Classic loop unrolling allows to increase the performance of sequential loops by reducing the overheads of the non-computational parts of the loop. Unfortunately, when the loop con...
Roger Ferrer, Alejandro Duran, Xavier Martorell, E...
This paper improves our previous research effort [1] by providing an efficient method for kernel loop unrolling minimisation in the case of already scheduled loops, where circular...
Abstract. Current hardware trends place increasing pressure on programmers and tools to optimize scientific code. Numerous tools and techniques exist, but no single tool is a pana...
Abstract. Intervals are a new, higher-level primitive for parallel programming with which programmers directly construct the program schedule. Programs using intervals can be stati...
Programming heterogeneous parallel computer systems is notoriously difficult, but MIMD models have proven to be portable across multi-core processors, clusters, and massively paral...
Abstract. Many parallel programs are written in a single-program, multipledata (SPMD) style, in which synchronization is provided using collective operations that all threads execu...
PC grids represent massive computation capacity at a low cost, but are challenging to employ for parallel computing because of variable and unpredictable performance and availabili...
Nagarajan Kanna, Jaspal Subhlok, Edgar Gabriel, Es...
The advent of multicores presents a promising opportunity for exploiting fine grained parallelism present in programs. Programs parallelized in the above fashion, typically involv...
Abstract. In this paper, we describe transformation recipes, which provide a high-level interface to the code transformation and code generation capability of a compiler. These rec...
Mary W. Hall, Jacqueline Chame, Chun Chen, Jaewook...
Abstract. We describe Fastpath, a system for speculative parallelization of sequential programs on conventional multicore processors. Our system distinguishes between the lead thre...
Michael F. Spear, Kirk Kelsey, Tongxin Bai, Luke D...