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High Performance Computing

Approx. 4 months

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Course Summary

Learn how to optimize the performance of your code and accelerate your computing applications with this High Performance Computing Course. Explore parallel programming and distributed computing to increase your efficiency and speed.

Key Learning Points

Understand the fundamentals of parallel computing and distributed computing
Optimize your code and increase application performance
Explore techniques for scaling your computing applications

Learning Outcomes

Develop the skills needed to create more efficient and faster computing applications
Understand the principles of parallel and distributed computing
Learn how to analyze the performance of your code and optimize it for better results

Prerequisites or good to have knowledge before taking this course

Basic knowledge of programming in C or C++
Familiarity with Linux command line

Course Difficulty Level

Intermediate

Course Format

Online self-paced course
Video lectures
Hands-on exercises

Similar Courses

Parallel Programming in C++
Distributed Systems
Scalable Machine Learning

Related Education Paths

Notable People in This Field

Chairman of Alphabet, Inc.
Computer Scientist and Professor at UC Berkeley
Principal Data Scientist at Booz Allen Hamilton

Related Books

Description

This course will give you solid foundations for developing, analyzing, and implementing parallel and locality-efficient algorithms. Offered at Georgia Tech as CS6220

Requirements

A "second course" in algorithms and data structures, a la Georgia Tech’sCS 3510-B or Udacity’s Intro to Algorithms For the programming assignments, programming experience in a "low-level" "high-level" language like C or C++ Experience using command line interfaces in *nix environments (e.g.,Unix, Linux) Course readiness survey. You should feel comfortable answering questions like those found in the Readiness Survey Course, HPC-0 See the Technology Requirements for using Udacity.

Knowledge

Instructor videosLearn by doing exercisesTaught by industry professionals

Outline

lesson 1 Work-Span or Dynamic Multithreading Model Intro to the basic algorithmic model Intro to OpenMP a practical programming model Comparison-based sorting algorithms Scans and linked list algorithms Tree algorithms Graph algorithms e.g. breadth-first search lesson 2 Distributed Memory or Network Models The basic algorithmic model Intro to the Message Passing Interface a practical programming model Reasoning about the effects of network topology Dense linear algebra Sorting Sparse graph algorithms Graph partitioning lesson 3 Two-Level Memory or I/O Models Basic models Efficiency metrics including “emerging” metrics like energy and power I/O-aware algorithms Cache-oblivious algorithms

Summary of User Reviews

Read reviews on Udacity's High Performance Computing course! Learners praised this course for its comprehensive curriculum and hands-on projects. Overall, users found the course helpful and informative.

Key Aspect Users Liked About This Course

The hands-on projects were a highlight for many learners.

Pros from User Reviews

Comprehensive curriculum
In-depth explanations of complex topics
Good balance of theory and practical applications
Engaging and knowledgeable instructors
Convenient online format

Cons from User Reviews

Some learners found the pacing too slow
Challenging for those without a background in computer science
Not enough focus on specific programming languages
Limited interaction with instructors and classmates
Occasional technical issues with the platform

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