Memory Systems and Memory-Centric Computing Systems: Challenges and Opportunities

Content of the lecture:

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 lecture, 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 some 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. 

Teacher: Prof. Onur Mutlu

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 Strecker Early Career Professorship. His current broader research interests are in computer architecture, systems, hardware security, and bioinformatics. A variety of techniques he, along with his group and collaborators, has 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. He started the Computer Architecture Group at Microsoft Research (2006-2009), and held 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, US National Science Foundation CAREER Award, Carnegie Mellon University Ladd Research Award, faculty partnership awards from various companies, and a healthy number of best paper or “Top Pick” paper recognitions at various computer systems, architecture, and hardware security venues. He is an ACM Fellow “for contributions to computer architecture research, especially in memory systems”, IEEE Fellow for “contributions to computer architecture research and practice”, and an elected member of the Academy of Europe (Academia Europaea). His computer architecture and digital circuit design course lectures and materials are freely available on YouTube, and his research group makes a wide variety of software and  hardware artifacts freely available online. For more information, please see his webpage at https://people.inf.ethz.ch/omutlu/.

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