Reviewers
|
Book & Monographs
|
Conference
|
Contact Us
SEARCH
|
My Profile
|
My Shopping Cart
|
Logout
Home
Publication Ethics
Open Access Policy
Guidelines
Journals
▼pphmjopenaccess.com▼
Engineering
Mathematics
Statistics
All Journals
Submit a Manuscript
Author Login
Author Registration
Forget Password
Journal Menu
Journal Home
Editorial Board
Guidelines for Authors
Indexing
Contents
Contents
Subscribe
Publication Ethics and Publication Malpractice Statement
Content
Volume 19 (2022)
Volume 19, (In Progress)
Pg 1 - 11 (June 2022)
Volume 18 (2019)
Volume 18, Issue 1
Pg 1 - 37 (June 2019)
Volume 17 (2018)
Volume 17, Issue 2
Pg 55 - 74 (December 2018)
Volume 17, Issue 1
Pg 1 - 54 (June 2018)
Volume 16 (2016)
Volume 16, Issue 3-4
Pg 61 - 101 (November 2016)
Volume 16, Issue 1-2
Pg 1 - 60 (May 2016)
Volume 15 (2015)
Volume 15, Issue 1-2
Pg 1 - 55 (November 2015)
Volume 14 (2015)
Volume 14, Issue 2
Pg 59 - 109 (May 2015)
Volume 14, Issue 1
Pg 1 - 57 (February 2015)
Volume 13 (2014)
Volume 13, Issue 2
Pg 73 - 152 (November 2014)
Volume 13, Issue 1
Pg 1 - 72 (August 2014)
Volume 12 (2014)
Volume 12, Issue 2
Pg 61 - 128 (May 2014)
Volume 12, Issue 1
Pg 1 - 60 (February 2014)
Volume 11 (2013)
Volume 11, Issue 2
Pg 51 - 107 (November 2013)
Volume 11, Issue 1
Pg 1 - 50 (August 2013)
Volume 10 (2013)
Volume 10, Issue 2
Pg 77 - 131 (May 2013)
Volume 10, Issue 1
Pg 1 - 76 (February 2013)
Volume 9 (2012)
Volume 9, Issue 2
Pg 83 - 159 (November 2012)
Volume 9, Issue 1
Pg 1 - 82 (August 2012)
Volume 8 (2012)
Volume 8, Issue 2
Pg 69 - 145 (May 2012)
Volume 8, Issue 1
Pg 1 - 67 (February 2012)
Volume 7 (2011)
Volume 7, Issue 2
Pg 99 - 168 (November 2011)
Volume 7, Issue 1
Pg 1 - 97 (August 2011)
Volume 6 (2011)
Volume 6, Issue 2
Pg 105 - 204 (May 2011)
Volume 6, Issue 1
Pg 1 - 104 (February 2011)
Volume 5 (2010)
Volume 5, Issue 2
Pg 131 - 263 (November 2010)
Volume 5, Issue 1
Pg 1 - 129 (August 2010)
Volume 4 (2010)
Volume 4, Issue 2
Pg 93 - 184 (May 2010)
Volume 4, Issue 1
Pg 1 - 92 (February 2010)
Volume 3 (2009)
Volume 3, Issue 3
Pg 175 - 266 (November 2009)
Volume 3, Issue 2
Pg 87 - 174 (July 2009)
Volume 3, Issue 1
Pg 1 - 85 (March 2009)
Volume 2 (2008)
Volume 2, Issue 3
Pg 201 - 284 (November 2008)
Volume 2, Issue 2
Pg 97 - 199 (July 2008)
Volume 2, Issue 1
Pg 1 - 96 (March 2008)
Volume 1 (2007)
Volume 1, Issue 3
Pg 189 - 283 (November 2007)
Volume 1, Issue 2
Pg 105 - 187 (July 2007)
Volume 1, Issue 1
Pg 1 - 104 (March 2007)
Categories
▼pphmjopenaccess.com▼
Engineering
Mathematics
Statistics
All Journals
Advances in Computer Science and Engineering
Advances in Computer Science and Engineering
Volume 7, Issue 1, Pages 1 - 24 (August 2011)
A GENERALIZED METHOD FOR REALIZING PARTIAL REDUNDANCY ELIMINATION FOR NORMAL FORMS IN STATIC SINGLE ASSIGNMENT FORMS
Masataka Sassa, Takanori Imahashi and Yo Ito
Abstract:
Partial Redundancy Elimination (PRE) is an effective optimization for eliminating partially redundant expressions and includes the effects of common subexpression elimination and hoisting loop invariant expressions. There have been some previous attempts to realize PRE on the Static Single Assignment (SSA) form, which is a suitable intermediate form for optimization. However, such attempts are generally difficult because of the uniqueness of variable names in the SSA form. For example, a variable that is used in several contexts in the normal form may be assigned a new name for each context in the SSA form, so it is difficult to identify the same variables in the two forms. To handle such problems, previous methods performed complicated processing by using special data structures.
To deal with this problem, we pay attention to the so-called Conventional SSA (CSSA) form and phi congruence class (pcc). Using these concepts, we can identify the same variables in the normal form and the SSA form. We therefore propose a method for transforming PRE algorithms for the normal form to those for the SSA form. This transformation is a universal one, so, in principle, it can transform any PRE algorithm that has ordinary processes (selecting insertion points and inserting expressions, and replacing expressions) to the SSA form, without changing the framework of the original PRE algorithm, independently of the algorithm. Finally, as an experiment, we apply this method to Lazy Code Motion (LCM), which is a representative PRE algorithm. We confirmed that the transformed LCM in the SSA form performs PRE correctly and produces object code with the same efficiency as PRE in normal form.
Keywords and phrases:
compiler optimization, static single assignment form, partial redundancy elimination.
Number of Downloads:
288 |
Number of Views:
678
Next
P-ISSN: 0973-6999
Journal Stats
Publication count:
171
Citation count (Google Scholar):
0
h10-index (Google Scholar):
0
h-index (Google Scholar):
0
Downloads :
54482
Views:
146976
Downloads/publish articles:
318.61
Citations (Google Scholar)/publish articles:
0
This website is best viewed at 1024x768 or higher resolution with Microsoft Internet Explorer 6 or newer.