A Framework for Collective Personalized Communication

This paper explores collective personalized communication. For example, in all-to-all personalized communication (AAPC), each processor sends a distinct message to every other processor. However, for many applications, the collective communication pattern is many-to-many, where each processor sends a distinct message to a subset of processors. In this paper we first present strategies that reduce per-message cost to optimize AAPC. We then present performance results of these strategies in both all-to-all and many-to-many scenarios. These strategies are implemented in a flexible, asynchronous library with a non-blocking interface, and a message-driven runtime system. This allows the collective communication to run concurrently with the application, if desired. As a result the computational overhead of the communication is substantially reduced, at least on machines such as PSC Lemieux, which sport a coprocessor capable of remote DMA. We demonstrate the advantages of our framework wit...

• Type: Conference
• Year: 2003
• Where: IPPS
• Authors: Laxmikant V. Kalé, Sameer Kumar, Krishnan Varadarajan
• Keywords: Collective Communication, Distinct Message, Distributed And Parallel Computing, IPPS 2003, Personalized Communication