The memory system is a fundamental performance and energy bottleneck in almost all computing systems. Recent system design, application, and technology trends that require more capacity, bandwidth, efficiency, and predictability out of the memory system make it an even more important system bottleneck. At the same time, DRAM and flash technologies are experiencing difficult technology scaling challenges that make the maintenance and enhancement of their capacity, energy efficiency, performance, and reliability significantly more costly with conventional techniques. In fact, recent reliability issues with DRAM, such as the RowHammer problem, are already threatening system security and predictability. We are at the challenging intersection where issues in memory reliability and performance are tightly coupled with not only system cost and energy efficiency but also system security.
In this course, we first discuss major challenges facing modern memory systems (and the computing platforms we currently design around the memory system) in the presence of greatly increasing demand for data and its fast analysis. We then examine some promising research and design directions to overcome these challenges. We discuss at least three key topics in detail, focusing on both open problems and potential solution directions: 1) fundamental issues in memory reliability and security and how to enable fundamentally secure, reliable, safe architectures; 2) enabling data-centric and hence fundamentally energy-efficient architectures that are capable of performing computation near data; 3) reducing both latency and energy consumption by tackling the fixed-latency/energy mindset.
If time permits, we will also discuss research challenges and opportunities in enabling emerging NVM (non-volatile memory) technologies and scaling NAND flash memory and SSDs (solid state drives) into the future.
Onur Mutlu is a Professor of Computer Science at ETH Zurich. He is also a faculty member at Carnegie Mellon University, where he previously held the William D. and Nancy W. Strecker Early Career Professorship. His current broader research interests are in computer architecture, systems, and bioinformatics. He is especially interested in interactions across domains and between applications, system software, compilers, and microarchitecture, with a major current focus on memory and storage systems. A variety of techniques he, together with his group and collaborators, have invented over the years have influenced industry and have been employed in commercial microprocessors and memory/storage systems. He obtained his PhD and MS in ECE from the University of Texas at Austin and BS degrees in Computer Engineering and Psychology from the University of Michigan, Ann Arbor. His industrial experience spans starting the Computer Architecture Group at Microsoft Research (2006-2009), and various product and research positions at Intel Corporation, Advanced Micro Devices, VMware, and Google.
He received the inaugural IEEE Computer Society Young Computer Architect Award, the inaugural Intel Early Career Faculty Award, faculty partnership awards from various companies, a healthy number of best paper or "Top Pick" paper recognitions at various computer systems and architecture venues, and the ACM Fellow recognition "for contributions to computer architecture research, especially in memory systems."
His computer architecture course lectures and materials are freely available on YouTube, and his research group makes software artifacts freely available online.