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Fundamentals of Parallelism on Intel Architecture (Coursera)

This course will introduce you to the multiple forms of parallelism found in modern Intel architecture processors and teach you the programming frameworks for handling this parallelism in applications. You will get access to a cluster of modern manycore processors (Intel Xeon Phi architecture) for experiments with graded programming exercises.

This course can apply to various HPC and datacenter workloads and framework including artificial intelligence (AI). You will learn how to handle data parallelism with vector instructions, task parallelism in shared memory with threads, parallelism in distributed memory with message passing, and memory architecture parallelism with optimized data containers. This knowledge will help you to accelerate computational applications by orders of magnitude, all the while keeping your code portable and future-proof.

Who is this class for: For developers of machine learning libraries and frameworks. For innovators looking to combine machine learning and traditional computing in artificial intelligence systems. For engineers, students and researchers in computational disciplines interested in parallel computing.

Syllabus

WEEK 1

Modern Code

In the Introduction we will learn…

Graded: Modern code

Graded: Hello World

WEEK 2

Vectorization

Graded: Vectorization

Graded: Vectorizing Monte-Carlo Diffusion

WEEK 3

Multithreading with OpenMP

Graded: OpenMP

Graded: Multithreaded Filtering

WEEK 4

Memory Traffic

Graded: Memory traffic

Graded: Batch FFTs in HBM

WEEK 5

Clusters and MPI

Graded: MPI

Graded: MPI String Vibration

ENROLL IN COURSE