Array Operation Synthesis to Optimize HPF Programs

An increasing number of programming languages, such as Fortran 90, HPF, and APL, are providing a rich set of intrinsic array functions and array expressions. These constructs which constitute an important part of data parallel languages provide excellent opportunities for compiler optimizations. The synthesis of consecutive array operations or array expressions into a composite access function of the source arrays at compile time has been shownn2] that it can reduce the redundant data movement, temporary storage usage, and loop synchronization overhead on at shared memory parallel machines with uniform memory accesses. However, it remains open how the synthesis scheme can be incorporated into optimizing HPF programs on distributed memory parallel machines by taking into account communication costs. In this paper, we propose solutions to address this open problem. We rst apply the array synthesis scheme (developed earlier by us for Fortran 90 programs) to HPF programs and demonstrate its performance beneets on distributed memory machines. In addition, to prevent a situation we call \synthesis performance anomaly", we derive a cost model and present an optimal solution based on the cost model to guide the array synthesis process on distributed memory machines. We also show that the optimal problem is NP-hard. Therefore, we develop a practical heuristic algorithm for compilers to devise synthesis strategy on distributed memory machines with HPF programs. Experimental results show signiicant performance improvement over the base codes for HPF code fragments from real applications on a DEC Farm by incorporating our proposed optimizations. The array operation synthesis scheme is demonstrated to be equally eeective for programs running on parallel distributed memory machines.