affiliation: University of Virginia and Google Research(Shandong university and university of virginia (lou, Liming; Barnes, Connelly); University of virginia (nguyen, Paul; Lawrence, Jason))
Abstract	Image pipelines arise frequently in modern computational photography systems and consist of multiple processing stages where each stage produces an intermediate image that serves as input to a future stage. Inspired by recent work on loop perforation [Sidiroglou-Douskos et al. 2011], this article introduces image perforation, a new optimization technique that allows us to automatically explore the space of performance-accuracy tradeoffs within an image pipeline. Image perforation works by transforming loops over the image at each pipeline stage into coarser loops that effectively “skip” certain samples. These missing samples are reconstructed for later stages using a number of different interpolation strategies that are relatively inexpensive to perform compared to the original cost of computing the sample. We describe a genetic algorithm for automatically exploring the resulting combinatoric search space of which loops to perforate, in what manner, by how much, and using which reconstruction method. We also present a prototype language that implements image perforation along with several other domain-specific optimizations and show results for a number of different image pipelines and inputs. For these cases, image perforation achieves speedups of 2 × --10 × with acceptable loss in visual quality and significantly outperforms loop perforation.
Starting Page	1
Ending Page	14
Page Count	14
File Format	PDF
ISSN	07300301
e-ISSN	15577368
DOI	10.1145/2904903
Volume Number	35
Issue Number	5
Journal	ACM Transactions on Graphics (TOG)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-09-02
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Image filters Compilers Optimizations
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design

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