NDLI: Strategies for mapping dataflow blocks to distributed hardware

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Strategies for mapping dataflow blocks to distributed hardware

Content Provider	ACM Digital Library
Author	McKinley, Kathryn S. Robatmili, Behnam Coons, Katherine E. Burger, Doug
Abstract	Distributed processors must balance communication and concurrency. When dividing instructions among the processors, key factors are the available concurrency, criticality of dependence chains, and communication penalties. The amount of concurrency determines the importance of the other factors: if concurrency is high, wider distribution of instructions is likely to tolerate the increased operand routing latencies. If concurrency is low, mapping dependent instructions close to one another is likely to reduce communication costs that contribute to the critical path. This paper explores these tradeoffs for distributed Explicit Dataflow Graph Execution (EDGE) architectures that execute blocks of dataflow instructions atomically. A runtime block mapper assigns instructions from a single thread to distributed hardware resources (cores) based on compiler-assigned instruction identifiers. We explore two approaches: fixed strategies that map all blocks to the same number of cores, and adaptive strategies that vary the number of cores for each block. The results show that best fixed strategy varies, based on the cores’ issue width. A simple adaptive strategy improves performance over the best fixed strategies for single and dual-issue cores, but its benefits decrease as the cores’ issue width increases. These results show that by choosing an appropriate runtime block mapping strategy, average performance can be increased by 18%, while simultaneously reducing average operand communication by 70%, saving energy as well as improving performance. These results indicate that runtime block mapping is a promising mechanism for balancing communication and concurrency in distributed processors.
Starting Page	23
Ending Page	34
Page Count	12
File Format	PDF
ISBN	9781424428366
DOI	10.1109/MICRO.2008.4771776
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2008-11-08
Access Restriction	Subscribed
Content Type	Text
Resource Type	Article

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