Loop fusion and temporal common subexpression elimination in window-based loops

2005 ◽  
Author(s):  
J. Hammes ◽  
A.P.W. Bohm ◽  
C. Ross ◽  
M. Chawathe ◽  
B. Draper ◽  
...  
Keyword(s):  
Loop Fusion ◽  
Common Subexpression Elimination

Energy minimization with loop fusion and multi-functional-unit scheduling for multidimensional DSP

2008 ◽  
Vol 68 (4) ◽  
pp. 443-455 ◽  
Author(s):  
Meikang Qiu ◽  
Edwin H.-M. Sha ◽  
Meilin Liu ◽  
Man Lin ◽  
Shaoxiong Hua ◽  
...  
Keyword(s):  
Energy Minimization ◽  
Functional Unit ◽  
Loop Fusion

scholarly journals Automatically Improving Constraint Models in Savile Row through Associative-Commutative Common Subexpression Elimination

2014 ◽  
pp. 590-605 ◽  
Author(s):  
Peter Nightingale ◽  
Özgür Akgün ◽  
Ian P. Gent ◽  
Christopher Jefferson ◽  
Ian Miguel
Keyword(s):  
Common Subexpression Elimination

Memory requirement optimization with loop fusion and loop shifting

2004 ◽  
Author(s):  
Qubo Hu ◽  
M. Palkovic ◽  
P.G. Kjeldsberg
Keyword(s):  
Memory Requirement ◽  
Loop Fusion

scholarly journals THEMIS: COMPONENT DEPENDENCE METADATA IN ADAPTIVE PARALLEL APPLICATIONS

2001 ◽  
Vol 11 (04) ◽  
pp. 455-470 ◽  
Author(s):  
PAUL H. J. KELLY ◽  
OLAV BECKMANN ◽  
TONY FIELD ◽  
SCOTT B. BADEN
Keyword(s):  
Performance Optimization ◽  
Programming Model ◽  
Data Distribution ◽  
Parallel Applications ◽  
Problem Instance ◽  
Placement Optimization ◽  
Loop Fusion ◽  
Run Time ◽  
Optimization Loop ◽  
Execution Order

This paper describes THEMIS, a programming model and run-time library being designed to support cross-component performance optimization through explicit manipulation of the computation's iteration space at run-time. Each component is augmented with "component dependence metadata", which characterizes the constraints on its execution order, data distribution and memory access order. We show how this supports dynamic adaptation of each component to exploit the available resources, the context in which its operands are generated, and results are used, and the evolution of the problem instance. Using a computational fluid dynamics visualization example as motivation, we show how component dependence metadata provides a framework in which a number of interesting optimizations become possible. Examples include data placement optimization, loop fusion, tiling, memoization, checkpointing and incrementalization.

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