Reliability challenges for electric vehicles: from devices to architecture and systems software
Proceedings of the 50th Annual Design Automation Conference
An analytical method for reliability aware instruction set extension
The Journal of Supercomputing
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Application-specific instruction-set processors (ASIPs) allow the designer to extend the instruction set of the base processor with selected custom instructions to tailor-fit the application. In this paper, with the help of a motivational example, we first demonstrate that different custom instructions are vulnerable to faults with varying probabilities. This shows that by ignoring the vulnerability to faults, traditional methods of instruction set customization can provide no guarantees on the reliability of the system. Apart from such inherent disparity in error vulnerability across custom instructions, each custom instruction can have multiple implementation choices corresponding to varying hardened levels. Hardening reduces the vulnerability to errors but this comes at the overhead of area costs and reduced performance gain. In this paper, we propose a framework to select custom instructions and their respective hardening levels such that reliability is optimized while the performance gain is satisfied and area costs are met as well. Our framework is based on a novel analytical method to compute the overall system reliability based on the probability of failure of individual instructions. Wide range of experiments that were conducted illustrate how our tool navigates the design space to reveal interesting tradeoffs.