A confidence-driven model for error-resilient computing

We propose an adaptive reliability enhancement structure for deeply-scaled CMOS and future devices that exhibit nondeterministic behavior. This structure forms the basis of a confidence-driven computing model that can be implemented in either a rollback recovery or an iterative dual modular redundancy method incorporating synchronous handshake schemes. The performance and cost of the computing model are estimated using a 45 nm CMOS technology and the functionality is verified by FPGA-based emulation. The confidence-driven computing model is demonstrated using a 16-bit, 12-stage CORDIC processor operating under random, transient errors. The confidence-driven computing model adapts to the fluctuating error rates at the device substrate level to guarantee the reliability of computation at the system level. This computing model costs 4.2 times smaller area and 2.7 times less energy overhead than triple modular redundancy to guarantee a system-level mean time to failure of two years.