NDLI: A Model-Based Framework: An Approach for Profit-Driven Optimization

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Virtual Machine Learning: Thinking like a Computer Architect

Context Threading: A Flexible and Efficient Dispatch Technique for Virtual Machine Interpreters

Automatically Reducing Repetitive Synchronization with a Just-in-Time Compiler for Java

Compile-Time Concurrent Marking Write Barrier Removal

Collecting and Exploiting High-Accuracy Call Graph Profiles in Virtual Machines

Effective Adaptive Computing Environment Management via Dynamic Optimization

Maintaining Consistency and Bounding Capacity of Software Code Caches

Performance of Runtime Optimization on BLAST

Optimizing Sorting with Genetic Algorithms

Combining Models and Guided Empirical Search to Optimize for Multiple Levels of the Memory Hierarchy

Predicting Unroll Factors Using Supervised Classification

Multicores from the Compiler's Perspective: A Blessing or a Curse?

Optimizing Address Code Generation for Array-Intensive DSP Applications

Efficient SIMD Code Generation for Runtime Alignment and Length Conversion

Superword-Level Parallelism in the Presence of Control Flow

Compiler Managed Dynamic Instruction Placement in a Low-Power Code Cache

Phase-Aware Remote Profiling

Practical Path Profiling for Dynamic Optimizers

A Programmable Hardware Path Profiler

Automatic Generation of High-Performance Trace Compressors

SWIFT: Software Implemented Fault Tolerance

Building Intrusion-Tolerant Secure Software

A Progressive Register Allocator for Irregular Architectures

A General Compiler Framework for Speculative Optimizations Using Data Speculative Code Motion

Practical and Accurate Low-Level Pointer Analysis

Reactive Techniques for Controlling Software Speculation

A Model-Based Framework: An Approach for Profit-Driven Optimization

Sentinel PRE: Hoisting beyond Exception Dependency with Dynamic Deoptimization

Author Index

A Model-Based Framework: An Approach for Profit-Driven Optimization

Content Provider	ACM Digital Library
Author	Zhao, Min Childers, Bruce R. Soffa, Mary Lou
Abstract	Although optimizations have been applied for a number of years to improve the performance of software, problems that have been long-standing remain, which include knowing what optimizations to apply and how to apply them. To systematically tackle these problems, we need to understand the properties of optimizations. In our current research, we are investigating the profitability property, which is useful for determining the benefit of applying an optimization. Due to the high cost of applying optimizations and then experimentally evaluating their profitability, we use an analytic model framework for predicting the profitability of optimizations. In this paper, we target scalar optimizations, and in particular, describe framework instances for Partial Redundancy Elimination (PRE) and Loop Invariant Code Motion (LICM). We implemented the framework for both optimizations and compare profit-driven PRE and LICM with a heuristic-driven approach. Our experiments demonstrate that a model-based approach is effective and efficient in that it can accurately predict the profitability of optimizations with low overhead. By predicting the profitability using models, we can selectively apply optimizations. The model-based approach does not require tuning of parameters used in heuristic approaches and works well across different code contexts and optimizations.
Starting Page	317
Ending Page	327
Page Count	11
File Format	PDF
ISBN	076952298X
DOI	10.1109/CGO.2005.2
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2005-03-20
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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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
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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

A model-based framework: An approach for profit-driven optimization (2005)

A model-based framework: an approach for profit-driven optimization (2005)

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