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
Related Topics for further study
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
IntermediateCourse 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 CS6220Requirements
- 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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