Multiprocessors are basic building blocks for all computer systems. This course covers the architecture and organization of modern multiprocessors, prevalent accelerators (e.g., GPU, TPU), and datacen
This hands-on course teaches the tools & methods used by data scientists, from researching solutions to scaling up
prototypes to Spark clusters. It exposes the students to the entire data science pipe
This course will teach operating systems and networks in an integrated fashion,emphasising the fundamental concepts and techniques that make their interaction possible/practical. Core lectures will be
This course completes the overview of computer architecture started on the first year (CS-173 DSD).
Computing is nowadays distributed over several machines, in a local IP-like network, a cloud or a P2P network. Failures are common and computations need to proceed despite partial failures of machin
The course studies techniques to exploit Instruction-Level Parallelism (ILP) statically and dynamically. It also addresses some aspects of the design of domain-specific accelerators. Finally, it explo
This course provides insight into a broad variety of High Performance Computing (HPC) concepts and the majority of modern HPC architectures. Moreover, the student will learn to have a feeling about wh
Hardware-software co-design is a well known concept in embedded system design.It is also a concept required in designing FPGA-accelerators in data-centers.This course teaches how to transform algorith
This course covers the data management system design concepts using a hands-on approach.
With the advent of modern architectures, it becomes crucial to master the underlying algorithmics of concurrency. The objective of this course is to study the foundations of concurrent algorithms and
