CAREER: Advancing STTRAM Caches for Runtime Adaptable and Energy-Efficient Microarchitectures

University Of Arizona, Tucson AZ

Investigators

Abstract

On-chip caches are important due to their substantial impact on the energy consumption and performance of a wide variety of computer systems, including desktop computers, embedded systems, mobile devices, servers, etc. As an alternative to traditional static random-access memory (SRAM) for implementing caches, the spin-transfer torque RAM (STTRAM) is a type of non-volatile memory that promises several advantages, such as high density, low leakage, high endurance, and compatibility with complementary metal-oxide-semiconductor (CMOS). However, STTRAM caches still face critical challenges that impede their widespread adoption, such as high write latency and energy. In addition, users of computer systems and the programs that run on the systems typically have variable resource requirements, necessitating caches that can dynamically adapt to runtime needs. This CAREER project will investigate several interrelated research problems, including: STTRAM's characteristics and how they can be leveraged for improving the energy efficiency and performance of computer systems that run diverse programs; techniques for improving the user's experience while running the programs; new architectures and management techniques for enabling STTRAM caches that are energy-efficient and can dynamically adapt to running programs? individual needs; and novel methods to address the challenges of implementing STTRAM caches in complex multicore computer systems. Ultimately, the project will develop STTRAM cache architectures that can automatically adapt to the execution needs of diverse programs, resulting in more energy-efficient and faster computer systems. The project's broader impacts include architectures and methods that will improve the performance and energy efficiency of a wide variety of computer systems for running a wide variety of programs. With the growth of the Internet of Things (IoT), spanning diverse computing and user needs, this project represents an important and necessary step towards adaptable and low-overhead computer systems. This CAREER project also seeks to foster education and diversity in science, technology, engineering, and math (STEM) fields through K-12 seminars, and by engaging and equipping a diverse group of young engineers with necessary techniques and skills to design innovative solutions for energy-efficient and adaptable Internet of Things architectures. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.