Date of Award



Electrical and Computer Engineering

Faculty Advisor

Anagnostopoulos, Iraklis


Approximate computing has emerged as a new computing paradigm capable of reducing the power requirements for or accelerating some workloads. Due to cascading error and the nature of binary arithmetic, it is difficult to predict the exact effects that approximation may have on an error tolerant workload. In this work, we implemented configurable levels of approximation into a Coarse Grained Reconfigurable Architecture (CGRA) to study the effects of error tolerant algorithms on an approximate CGRA. We will use the CGRA Compilation Framework which simulates a CGRA using gem5, and we will implement the approximate hardware using multiple different approximate arithmetic modules included in Low Power Approximate Computing Library. Finally, we will perform a hardware level simulation on approximate modules to estimate the reduction in power from using approximate hardware.


I would like to thank Dr. Iraklis Anagnostopoulos and Ioannis Galanis for their support in developing my researching abilities and helping me with this undergraduate research project. I would also like to thank the SIUC Honors Program for their guidance and mentorship through my bachelor’s degree. Finally, I would like to thank my friends and family for supporting me throughout my studies.