Skewed pipelining for parallel simulink simulations

Canedo,; Yoshizawa,; Komatsu,

doi:10.1109/date.2010.5456927

Cited by 4 publications

(1 citation statement)

References 8 publications

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“…Most methods are based on functional modeling, such as Khan process networks [4], dataflow [5], UML [6], and Simulink [7]. As a prevalent environment for modeling and simulating complex systems at an algorithmic level of abstraction, Simulink has been widely used, such as in Real-Time Workshop® [8], dSpace [9], and many other code generators [10]- [11]. Light and Efficient Simulink Compiler for Embedded Application (LESCEA) [12] is an automatic code generation tool with memory-oriented optimization techniques.…”

Section: Related Workmentioning

confidence: 99%

Software Pipeline–Based Partitioning Method with Trade-Off between Workload Balance and Communication Optimization

Huang¹,

Xiu²,

Yu³

et al. 2015

ETRI J

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For a multiprocessor System‐on‐Chip (MPSoC) to achieve high performance via parallelism, we must consider how to partition a given application into different components and map the components onto multiple processors. In this paper, we propose a software pipeline–based partitioning method with cyclic dependent task management and communication optimization. During task partitioning, simultaneously considering computation load balance and communication optimization can cause interference, which leads to performance loss. To address this issue, we formulate their constraints and apply an integer linear programming approach to find an optimal partitioning result — one that requires a trade‐off between these two factors. Experimental results on a reconfigurable MPSoC platform demonstrate the effectiveness of the proposed method, with 20% to 40% performance improvements compared to a traditional software pipeline–based partitioning method.

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