Course

CS-307: Introduction to multiprocessor architecture

Summary

Multiprocessors are a core component in all types of computing infrastructure, from phones to datacenters. This course will build on the prerequisites of processor design and concurrency to introduce the essential technologies required to combine multiple processing elements into a single computer.

Lectures

Instructor

Babak Falsafi

Babak is a Professor in the School of Computer and Communication Sciences and the founding director of the EcoCloud, an industrial/academic consortium at EPFL investigating scalable data-centric technologies. He has made numerous contributions to computer system design and evaluation including a scalable multiprocessor architecture which was prototyped by Sun Microsystems (now Oracle), snoop filters and memory streaming technologies that are incorporated into IBM BlueGene/P and Q and ARM cores, and computer system performance evaluation methodologies that have been in use by AMD, HP and Google PerKit . He has shown that hardware memory consistency models are neither necessary (in the 90's) nor sufficient (a decade later) to achieve high performance in multiprocessor systems. These results eventually led to fence speculation in modern microprocessors. His latest work on workload-optimized server processors laid the foundation for the first generation of Cavium ARM server CPUs, ThunderX. He is a recipient of an NSF CAREER award, IBM Faculty Partnership Awards, and an Alfred P. Sloan Research Fellowship. He is a fellow of IEEE and ACM.

Official source

https://edu.epfl.ch/coursebook/en/introduction-to-multiprocessor-architecture-CS-307

Moodle Page

http://go.epfl.ch/CS-307

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Summary

Lectures

Instructor

Babak Falsafi

Official source

https://edu.epfl.ch/coursebook/en/introduction-to-multiprocessor-architecture-CS-307

Moodle Page

http://go.epfl.ch/CS-307

Lectures in this course (38)

Introduction to Multiprocessor Architecture

Introduces the fundamentals of multiprocessor architecture, covering post-Moore servers, sustainable datacenters, parallel programming, and GPU utilization.

Multiprocessors: Overview and Challenges

Covers the evolution and challenges of multiprocessors, emphasizing energy efficiency, parallel programming, cache coherence, and the role of GPUs.

Introduction to Multiprocessor Architecture

Covers multiprocessor architecture, sustainable computing, AI model training impact, and parallel programming fundamentals.

Principles of Parallel Computing: OpenMP

Explores the principles of parallel computing, focusing on OpenMP as a tool for creating concurrent code from serial code.

Parallelism: Programming and Performance

Explores parallelism in programming, emphasizing trade-offs between programmability and performance, and introduces shared memory parallel programming using OpenMP.

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