Adaptive algorithm and tool flow for accelerating SystemC on many-core architectures

Reder, Simon; Roth, Christoph; Bucher, Harald; Sander, Oliver; Becker, J.

doi:10.1016/j.micpro.2015.06.001

Cited by 4 publications

(1 citation statement)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The solution presented in [30] uses both static and dynamic analysis to propose an adaptive algorithm and tool flow for SystemC/RTL parallelization. Their current solution is based on RTL features, e.g., sc_signal, but they used a sufficient level of abstraction in their algorithm to keep hope for future TLM support (planned as a future work by the authors).…”

Section: Dependency Analysismentioning

confidence: 99%

Parallel Simulation of Loosely Timed SystemC/TLM Programs: Challenges Raised by an Industrial Case Study

2016

View full text Add to dashboard Cite

Transaction level models of systems-on-chip in SystemC are commonly used in the industry to provide an early simulation environment. The SystemC standard imposes coroutine semantics for the scheduling of simulated processes, to ensure determinism and reproducibility of simulations. However, because of this, sequential implementations have, for a long time, been the only option available, and still now the reference implementation is sequential. With the increasing size and complexity of models, and the multiplication of computation cores on recent machines, the parallelization of SystemC simulations is a major research concern. There have been several proposals for SystemC parallelization, but most of them are limited to cycle-accurate models. In this paper we focus on loosely timed models, which are commonly used in the industry. We present an industrial context and show that, unfortunately, most of the existing approaches for SystemC parallelization can fundamentally not apply in this context. We support this claim with a set of measurements performed on a platform used in production at STMicroelectronics. This paper surveys existing techniques, presents a visualization and profiling tool and identifies unsolved challenges in the parallelization of SystemC models at transaction level.

show abstract

Section: Dependency Analysismentioning

confidence: 99%