A smart protocol-level task mapping for energy efficient traffic on network-on-chip

Abstract

Previous task mapping assumes that applications directly fetch data on remote nodes and build up their energy efficient mapping based on pattern of the NoC traffic. However, the data movement is actually managed by a cache coherence mechanism that executes a much more complicated protocol under application layer to guarantee data correction. Thus, we propose an energy efficient task mapping referring the protocol layer, rather than application layer, to precisely model protocol activities and energy dissipation. By a probabilistic description of cache accessing, we find a efficient method to convert application activities to energy consumption, generating an energy evaluation as a global optimization goal. We also propose a task mapping algorithm to minimize the energy consumption by referring activity intensity of the protocol. The experimental results show that the proposed energy model achieves a precision with less than 2% error and provides a credible quantitative criterion for energy optimization of cache coherence protocols. Comparing to application-layer optimization, our task mapping can obtain 20% energy saving and 15% latency reduction on average.