NDLI: Predicting the impact of optimizations for embedded systems

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Predicting the impact of optimizations for embedded systems

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Predicting the impact of optimizations for embedded systems

Content Provider	ACM Digital Library
Author	Zhao, Min Soffa, Mary Lou Childers, Bruce
Abstract	When applying optimizations, a number of decisions are made using fixed strategies, such as always applying an optimization if it is applicable, applying optimizations in a fixed order and assuming a fixed configuration for optimizations such as tile size and loop unrolling factor. While it is widely recognized that these fixed strategies may not be the most appropriate for producing high quality code, especially for embedded systems, there are no general and automatic strategies that do otherwise. In this paper, we present a framework that enables these decisions to be made based on predicting the impact of an optimization, taking into account resources and code context. The framework consists of optimization models, code models and resource models, which are integrated for predicting the impact of applying optimizations. Because data cache performance is important to embedded codes, we focus on cache performance and present an instance of the framework for cache performance in this paper. Since most opportunities for cache improvement come from loop optimizations, we describe code, optimization and cache models tailored to predict the impact of applying loop optimizations for data locality. Experimentally we demonstrate the need to selectively apply optimizations and show the performance benefit of our framework in predicting when to apply an optimization. We also show that our framework can be used to choose the most beneficial optimization when a number of optimizations can be applied to a loop nest. And lastly, we show that we can use the framework to combine optimizations on a loop nest.
Starting Page	1
Ending Page	11
Page Count	11
File Format	PDF
ISBN	1581136471
DOI	10.1145/780732.780734
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2003-06-11
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Embedded systems Optimizing compilers Optimization models Prediction Resource models Code models Loop optimizations
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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