This course is targeted to scientists, engineers, scholars, or anyone seeking to solve problems efficiently in high-performance computing environments or in the cloud. Students completing this course will have a basic understanding of how to find bottlenecks in their programs as well as how to address those bottlenecks. The course will provide a high-level introduction to modern compute node architectures of high-performance and cloud computing instances.
Efficient Programming
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
7 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
Describe the computing and memory architecture of a supercomputing node or cloud computing instance
Utilize compiler and libraries to increase the performance of your program
Understand how to utilize vector operations of a modern microprocessor to maximize performance
Use OpenMP directives to improve vectorization of your programs
Skills you'll gain
Details to know
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Recently updated!
August 2025
Assessments
5 assignments
Taught in English
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There are 5 modules in this course
In this module, we cover an approach to analyze and optimize program performance, such as profiling, using optimized libraries, and compiler options for increasing efficiency.
What's included
5 videos2 readings1 assignment1 programming assignment
In this module, we examine simple techniques that help with program performance. We are looking at scalar and loop optimization methods that can have a large impact on a program’s floating-point performance.
What's included
5 videos1 assignment1 programming assignment
In this module, we introduce the basic architecture of modern computers focusing on how the architecture influences program performance. We are looking at processor level data parallelism and how optimized code for parallelism has a much increased floating-point performance.
What's included
4 videos1 assignment1 programming assignment
Memory performance is generally the main performance bottleneck since the speed of the main memory has not kept up with the capabilities of processors to process floating-point numbers. We introduce how layers of fast memory, called cache memory, can speed up computations and provide an example of how to optimize algorithms for better memory performance.
What's included
4 videos1 assignment1 programming assignment
This module will provide an introduction to parallel and high throughput computing. It will also demonstrate slurm job arrays, where there are mechanisms for working with many similar jobs quickly and easily. Finally, this module will look at running many jobs concurrently with GNU Parallel.
What's included
4 videos1 assignment1 programming assignment
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