Algorithm + Strategy = Parallelism

The process of writing large parallel programs is complicated by the need to specify both the parallel behaviour of the program and the algorithm that is to be used to compute its result This paper introduces evaluation strategies lazy higher order functions that control the parallel evaluation of non strict functional languages Using evaluation strategies it is possible to achieve a clean separation between algorithmic and behavioural code The result is enhanced clarity and shorter parallel programs Evaluation strategies are a very general concept this paper shows how they can be used to model a wide range of commonly used programming paradigms including divide and conquer pipeline parallelism producer consumer parallelism and data oriented par allelism Because they are based on unrestricted higher order functions they can also capture irregular parallel structures Evaluation strategies are not just of theoretical interest they have evolved out of our experience in parallelising several large scale parallel applications where they have proved invaluable in helping to manage the complexities of parallel behaviour These applications are described in detail here The largest application we have studied to date Lolita is a line natural language parser Initial results show that for these programs we can achieve acceptable parallel performance while incurring minimal overhead for using evaluation strategies Writing Parallel Programs While it is hard to write good sequential programs it can be considerably harder to write good parallel ones At Glasgow we have worked on several fairly large parallel programming projects and have slowly and sometimes painfully developed a methodology for parallelising sequential programs The essence of the problem facing the parallel programmer is that in addition to specifying what value the program should compute explicitly parallel programs y This work is supported by the UK EPSRC Engineering and Physical Science Research Council AQUA and Parade grants