Optimizing communication for array operations on message-passing multicomputers

Whole array operations and array section operations are important features of many data-parallel languages. Efficient implementation of these operations on distributed-memory multicomputers is critical to the scalability and high-performance of data-parallel programs. We present an approach for analyzing communication patterns induced by array operations and for scheduling message flow based on the information. Our scheduling algorithm guarantees contention-free data transfer and utilizes network resources optimally. It incurs little overhead and is suitable to be used in compilers and in runtime libraries. We also present simulation results that demonstrate the algorithm´s superiority to the asynchronous transfer mode that is commonly used for this type of communication