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

“这项奖励是根据2009年美国复苏和再投资法案（公法111-5）资助的。”题目：多核微处理器设计的参数化体系结构级热建模和表征多核（也被称为芯片多处理器（CMP））架构是当前和未来微处理器设计的趋势。它们通过线程级并行性提供更好的性能，更好的功率/热缩放，以及简单的设计重用。然而，功率/热的考虑仍然是多核微处理器设计的首要限制。多核微处理器在核心和架构层面的热感知设计空间探索成为关键的设计问题。本研究旨在探索构建紧凑的参数化瞬态热模型的新技术，以便在多核微处理器设计中进行有效的热感知设计空间探索。该项目包括三个重点：(1)建筑级行为瞬态热建模和表征；(2)考虑可变设计参数的参数化热建模；(3)热模型优化与还原。所提出的方法是一种自顶向下的黑盒方法，这意味着它不需要系统内部结构的任何知识；与现有方法相比，该方法具有通用性和灵活性。模型的准确性由测量或精确计算的硬件热功率信息来保证。参数化模型可以适应不同的设计变量参数，从而实现高效的设计空间探索。本研究成果将对热建模多核设计的核心知识有重要的补充。它将为架构社区提供一种新的替代方法来补充现有的架构级热模型。由于pi将与SRC密切合作，因此拟议的项目将对工业中的热感知多核微处理器设计产生直接影响。这笔拨款将使PI能够雇用更多的女性和未被充分代表的少数族裔学生，为美国科技劳动力的更大多样性做出贡献。

"This award is funded under the American Recovery and Reinvestment Act of 2009(Public Law 111-5)."Lead Proposal#: 0902885Title: Parameterized Architecture-Level Thermal Modeling and Characterization for Multi-Core Microprocessor DesignPI: Sheldon X.-D. Tan, Dept of Electrical Engineering, UC Riversideco-PI: Yingbo Hua, Dept of Electrical Engineering, UC Riverside Inst: Department of Electrical EngineeringCoPI Inst:University of California at RiversideABSTRACTMulticore (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.