Parameterized Architecture-Level Thermal Modeling and Characterization for Multi-Core Microprocessor Design

University Of California-Riverside, Riverside CA

Investigators

Abstract

"This award is funded under the American Recovery and Reinvestment Act of 2009(Public Law 111-5)." Lead Proposal#: 0902885 Title: Parameterized Architecture-Level Thermal Modeling and Characterization for Multi-Core Microprocessor Design PI: Sheldon X.-D. Tan, Dept of Electrical Engineering, UC Riverside co-PI: Yingbo Hua, Dept of Electrical Engineering, UC Riverside Inst: Department of Electrical Engineering CoPI Inst:University of California at Riverside ABSTRACT Multicore (also known as so-called chip-multiprocessors (CMP)) architectures are the trend for current and future microprocessor designs. They provide better performance via thread-level parallelism, better power/thermal scaling, and easy design by design reuse. However, power/thermal considerations are still the first-class constraints for multicore microprocessor designs. Thermal-aware design space explorations at core and architecture level for multicore microprocessors become critical design issues. This research seeks to explore new techniques of building compact parameterized, transient thermal models for efficient thermal-aware design space explorations in multicore microprocessor designs. The project consists of three thrusts: (1) Architecture-level behavioral transient thermal modeling and characterization; (2) Parameterized thermal modeling considering variable design parameters; (3) Thermal model optimization and reduction. The proposed method is a top-down, black-box approach, meaning that it does not require any knowledge of the internal structures of the systems; This approach makes the proposed method very general and flexible, which contrasts the existing approaches. The accuracy of the models is ensured by the measured or precisely computed thermal-power information from hardware. The parameterized models can accommodate different design variable parameters for efficient design space explorations. The outcome of this research will add significantly to the core knowledge of thermal modeling multicore design. It will provide a new alternative way to complement existing architecture-level thermal models for the architecture community. Since the PIs will work closely with SRC, the proposed project will have immediate impacts on thermal-aware multicore microprocessor design in industry. This grant will enable the PI to hire more women and underrepresented minority students to contribute to the greater diversity in America's science and technology workforce.