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. Prerequisite: programming in C/C++ or Fortran in the Linux environment and Linux shell proficiency (navigation, file copying, editing files in text-based editors, compilation).
Fundamentals of Parallelism on Intel Architecture
Offered By
Skills you will gain
Syllabus - What you will learn from this course
Modern Code
In the Introduction we will learn...
Vectorization
Multithreading with OpenMP
Memory Traffic
Top reviews from Fundamentals of Parallelism on Intel Architecture
Nice course, really enjoyed every challenge in the course. Well laid out goals for a Computer Science student.
Please bring advance courses by Intel also such as FPGA based courses.
Instructor
Andrey Vladimirov
Head of High-Performance Computing ResearchAbout Intel
Frequently Asked Questions
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Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
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