High-speed DFG-level SEU vulnerability analysis for applying selective TMR to resource-constrained CGRA

In this paper, we investigate a method to achieve cost-effective selective triple modular redundancy (selective TMR) against single event upset (SEU). This method enables us to minimize the vulnerability of the target application circuit implemented on a resource-constrained coarse-grained reconfigurable architecture (CGRA). The key of the proposed method is the evaluation function to determine the vulnerable node in the data flow graph (DFG) of the target application. Since the influence of the fault in a node to the primary outputs depends on its fains and fanouts as well as the node itself, this paper proposes an enhanced evaluation function that reflects the operation of fanins/fanouts of a node. This paper also improves the method to derive weight vector which is used in the evaluation function, by assuming exponential distribution instead of linear distribution for the vulnerability of nodes. To derive a generic weight vector, we propose to solve a concatenated linear equations obtained from multiple sample applications, instead of averaging the weight vectors for applications. Using generalized inverse matrix to solve the equation, the proposed method takes less than ten seconds to extract a reasonable priority for selective TMR, which is extremely faster than the exhaustive exploration for the optimal solution that takes more than 15 hours. This paper also compares the contributions of the features use in the evaluation function, which would be insightful for designing reliability-aware CGRA architecture and synthesis tools.