Loop Tiling for Parallelism
Springer Science & Business Media, 31 août 2000 - 256 pages
Loop tiling, as one of the most important compiler optimizations, is beneficial for both parallel machines and uniprocessors with a memory hierarchy. This book explores the use of loop tiling for reducing communication cost and improving parallelism for distributed memory machines. The author provides mathematical foundations, investigates loop permutability in the framework of nonsingular loop transformations, discusses the necessary machineries required, and presents state-of-the-art results for finding communication- and time-minimal tiling choices. Throughout the book, theorems and algorithms are illustrated with numerous examples and diagrams. The techniques presented in Loop Tiling for Parallelism can be adapted to work for a cluster of workstations, and are also directly applicable to shared-memory machines once the machines are modeled as BSP (Bulk Synchronous Parallel) machines.
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algorithm allocated applying approximated array assume Based boundary bounds called canonical Chapter column communication compiler component computation cone Consider consists constructed contains convex defined denoted dependence vector depicted dimension discussed distance vectors distribution element equation exactly example execution extremal rays Fidle Figure fully permutable function given holds illustrated indices inequalities integer iteration space k-th legality Lemma lexicographic linear loop nest mapping matrix memory Minimise nonlocal nonsingular Note obtain operations optimal solution optimal tile optimisation origin parallelepiped tiling parallelism performance points polyhedron polytope present problem processor Proof read-only data received rectangular tiling references represented shape shown in Figure shows simplified solved specified techniques Tfree Theorem tile dependences tile loops tile space tiled code transformation unimodular unique values volume
Page iii - School of Computer Science and Engineering, The University of New South Wales, Sydney, NSW 2052, Australia, Email: firstname.lastname@example.org Abstract.
Page 252 - Static and dynamic evaluation of data dependence analysis techniques. IEEE Transactions on Parallel and Distributed Systems, 7(1 1):1 121-1 132, november 1996.  K. Psarris and K. Kyriakopoulos. An experimental evaluation of data dependence analysis techniques.
Page 252 - GL Nemhauser and LA Wolsey, Integer and Combinatorial Optimization, Interscience Series in Discrete Mathematics and Optimization (John Wiley & Sons, 1988).