基于选择性估计的抽象建模与仿真

Yaseen Zaidi, Sumit Adhikari, C. Grimm
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引用次数: 4

摘要

通过静态调度、恒定时间步进、线性求解器和数据流范式等计算模型和语言特性,SystemC AMS提供了较高的抽象和仿真速度。我们证明了这种丰富的表达可以在系统级描述中呈现非理想行为。还演示了从系统级到周期精度或电路级的设计探索和改进。主要的贡献是细粒度表征可以从系统级设计开始。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Abstract modeling and simulation based selective estimation
SystemC AMS offers high abstraction and simulation speed through models of computation and language features such as static scheduling, constant time stepping, linear solver and dataflow paradigm. We demonstrate that such rich expressiveness can render non-ideal behavior in system level description. Design exploration and refinement from system level down to cycle accurate or circuit level is also demonstrated. The main contribution is that the fine grain characterization can start at system level design.
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