A data locality optimizing algorithm
PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
Compiling for numa parallel machines
Compiling for numa parallel machines
Unifying data and control transformations for distributed shared-memory machines
PLDI '95 Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation
The Omega Library interface guide
The Omega Library interface guide
Improving data locality with loop transformations
ACM Transactions on Programming Languages and Systems (TOPLAS)
Custom Memory Management Methodology: Exploration of Memory Organisation for Embedded Multimedia System Design
High Performance Compilers for Parallel Computing
High Performance Compilers for Parallel Computing
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Optimizing array accesses is extremely critical in embedded computingas many embedded applications make use of arrays (in formof images, video frames, etc). Previous research considered bothloop and data transformations for improving array accesses. However,data transformations considered were mostly limited to lineardata transformations and array interleaving. In this paper, we introducetwo data transformations: array decomposition (breaking upa large array into multiple smaller arrays) and array composition(combining multiple small arrays into a single large array). Thispaper discusses that it is feasible to implement these optimizationswithin an optimizing compiler.