Procedure Restructuring for Ambitious Optimization: Using demand-driven, partial, and heuristics-guided inlining to improve the scalability of region-based optimization - Image 1

£69.00

LAP Lambert Academic Publishing Procedure Restructuring for Ambitious Optimization: Using demand-driven, partial, and heuristics-guided inlining to improve the scalability of region-based optimization

Name: Procedure Restructuring for Ambitious Optimization: Using demand-driven, partial, and heuristics-guided inlining to improve the scalability of region-based optimization
Brand: LAP Lambert Academic Publishing
Price: 69.0 GBP
Availability: InStock

Introduction to Programming

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Description

Compiler optimization of computer programs is necessary to exploit the features of the target architecture while masking the details of the architecture from the programmer. The continuing trends toward instruction-level parallel computers and larger programs promote and necessitate the development of optimization techniques which increase available parallelism simultaneously with controlling compilation time and memory usage. These state-of-the-art techniques are referred to as ambitious optimization techniques. Well-known approaches to increasing the scope of optimization without sacrificing precision of analysis include procedure inlining and cloning. Region-based compilation seeks to improve the scope of optimization to improve code quality while bounding optimization costs associated with inlining and cloning. This book develops and explores scalable procedure restructuring techniques that use demand-driven inlining and region-based optimizations, focused on the application of heuristics.

Product Specifications

Brand: LAP Lambert Academic Publishing
Format: paperback
ASIN: 3838345061
Category: Books > Subjects > Computing & Internet > Programming > Introduction to Programming
Domain: Amazon UK
Release Date: 19 February 2010
Listed Since: 24 February 2010

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LAP Lambert Academic Publishing Procedure Restructuring for Ambitious Optimization: Using demand-driven, partial, and heuristics-guided inlining to improve the scalability of region-based optimization

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