A Prediction Packetizing Scheme for Reducing Channel Traffic in Transaction-Level Hardware/Software Co-Emulation

Jae-Gon Lee, Moo-Kyoung Chung, Ki-Yong Ahn, Sang-Heon Lee, Chong-Min Kyung

This paper presents a scheme for efficient channel usage between simulator and accelerator where the accelerator models some RTL sub-blocks in the accelerator-based hardware/software co-simulation while the simulator runs transaction-level model of the remaining part of the whole chip being verified. With conventional simulation accelerator, evaluations of simulator and accelerator alternate at every valid simulation time, which results in poor simulation performance due to startup overhead of simulator-accelerator channel access. The startup overhead can be reduced by merging multiple transactions on the channel into a single burst traffic. We propose a predictive packetizing scheme for reducing channel traffic by merging as many transactions into a burst traffic as possible based on 'prediction and rollback.' Under ideal condition with 100% prediction accuracy, the proposed method shows a performance gain of 1500% compared to the conventional one.

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