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Locality management using multiple SPMs on the Multi-Level Computing Architecture

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2 Author(s)
Abdelkhalek, A.M. ; Dept. of Electr. & Comput. Eng., Toronto Univ., Ont. ; Abdelrahman, T.S.

The multi-level computing architecture (MLCA) is a novel system-on-chip architecture for embedded systems designed to exploit task-level and instruction-level parallelism in multimedia applications. The MLCA provides a unique two-level programming model that simplifies the development of embedded applications. To cope with increasing intra-system communication delays, we introduce a distributed memory version of the MLCA where separate storage is used for global and local application data. Global data is stored on multiple on-chip scratch-pad memories (SPMs) with non-uniform-memory access (NUMA) latencies, while local data is stored on PU-private memories. In such designs, one of the key factors affecting application performance is the locality of access to global data. We introduce programming constructs and run-time support to dynamically manage data stored in the SPMs and to influence run-time task scheduling. Collectively, our techniques improve performance by 6%-40%, compared to simple static memory management and scheduling approaches

Published in:

Embedded Systems for Real Time Multimedia, Proceedings of the 2006 IEEE/ACM/IFIP Workshop on

Date of Conference:

Oct. 2006