227-0150-00L  Energy-Efficient Parallel Computing Systems for Data Analytics

SemesterFrühjahrssemester 2018
DozierendeL. Benini
Periodizitätjährlich wiederkehrende Veranstaltung
LehrspracheEnglisch
KommentarPreviously called "Advanced System-on-chip Design: Integrated Parallel Computing Architectures"


KurzbeschreibungAdvanced Parallel Computing Architectures and related design issues. It will cover multi-cores, many-cores, vector engines, GP-GPUs, application-specific processors and heterogeneous compute accelerators. Focus on integrated architectures for data analytics applications. Special emphasis given to energy-efficiency issues and hardware-software design for power and energy minimizazion.
LernzielGive in-depth understanding of the links and dependencies between architectures and their energy-efficient implementation and to get a comprehensive exposure to state-of-the-art computing platforma for data anlytics applications. Practical experience will also be gained through practical exercises and mini-projects (hardware and software) assigned on specific topics.
InhaltThe course will cover advanced parallel computing architectures architectures, with an in-depth view on design challenges related to advanced silicon technology and state-of-the-art system integration options (nanometer silicon technology, novel storage devices, three-dimensional integration, advanced system packaging). The emphasis will be on programmable parallel architectures, namely, multi and many- cores, GPUs, vector accelerators, application-specific processors, heterogeneous platforms, and the complex design choices required to achieve scalability and energy proportionality. The course will will also delve into system design, touching on hardware-software tradeoffs and full-system analysis and optimization taking into account non-functional constraints and quality metrics, such as power consumption, thermal dissipation, reliability and variability. The application focus will be on emerging data analytics both in the cloud at at the edges (near-sensor analytics).
SkriptSlides will be provided to accompany lectures. Pointers to scientific literature will be given. Exercise scripts and tutorials will be provided.
LiteraturD. Patterson, J. Hennessy, Computer Architecture, Fifth Edition: A Quantitative Approach (The Morgan Kaufmann Series in Computer Architecture and Design), 2011.

D. Patterson, J. Hennessy, Computer Organization and Design, Fifth Edition: The Hardware/Software Interface (The Morgan Kaufmann Series in Computer Architecture and Design), 2013.
Voraussetzungen / BesonderesKnowledge of digital design at the level of "Design of Digital Circuits SS12" is required.

Knowledge of basic VLSI design at the level of "VLSI I: Architectures of VLSI Circuits" is required