NDLI: Tightly-coupled hardware support to dynamic parallelism acceleration in embedded shared memory clusters

Content Provider	IEEE Xplore Digital Library
Author	Burgio, P. Tagliavini, G. Conti, F. Marongiu, A. Benini, L.
Copyright Year	2014
Description	Author affiliation: DEI, Univ. degli Studi di Bologna, Bologna, Italy (Burgio, P.; Tagliavini, G.; Conti, F.; Marongiu, A.; Benini, L.)
Abstract	Modern designs for embedded systems are increasingly embracing cluster-based architectures, where small sets of cores communicate through tightly-coupled shared memory banks and high-performance interconnections. At the same time, the complexity of modern applications requires new programming abstractions to exploit dynamic and/or irregular parallelism on such platforms. Supporting dynamic parallelism in systems which i) are resource-constrained and ii) run applications with small units of work calls for a runtime environment which has minimal overhead for the scheduling of parallel tasks. In this work, we study the major sources of overhead in the implementation of OpenMP dynamic loops, sections and tasks, and propose a hardware implementation of a generic Scheduling Engine (HWSE) which fits the semantics of the three constructs. The HWSE is designed as a tightly-coupled block to the PEs within a multi-core cluster, communicating through a shared-memory interface. This allows very fast programming and synchronization with the controlling PEs, fundamental to achieving fast dynamic scheduling, and ultimately to enable fine-grained parallelism. We prove the effectiveness of our solutions with real applications and synthetic benchmarks, using a cycle-accurate virtual platform.
Starting Page	1
Ending Page	6
File Size	190957
Page Count	6
File Format	PDF
ISBN	9783981537024
DOI	10.7873/DATE.2014.169
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-03-24
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	European Design Automation Association (EDAA)
Subject Keyword	Parallel processing Programming Dynamic scheduling Hardware Software Acceleration Computer architecture
Content Type	Text
Resource Type	Article

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