Mapping stream programs onto heterogeneous multiprocessor systems

This paper presents a partitioning and allocation algorithm for an iterative stream compiler, targeting heterogeneous multiprocessors with constrained distributed memory and any communications topology. We introduce a novel definition of connectedness that enables the algorithm to model the capabilities of the compiler. The algorithm uses convexity and connectedness constraints to produce partitions that are easier to compile and require short pipelines. Software pipelining is an effective transformation, but it increases memory footprint and latency, and has a startup overhead. Our algorithm takes account of these downstream costs.

• Type: Journal
• Year: 2009
• Where: CASES
• Authors: Paul M. Carpenter, Alex Ramírez, Eduard Ayguadé
• Keywords: Algorithm, Allocation Algorithm, CASES 2009, Iterative Stream Compiler, System Software