Computer Architecture

МООК
en
Английский
55 h
This content is rated 4.3 out of 5
Source
  • From www.coursera.org
Conditions
  • Self-paced
  • Free Access
  • Fee-based Certificate
More info
  • 11 Sequences
  • Advanced Level

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Course details

Syllabus

  • Week 1 - Introduction, Instruction Set Architecture, and Microcode
    This lecture will give you a broad overview of the course, as well as the description of architecture, micro-architecture and instruction set architectures.
  • Week 1 - Pipelining Review
    This lecture covers the basic concept of pipeline and two different types of hazards.
  • Week 2 - Cache Review
    This lecture covers control hazards and the motivation for caches.
  • Week 2 - Superscalar 1
    This lecture covers cache characteristics and basic superscalar architecture.
  • Week 3 - Superscalar 2 & Exceptions
    This lecture covers the common issues for superscalar architecture.
  • Week 3 - Superscalar 3
    This lecture covers different kinds of architectures for out-of-order processors.
  • Week 4 - Superscalar 4
    This lecture covers the common methods used to improve the performance of out-of-order processors including register renaming and memory disambiguation.
  • Week 4 - VLIW 1
    This lecture covers the basic concept of very long instruction word (VLIW) processors.
  • Week 5 - VLIW2
    This lecture covers the common methods used to improve VLIW performance.
  • Week 5 - Branch Prediction
    This lecture covers the motivation and implementation of branch predictors.
  • Week 6 - Advanced Caches 1
    This lecture covers the advanced mechanisms used to improve cache performance.
  • Week 6 - Advanced Caches 2
    This lecture covers more advanced mechanisms used to improve cache performance.
  • Week 7 - Memory Protection
    This lecture covers memory management and protection.
  • Week 7 - Vector Processors and GPUs
    This lecture covers the vector processor and optimizations for vector processors.
  • Week 8 - Multithreading
    This lecture covers different types of multithreading.
  • Week 8 - Parallel Programming 1
    This lecture covers the concepts of parallelism, consistency models, and basic parallel programming techniques.
  • Week 9 - Parallel Programming 2
    This lecture covers the solutions for the consistency problem in parallel programming.
  • Week 9 - Small Multiprocessors
    This lecture covers the implementation of small multiprocessors.
  • Week 10 - Multiprocessor Interconnect 1
    This lecture covers the design of interconnects for a multiprocessor.
  • Week 10 - Multiprocessor Interconnect 2
    This lecture covers the design of interconnects for multiprocessor and network topology.
  • Week 11 - Large Multiprocessors (Directory Protocols)
    This lecture covers the motivation and implementation of directory protocol used for coherence on large multiproccesors.

Prerequisite

None.

Instructors

David Wentzlaff
Associate Professor
Electrical Engineering

Editor

L'université de Princeton aussi appelée Princeton est une université américaine privée située dans la ville de Princeton (New Jersey), aux États-Unis. Fondée en 1746, elle est le quatrième plus ancien établissement d'enseignement supérieur des États-Unis.

Arrivant parmi les premières universités au monde dans la plupart des classements internationaux, elle jouit d'un grand prestige1. Elle est membre de la Ivy League où elle entretient une rivalité historique avec l'université Harvard et l'université Yale2.

Elle a formé 65 prix Nobel, 15 médailles Fields, 21 National Medal of Science, 11 National Humanities Medal, 3 présidents américains et 12 juges à la Cour suprême des États-Unis.

Platform

Coursera - это цифровая компания, предлагающая массовые открытые онлайн-курсы, основанные учителями компьютеров Эндрю Нгом и Стэнфордским университетом Дафни Коллер, расположенные в Маунтин-Вью, штат Калифорния.

Coursera работает с ведущими университетами и организациями, чтобы сделать некоторые из своих курсов доступными в Интернете, и предлагает курсы по многим предметам, включая: физику, инженерию, гуманитарные науки, медицину, биологию, социальные науки, математику, бизнес, информатику, цифровой маркетинг, науку о данных и другие предметы.

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