Communication and migration energy aware task mapping for reliable multiprocessor systems

• Authors: Anup Das;Akash Kumar;Bharadwaj Veeravalli
• Venue: Future Generation Computer Systems
• Year: 2014

Heterogeneous multiprocessor systems-on-chip (MPSoCs) are emerging as a promising solution in deep sub-micron technology nodes to satisfy design performance and power requirements. However, shrinking transistor geometry and aggressive voltage scaling are negatively impacting the dependability of these MPSoCs by increasing the chances of failures. This paper proposes an offline (design-time) task remapping technique to minimize the communication energy and task migration overhead of an application mapped on a heterogeneous multiprocessor system for all processor fault-scenarios. The proposed technique involves two steps-(1) Communication Energy driven Design Space Exploration (CDSE) to select an initial mapping and (2) Communication energy and Migration overhead aware Task Mapping (CMTM) for different fault-scenarios. The CDSE is formulated as a Mixed Integer Quadratic Programming (MIQP) problem and solved using an energy-gradient based heuristic. The CMTM problem is solved using a fast heuristic with the starting mapping selected using CDSE step. The proposed two steps technique is compared with state-of-the-art approaches through rigorous simulations with synthetic and real application graphs. Results demonstrate that the proposed CDSE reduces design space exploration time by 99% with a maximum variation of 5% from the optimal solution obtained by solving the MIQP problem directly. Further, the proposed CMTM reduces communication energy by an average 35% and migration overhead by an average 20% for all single and double fault-scenarios as compared to the existing fault-tolerant techniques. The CMTM also achieves over 30x reductions in execution time for large problem sizes with a maximum deviation of 15% from the minimum communication energy achievable with the given application on a given architecture. For streaming multimedia applications, the proposed technique delivers 50% higher throughput per unit energy as compared to the existing approaches.