scholarly journals Statement-level communication-free partitioning techniques for parallelizing compilers

1997 ◽  
pp. 389-403 ◽  
Author(s):  
Kuei-Ping Shih ◽  
Jang-Ping Sheu ◽  
Chua-Huang Huang
Keyword(s):  
Parallelizing Compilers

REVIEW OF PARALLEL TECHNIQUES AND ITS IMPLICATION FOR JAVA

2010 ◽  
Vol 19 (07) ◽  
pp. 1465-1481
Author(s):  
SUN YU ◽  
WEI ZHANG
Keyword(s):  
Garbage Collection ◽  
Virtual Machines ◽  
State Of The Art ◽  
Parallelizing Compilers ◽  
Research Topics ◽  
Multiprocessor Architectures ◽  
Program Parallelization ◽  
Java Programs ◽  
Java Virtual Machines ◽  
Parallel Techniques

This paper surveys the state-of-the-art parallel techniques for multiprocessor architectures, and studies its implication for Java programs, which are typically compiled at run-time. First, this paper overviews basic techniques of program parallelization in traditional static compilers, followed by a survey of successful parallelizing compilers. Then this paper introduces the latest research topics in this area, particularly focusing on the efforts of combining parallelizing techniques with Java virtual machines, including parallel compilation and parallel real-time garbage collection. Finally, this paper summaries the opportunities and challenges of parallelizing Java computing on multicore platforms.

scholarly journals Interprocedural Induction Variable Analysis

2003 ◽  
Vol 14 (03) ◽  
pp. 405-423
Author(s):  
Peiyi Tang ◽  
Pen-Chung Yew
Keyword(s):  
Symbolic Analysis ◽  
Data Dependence ◽  
Parallelizing Compilers ◽  
Recursive Procedure ◽  
Induction Variables ◽  
Variable Analysis

Induction variable analysis is an important part of the symbolic analysis in parallelizing compilers. Induction variables can be formed by for or [Formula: see text] loops within procedures or loops of recursive procedure calls. This paper presents an algorithm to find induction variables in formal parameters of procedures caused by recursive procedure calls. The compile-time knowledge of induction variables in formal parameters is essential to summarize array sections to be used for data dependence test and parallelization.

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