Onur Mutlu: Catalogue data in Spring Semester 2022

Name	Prof. Dr. Onur Mutlu
Field	Computer Science
Address	Dep. Inf.techno.u.Elektrotechnik ETH Zürich, ETZ F 84 Gloriastrasse 35 8092 Zürich SWITZERLAND
E-mail	onur.mutlu@safari.ethz.ch
URL	https://people.inf.ethz.ch/omutlu/
Department	Information Technology and Electrical Engineering
Relationship	Full Professor

Number	Title	ECTS	Hours	Lecturers
227-0085-51L	Projects & Seminars: Hands-on Acceleration on Heterogeneous Computing Systems Only for Electrical Engineering and Information Technology BSc. Course can only be registered for once. A repeatedly registration in a later semester is not chargeable.	3 credits	3P	O. Mutlu, J. Gómez Luna
Abstract	The category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.
Learning objective	The increasing difficulty of scaling the performance and efficiency of CPUs every year has created the need for turning computers into heterogeneous systems, i.e., systems composed of multiple types of processors that can suit better different types of workloads or parts of them. More than a decade ago, Graphics Processing Units (GPUs) became general-purpose parallel processors, in order to make their outstanding processing capabilities available to many workloads beyond graphics. GPUs have been critical key to the recent rise of Machine Learning and Artificial Intelligence, which took unrealistic training times before the use of GPUs. Field-Programmable Gate Arrays (FPGAs) are another example computing device that can deliver impressive benefits in terms of performance and energy efficiency. More specific examples are (1) a plethora of specialized accelerators (e.g., Tensor Processing Units for neural networks), and (2) near-data processing architectures (i.e., placing compute capabilities near or inside memory/storage). Despite the great advances in the adoption of heterogeneous systems in recent years, there are still many challenges to tackle, for example: - Heterogeneous implementations (using GPUs, FPGAs, TPUs) of modern applications from important fields such as bioinformatics, machine learning, graph processing, medical imaging, personalized medicine, robotics, virtual reality, etc. - Scheduling techniques for heterogeneous systems with different general-purpose processors and accelerators, e.g., kernel offloading, memory scheduling, etc. - Workload characterization and programming tools that enable easier and more efficient use of heterogeneous systems. If you are enthusiastic about working hands-on with different software, hardware, and architecture projects for heterogeneous systems, this is your P&S. You will have the opportunity to program heterogeneous systems with different types of devices (CPUs, GPUs, FPGAs, TPUs), propose algorithmic changes to important applications to better leverage the compute power of heterogeneous systems, understand different workloads and identify the most suitable device for their execution, design optimized scheduling techniques, etc. In general, the goal will be to reach the highest performance reported for a given important application. Prerequisites of the course: - Digital Design and Computer Architecture (or equivalent course). - Familiarity with C/C++ programming and strong coding skills. - Interest in future computer architectures and computing paradigms. - Interest in discovering why things do or do not work and solving problems - Interest in making systems efficient and usable The course is conducted in English. The course has two main parts: 1. Weekly lectures on GPU and heterogeneous programming. 2. Hands-on project: Each student develops his/her own project.
227-0085-56L	Projekte & Seminare: Intelligent Architectures via Hardware/Software Cooperation Only for Electrical Engineering and Information Technology BSc. Course can only be registered for once. A repeatedly registration in a later semester is not chargeable.	3 credits	3P	O. Mutlu
Abstract	The category of "Laboratory Courses, Projects, Seminars" includes courses and laboratories in various formats designed to impart practical knowledge and skills. Moreover, these classes encourage independent experimentation and design, allow for explorative learning and teach the methodology of project work.
Learning objective	Modern general-purpose processors are agnostic to an application’s high-level semantic information. Hence, they employ prediction-based techniques to enable computational and memory optimizations, such as prefetching, cache management policies, memory data placement, instruction scheduling, and many others. As such, the potential of such optimizations is limited due to the limited information the underlying hardware can discover on its own and such optimizations come with large area, power and complexity overheads required by the hardware for prediction purposes. Purely-hardware optimizations cannot achieve their performance potential and waste power, complexity and hardware area, since they are not aware of the application characteristics. On the other hand, purely-software optimizations are fundamentally tied up and limited by the underlying hardware. A promising way to increase the performance of modern applications is to co-design software and hardware. Hence, lately both industry and academia are making serious attempts to improve performance, energy and security using hardware/software cooperative schemes such as application-specific hardware accelerators (e.g., Google’s Tensor Processing Unit) and application-specific extensions in general-purpose processors (e.g., Media Engine in Apple M1). In this course, we will explore several different topics around hardware/software co-design such as: (i) new hardware/software interfaces (e.g., virtual memory, instruction set architecture) to enhance performance, energy and security, (ii) hardware/software co-design schemes to improve the performance of the memory subsystem in killer memory-intensive applications (e.g., sparse and irregular workloads), (iii) hardware/software cooperative machine-learning-based techniques for different microarchitectural components such as prefetchers, caches and branch predictors, which would continuously learn from the vast amount of memory accesses seen by a processor and adapt to the varying workload and system conditions. If you are enthusiastic about working hands-on to design both software and hardware, this is your P&S. You will have the opportunity to study modern applications, propose software changes to better match the underlying hardware components, design new hardware components that better match the overlying software and come up with new machine-learning techniques to design efficient microarchitectural components. You will also learn how to program industry-supported microarchitectural simulators and study the performance of modern workloads after your hardware/software modifications. Prerequisites of the course: - Digital Design and Computer Architecture (or equivalent course). - Familiarity with C/C++ programming and strong coding skills. - Interest in future computer architectures and computing paradigms. - Interest in discovering why things do or do not work and solving problems - Interest in making systems efficient and usable Preferable: - Hands-on experience with Machine Learning frameworks (depends on the topic you choose) The course is conducted in English.
