How to ensure the output quality is one of the most critical challenges in approximate computing. This paper presents an online quality management system in an approximate-accelerator-based computing environment that can effectively detect and correct large approximation errors.
['Daya Shanker Khudia', 'Babak Zamirai', 'Mehrzad Samadi', 'Scott A. Mahlke']
Quality Control for Approximate Accelerators by Error Prediction