This year, the SAMOS conference is hosting two tutorials, given by leading experts in various fields.

◊◊ ◊◊ ◊◊

Tutorial on Quantum Computing

Tutorial Organizer: Carmen G. Almudéver (Delft University of Technology)

Abstract: Quantum computers hold the promise for solving efficiently important problems in computational sciences that are intractable nowadays by exploiting quantum phenomena such are superposition and entanglement. One of the most famous examples is the factorization of large numbers using Shor’s algorithm. For instance, a 2000-bit number could be decomposed in a bit more than one day using a quantum computer whereas a data center of approx. 400.000 km2 built with the fastest today’s supercomputer would require around 100 years.

This extraordinary property of quantum computers together with the great evolution of the quantum technology in the last past years has made that large companies as Google, Lockheed Martin, Microsoft, IBM and Intel are substantially investing in quantum computing.

Up to now, quantum computing has been a field mostly dominated by physicists. They are working on the design and fabrication of the basic units of any quantum system, called quantum bits or qubits. However, building a quantum computer involves more than producing ‘good’ qubits. It requires the development on an entire quantum computer architecture.

This tutorial will introduce the basic notions of quantum computing; going from quantum bits, superposition and entanglement, to quantum gates and circuits, up to quantum algorithms. The tutorial will provide hands-on exercises based on our QX simulator platform (http://quantum-studio.net), allowing the participants to implement some simple quantum circuits/algorithms. We will also address the main challenges when building a large-scale quantum computer.

The objective of this tutorial is to introduce the basics of quantum computing and show where the scientific challenges are.

◊◊ ◊◊ ◊◊

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

Tutorial Organizer: Onur MutluETH Zurich

Abstract: 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 series, 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.

Bio: 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 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). For more information, please see his webpage at https://people.inf.ethz.ch/omutlu/.

[Part 1: Memory Importance and Trends: PPTX, PDF

[Part 2: RowHammer: PPTX, PDF

[Part 3: Computation in Memory: PPTX, PDF

[Part 4: Low-Latency Memory: PPTX, PDF

[Part 5: Principles and Conclusion: PPTX, PDF]