Design Automation and Architecture Design for Near Threshold Computing

• Applicant: Professor Mehdi B. Tahoori, Ph.D.
• Subject Area: Computer Architecture, Embedded and Massively Parallel Systems
• Term: from 2021 to 2024
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 447830483

Internet of Things (IoT) is a fast growing market with significant impacts in various aspects of industry and personal life. IoT edge devices critically depend on ultra-low power and reduced form-factor. Many IoT devices in various usage scenarios could be energy-harvested or work with limited battery, and expected to run for a long operational lifetime. They also require to adapt for energy on-the-fly, and adjust performance, accuracy, and correctness to meet the stringent energy budget. In this context, near threshold computing (NTC), by lowering the supply voltage down to the threshold voltage of transistors, is a promising approach to significantly reduce energy consumption. However, there are various challenges in NTC circuit, architecture and system design, which require completely new analysis frameworks, electronic design automation (EDA) tools, and design paradigms. In particular, reducing the supply voltage comes at the expense of significant resiliency loss, due to higher failure rates and increased sensitivity to variations. Therefore, energy-efficient resiliency is a major challenge for IoT edge devices operating at NTC. The main premise of this proposal is to develop cross-layer reliable design automation and architecture design methodologies for near threshold computing systems, which drive many emerging application domains in IoT. Proper design of resilient NTC circuits and architectures is achieved by a series of cross-layer techniques from circuit, logic design and automation flows all the way to the system architecture for NTC. We specifically proposed to develop i) logic and memory optimization to operate reliability at near threshold regime, ii) runtime tuning and adaptation to predict and mitigate failures due to near threshold operation, and iii) embracing residual errors in near threshold computing through approximate computing.

• DFG Programme: Research Grants