Iteration Space Slicing for Locality

2000 ◽  
pp. 164-184 ◽  
Author(s):  
William Pugh ◽  
Evan Rosser
Keyword(s):  
Iteration Space

scholarly journals A sparse iteration space transformation framework for sparse tensor algebra

2020 ◽  
Vol 4 (OOPSLA) ◽  
pp. 1-30 ◽  
Author(s):  
Ryan Senanayake ◽  
Changwan Hong ◽  
Ziheng Wang ◽  
Amalee Wilson ◽  
Stephen Chou ◽  
...  
Keyword(s):  
Tensor Algebra ◽  
Iteration Space ◽  
Space Transformation

Polygonal Iteration Space Partitioning

2017 ◽  
pp. 121-136
Author(s):  
Aniket Shivam ◽  
Alexandru Nicolau ◽  
Alexander V. Veidenbaum ◽  
Mario Mango Furnari ◽  
Rosario Cammarota
Keyword(s):  
Space Partitioning ◽  
Iteration Space

PROGRAM OPTIMIZATION BASED ON COMPILE-TIME CACHE PERFORMANCE PREDICTION

1996 ◽  
Vol 06 (01) ◽  
pp. 173-184 ◽  
Author(s):  
WESLEY K. KAPLOW ◽  
BOLESLAW K. SZYMANSKI
Keyword(s):  
Performance Prediction ◽  
Parallel Program ◽  
Program Optimization ◽  
Cache Performance ◽  
Processor Architectures ◽  
Loop Nests ◽  
Time Optimization ◽  
Iteration Space ◽  
Hit Rates

We present a novel, compile-time method for determining the cache performance of the loop nests in a program. The cache hit-rates are produced by applying the reference string, determined during compilation, to an architecturally parameterized cache simulator. We also describe a heuristic that uses this method for compile-time optimization of loop ranges in iteration-space blocking. The results of the loop program optimizations are presented for different parallel program benchmarks and various processor architectures, such as IBM SP1 RS/6000, the SuperSPARC, and the Intel 1860.

Cache-aware iteration space partitioning

2008 ◽  
Author(s):  
Arun Kejariwal ◽  
Alexandru Nicolau ◽  
Utpal Banerjee ◽  
Alexander V. Veidenbaum ◽  
Constantine D. Polychronopoulos
Keyword(s):  
Space Partitioning ◽  
Iteration Space

A layout-conscious iteration space transformation technique

2001 ◽  
Vol 50 (12) ◽  
pp. 1321-1335 ◽  
Author(s):  
M. Kandemir ◽  
J. Ramanujam ◽  
A. Choudhary ◽  
P. Banerjee
Keyword(s):  
Transformation Technique ◽  
Iteration Space ◽  
Space Transformation

GENERALISING THE UNIMODULAR APPROACH TO RESTRUCTURE IMPERFECTLY NESTED LOOPS

1996 ◽  
Vol 06 (03) ◽  
pp. 401-414
Author(s):  
Jingling Xue
Keyword(s):  
Code Generation ◽  
Lexicographic Order ◽  
Generation Algorithm ◽  
Loop Nest ◽  
Loop Nests ◽  
Iteration Space ◽  
New Concepts ◽  
Affine Constraints ◽  
Nested Loops ◽  
Unimodular Transformations

Although overcoming some limitations of the generate-and-test approach, unimodular transformations are limited to perfect loop nests only. Extending the unimodular approach, this paper describes a framework that enables the use of unimodular transformations to restructure imperfect loop nests. The concepts used previously for perfect loop nests, such as iteration vector, iteration space and lexicographic order, are generalised and some new concepts like preorder tree are introduced. Multiple unimodular transformations are allowed, one each statement in the loop nest. A code generation algorithm is provided that produces a possibly imperfect loop nest to scan an iteration space that is given as a union of sets of affine constraints.

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