Bridging the Gap Between Voltage Over-Scaling and Joint Hardware Accelerator-Algorithm Closed-Loop

Voltage over-scaling (VOS) optimizes energy while causing timing errors due to an unsustainable clock frequency. Many algorithms, such as in multimedia and machine learning applications, are capable of tolerating such errors. VOS has never been investigated in hardware accelerators running closed-loop algorithms. As the errors impact most decisions and actions in the subsequent steps, closed-loops dynamically change the execution flow. Timing errors should be evaluated by an accurate gate-level simulation, but a large gap still remains: how these timing errors propagate from the underlying hardware all the way up to the entire algorithm run, where they just may degrade the performance and quality of service of the application at stake? This paper tackles this issue showing a framework for VOS investigation, embracing any kind of application. Our framework simulates the VOS-induced timing errors at gate-level, dynamically linking the hardware result with the algorithm and vice versa during the evolution of the runtime of the application. The state-of-the-art VOS literature for video encoding application fails to assess the ultimate impacts of VOS-induced timing errors, as current works open the encoding loops. Unlike those, our work investigates the ultimate impact of a hardware accelerator dynamically carrying through to the video encoder all VOS-induced timing errors and preserving the full compliance to the standard. We employ a parallel sum of absolute differences (SAD) hardware accelerator as a case study. We assess the performance of the overall encoder under varying timing guardbands. Next, it is demonstrated that, under VOS, the ultimate impact in compression efficiency is related to the video’s motion intensity. Additionally, the advantages of timing guardband controlled reduction are clearly quantified in our results by virtue of the framework. Reducing at maximum 9.5% the clock frequency, energy savings (up to 16.5% in energy/operation) are achieved in SAD for video compression.