Reducing overheads of local communications in fine-grain parallel computation

For fine-grain computation to be effective, the cost of communications between the large number of subtasks should be minimized. In this paper we present an optimization technique which reduces overheads of communications between local subtasks by bypassing the network interface and transferring data directly from memory or registers to memory. On average, the optimization results in 35.6% improvement in total execution time on instruction-level simulations with six benchmark programs from 1 to 32 nodes.