Stream (data-flow) computing is considered an effective para-digm for parallel programming of high-end multi-core architectures for embedded applications (networking, multimedia, wireless communication). Our work addresses a key step in stream programming for embedded multicores, namely, the efficient mapping of a synchronous data-flow graph (SDFG) onto a multi-core platform subject to a minimum throughput requirement. This problem has been extensively studied in the past, and its complexity has lead researches to develop incomplete algorithms which cannot exclude false negatives. We developed a CP-based complete algorithm based on a new throughput-bounding constraint. The algorithm has been tested on a number of non-trivial SDFG mapping problems with promising results.
A. Bonfietti, M. Lombardi, M. Milano, L. Benini (2009). Throughput Constraint for Synchronous Data Flow Graphs. BERLIN/HEIDELBERG : Springer-Verlag [10.1007/978-3-642-01929-6_4].
Throughput Constraint for Synchronous Data Flow Graphs
BONFIETTI, ALESSIO;LOMBARDI, MICHELE;MILANO, MICHELA;BENINI, LUCA
2009
Abstract
Stream (data-flow) computing is considered an effective para-digm for parallel programming of high-end multi-core architectures for embedded applications (networking, multimedia, wireless communication). Our work addresses a key step in stream programming for embedded multicores, namely, the efficient mapping of a synchronous data-flow graph (SDFG) onto a multi-core platform subject to a minimum throughput requirement. This problem has been extensively studied in the past, and its complexity has lead researches to develop incomplete algorithms which cannot exclude false negatives. We developed a CP-based complete algorithm based on a new throughput-bounding constraint. The algorithm has been tested on a number of non-trivial SDFG mapping problems with promising results.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
