Implementation-aware model analysis: The case of buffer-throughput tradeoff in streaming applications

Mirzazad Barijough, K ; Sharif University of Technology | 2015

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  1. Type of Document: Article
  2. DOI: 10.1145/2670529.2754968
  3. Publisher: Association for Computing Machinery , 2015
  4. Abstract:
  5. Models of computation abstract away a number of implementation details in favor of well-defined semantics. While this has unquestionable benefits, we argue that analysis of models solely based on operational semantics (implementation oblivious analysis) is unfit to drive implementation design space exploration. Specifically, we study the tradeoff between buffer size and streaming throughput in applications modeled as synchronous data flow (SDF) graphs. We demonstrate the inherent inaccuracy of implementation-oblivious approach, which only considers SDF operational semantic. We propose a rigorous transformation, which equips the state of the art buffer-throughput tradeoff analysis technique with implementation awareness. Extensive empirical evaluation show that our approach results in significantly more accurate estimates in streaming throughput at the model level, while running two orders of magnitude faster than cycle-accurate simulation of implementations
  6. Keywords:
  7. Buffer-Throughput Tradeoff Analysis ; Embedded Multi-Processor ; Synchronous DataFlow (SDF) ; Computation theory ; Computational linguistics ; Digital storage ; Embedded systems ; Flow graphs ; Multiprocessing systems ; Program compilers ; Response time (computer systems) ; Semantics ; Throughput ; Cycle-accurate simulation ; Empirical evaluations ; Implementation design ; Multi-processors ; Operational semantics ; Streaming applications ; Synchronous Dataflow ; Trade-off analysis ; Data flow analysis
  8. Source: Proceedings of the ACM SIGPLAN Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES), 18 June 2015 through 19 June 2015 ; Volume 2015-June , 2015 , Pages 108-117 ; 9781450332576 (ISBN)
  9. URL: http://dl.acm.org/citation.cfm?id=2754968