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CUDA at Scale for the Enterprise
This course will aid in students in learning in concepts that scale the use of GPUs and the CPUs that manage their use beyond the most common consumer-grade GPU installations. They will learn how to manage asynchronous workflows, sending and receiving events to encapsulate data transfers and control signals. Also, students will walk through application of GPUs to sorting of data and processing images, implementing their own software using these techniques and libraries.
By the end of the course, you will be able to do the following:
- Develop software that can use multiple CPUs and GPUs
- Develop software that uses CUDA’s events and streams capability to create asynchronous workflows
- Use the CUDA computational model to to solve canonical programming challenges including data sorting and image processing
To be successful in this course, you should have an understanding of parallel programming and experience programming in C/C++.
This course will be extremely applicable to software developers and data scientists working in the fields of high performance computing, data processing, and machine learning.
Duration
8 Months
Institution
Johns Hopkins University
Format
Online
Eligibility Criteria
school
Academic Foundation
A recognized Bachelor’s degree or high school equivalent required for admission into Johns Hopkins University.
language
Language Proficiency
English proficiency required. IELTS, TOEFL, or standard medium-of-instruction certificates accepted.
Detailed Fees Breakdown
Base Tuition Fee
$212
Total Est. Investment
$212
Scholarships and early-bird waivers may apply. Contact admissions for exact institutional fees.
Academic Trajectory
Program Outcome
Graduates of the CUDA at Scale for the Enterprise program at Johns Hopkins University are equipped with global perspectives, ready to excel in international markets and top-tier career opportunities.