As-Is Approximate Computing

Abstract

Although approximate computing promises better performance for applications allowing marginal errors, dearth of hardware support and lack of run-time accuracy guarantees makes it difficult to adopt. We present As-Is, an Anytime Speculative Interruptible System that takes an approximate program and executes it with time-proportional approximations. That is, an approximate version of the program output is generated early and is gradually refined over time, thus providing the run-time guarantee of eventually reaching 100% accuracy. The novelty of our As-Is architecture is in its ability to conceptually marry approximate computing and speculative computing. We show how existing innovations in speculative architectures can be repurposed for anytime, best-effort approximation, facilitating the design efforts and overheads needed for approximate hardware support. As-Is provides a platform for real-time constraints and interactive users to interrupt programs early and accept their current approximate results as is. 100% accuracy is always guaranteed if more time can be spared. Our evaluations demonstrate favorable performance-accuracy tradeoffs for a range of approximate applications.