Profile-Guided Automatic Inline Expansion for C Programs

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryNational Science Foundation / MIP-8809478NCRAMD 29K Advanced Processor Development DivisionNational Aeronautics and Space Administration / NASA NAG 1-61

Efficient Instruction Sequencing with Inline Target Insertion

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryNational Science Foundation / MIP-8809478NCRNational Aeronautics and Space Administration / NASA NAG 1-613Office of Naval Research / N00014-88-K-065

The Importance of Prepass Code Scheduling for Superscalar and Superpipelined Processors

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryNational Science Foundation / MIP-8809478NCRAMD 29K Advanced Processor Development DivisionNational Aeronautics and Space Administration / NASA NAG 1-613U.S. Department of Energy / DOE DE-FGO2-85ER25001IBM Corporatio

The Effect of Code Expanding Optimizations on Instruction Cache Design

Coordinated Science Laboratory was formerly known as Control Systems LaboratoryNational Science Foundation / MIP-8809478NCRAMD 29K Advanced Processor Development DivisionNational Aeronautics and Space Administration / NASA NAG 1-613N00014-91-J-128

Inline function expansion for compiling c programs

Inline function expansion replaces a function call with the function body. With automatic inline function expansion, programs can be constructed with many small functions to handle complexity and then rely on the compilation to eliminate most of the function calls. Therefore, inline expansion serves a tool for satisfying two conflicting goals: minizing the complexity of the program development and minimizing the function call overhead of program execution. A simple inline expansion procedure is presented which uses profile information to address three critical issues: code expansion, stack expansion, and unavailable function bodies. Experiments show that a large percentage of function calls/returns (about 59%) can be eliminated with a modest code expansion cost (about 17%) for twelve UNIX * programs. * UNIX is a trademark of the AT&T Bell Laboratories. 1

Using Profile Information to Assist Classic Code Optimizations

This paper describes the design and implementation of an optimizing compiler that automatically generates profile information to assist classic code optimizations. This compiler contains two new components, an execution profiler and a profile-based code optimizer, which are not commonly found in traditional optimizing compilers. The execution profiler inserts probes into the input program, executes the input program for several inputs, accumulates profile information and supplies this information to the optimizer. The profile-based code optimizer uses the profile information to expose new optimization opportunities that are not visible to traditional global optimization methods. Experimental results show that the profile-based code optimizer significantly improves the performance of production C programs that have already been optimized by a high-quality global code optimize