227-2211-00L	Seminar in Computer Architecture Number of participants limited to 22. The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar.	2 credits	2S	O. Mutlu, M. H. K. Alser, J. Gómez Luna
Abstract	This seminar course covers fundamental and cutting-edge research papers in computer architecture. It has multiple components that are aimed at improving students' (1) technical skills in computer architecture, (2) critical thinking and analysis abilities on computer architecture concepts, as well as (3) technical presentation of concepts and papers in both spoken and written forms.
Learning objective	The main objective is to learn how to rigorously analyze and present papers and ideas on computer architecture. We will have rigorous presentation and discussion of selected papers during lectures and a written report delivered by each student at the end of the semester. This course is for those interested in computer architecture. Registered students are expected to attend every meeting, participate in the discussion, and create a synthesis report at the end of the course.
Content	Topics will center around computer architecture. We will, for example, discuss papers on hardware security; accelerators for key applications like machine learning, graph processing and bioinformatics; memory systems; interconnects; processing in memory; various fundamental and emerging paradigms in computer architecture; hardware/software co-design and cooperation; fault tolerance; energy efficiency; heterogeneous and parallel systems; new execution models; predictable computing, etc.
Lecture notes	All materials will be posted on the course website: https://safari.ethz.ch/architecture_seminar/ Past course materials, including the synthesis report assignment, can be found in the Fall 2020 website for the course: https://safari.ethz.ch/architecture_seminar/fall2020/doku.php
Literature	Key papers and articles, on both fundamentals and cutting-edge topics in computer architecture will be provided and discussed. These will be posted on the course website.
Prerequisites / Notice	Design of Digital Circuits. Students should (1) have done very well in Design of Digital Circuits and (2) show a genuine interest in Computer Architecture.
252-0028-00L	Digital Design and Computer Architecture	7 credits	4V + 2U	O. Mutlu, F. K. Gürkaynak
Abstract	The class provides a first introduction to the design of digital circuits and computer architecture. It covers technical foundations of how a computing platform is designed from the bottom up. It introduces various execution paradigms, hardware description languages, and principles in digital design and computer architecture.
Learning objective	This class provides a first approach to Computer Architecture. The students learn the design of digital circuits in order to: - understand the basics, - understand the principles (of design), - understand the precedents (in computer architecture). Based on such understanding, the students are expected to: - learn how a modern computer works underneath, from the bottom up, - evaluate tradeoffs of different designs and ideas, - implement a principled design (a simple microprocessor), - learn to systematically debug increasingly complex systems, - hopefully be prepared to develop novel, out-of-the-box designs. The focus is on basics, principles, precedents, and how to use them to create/implement good designs.
Content	The class consists of the following major blocks of contents: - Major Current Issues in Computer Architecture: Principles, Mysteries, Motivational Case Studies and Examples - Digital Logic Design: Combinational Logic, Sequential Logic, Hardware Description Languages, FPGAs, Timing and Verification. - Basics of Computer Architecture: Von Neumann Model of Computing, Instruction Set Architecture, Assembly Programming, Microarchitecture, Microprogramming. - Basics of Processor Design: Pipelining, Out-of-Order Execution, Branch Prediction. - Execution Paradigms: Out-of-order Execution, Dataflow, Superscalar Execution, VLIW, Decoupled Access/Execute, SIMD Processors, GPUs, Systolic Arrays, Multithreading. - Memory System: Memory Organization, Memory Technologies, Memory Hierarchy, Caches, Prefetching, Virtual Memory.
Lecture notes	All the materials (including lecture slides) will be provided on the course website: http://safari.ethz.ch/digitaltechnik/ The video recordings of the lectures are likely to be made available, but there may be delays associated with the posting of online videos.
Literature	Patt and Patel's "Introduction to Computing Systems" and Harris and Harris's "Digital Design and Computer Architecture" are the official textbooks of the course. We will provide required and recommended readings in every lecture since the course is cutting-edge and there is no textbook that covers what the course covers. They will be mostly chapters of the two textbooks, and important articles that are essential for understanding the material.