Classification-Based Improvement of Application Robustness and Quality of Service in Probabilistic Computer Systems

Future semiconductors no longer guarantee permanent deterministic operation. They are expected to show probabilistic behavior due to lowered voltages and shrinking structures.

Compared to radiation-induced errors, probabilistic systems face increased error frequencies leading to unexpected bit-flips. Approaches like probabilistic CMOS provide methods to control error distributions which reduce the error probability in more significant bits. However, instructions handling control flow or pointers still expect deterministic operation, thus requiring a classification to identify these instructions.

We apply our transient error classification to probabilistic circuits using differing voltage distributions. Static analysis ensures that probabilistic effects only affect

unreliable

operations which accept a certain level of impreciseness, and that errors in probabilistic components will never propagate to critical operations.

To evaluate, we analyze robustness and quality-of-service of an H.264 video decoder. Using classification results, we map unreliable arithmetic operations onto probabilistic components of a simulated ARM-based architecture, while the remaining operations use deterministic components.