A high resolution parallel legendre transform algorithm
Proceedings of the 1st International Conference on Supercomputing
Journal of Parallel and Distributed Computing - Special issue on tools and methods for visualization of parallel systems and computations
Performance visualisation in a portable parallel programming environment
Proceedings of the workshop on performance measurement and visualization on Performance measurement and visualization of parallel systems
Experimental analysis of parallel systems: techniques and open problems
Proceedings of the 7th international conference on Computer performance evaluation : modelling techniques and tools: modelling techniques and tools
Waiting time analysis and performance visualization in Carnival
SPDT '96 Proceedings of the SIGMETRICS symposium on Parallel and distributed tools
Performance improvement through overhead analysis: a case study in molecular dynamics
ICS '97 Proceedings of the 11th international conference on Supercomputing
SUIF Explorer: an interactive and interprocedural parallelizer
Proceedings of the seventh ACM SIGPLAN symposium on Principles and practice of parallel programming
A comparative analysis of four parallelisation schemes
ICS '99 Proceedings of the 13th international conference on Supercomputing
FINESSE: a prototype feedback-guided performance enhancement system
EURO-PDP'00 Proceedings of the 8th Euromicro conference on Parallel and distributed processing
Deep Start: A Hybrid Strategy for Automated Performance Problem Searches
Euro-Par '02 Proceedings of the 8th International Euro-Par Conference on Parallel Processing
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Automatic parallelisation tools implement sophisticated tactics for analysing and transforming application codes but, typically, their "one-step" strategy for finding a "good" parallel implementation remains naïve. In contrast, successful experts at parallelisation explore interesting parts of the space of possible implementations. FINESSE is an environment which supports this exploration by automating many of the tedious steps associated with experiment planning and execution and with the analysis of performance. FINESSE also harnesses the sophisticated techniques provided by automatic compilation tools to provide feedback to the user which can be used to guide the exploration. This paper briefly describes FINESSE and presents evidence for its effectiveness. The latter has been gathered from the experiences of a small number of users, both expert and non-expert, during their parallelisation efforts on a set of compute-intensive, kernel test codes. The evidence lends support to the hypothesis that users of FINESSE can find implementations that achieve performance comparable with that achieved by expert programmers, but in a shorter time.