CUDA at Scale for the Enterprise
Master enterprise-level GPU programming with CUDA. Learn multi-GPU systems, asynchronous processing, and advanced algorithms.
Master enterprise-level GPU programming with CUDA. Learn multi-GPU systems, asynchronous processing, and advanced algorithms.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full GPU Programming Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
3.4
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What you'll learn
Develop software for multiple CPU/GPU systems
Implement asynchronous workflows with CUDA events and streams
Create scalable enterprise-level GPU applications
Optimize sorting algorithms for GPU execution
Master image processing with NPP libraries
Skills you'll gain
This course includes:
3 Hours PreRecorded video
2 peer reviews, 4 programming assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This advanced course focuses on developing scalable GPU applications for enterprise environments. Students learn to manage multiple CPU/GPU systems, implement asynchronous workflows using CUDA events and streams, and develop complex algorithms for data processing. The curriculum covers advanced topics including multi-GPU programming, sorting algorithms, and image processing using NVIDIA Performance Primitives (NPP). Emphasis is placed on real-world enterprise applications and performance optimization.
Course Overview
Module 1 · 3 Hours to complete
Multiple CPU/GPU Systems
Module 2 · 9 Hours to complete
CUDA Events and Streams
Module 3 · 3 Hours to complete
Sorting Using GPUs
Module 4 · 5 Hours to complete
Image Processing using Nvidia Programming Primitives
Module 5 · 6 Hours to complete
Fee Structure
Instructor
Innovator in Computer Science Education
Chancellor Pascale has been a faculty member at Johns Hopkins University's Whiting School of Engineering for over 10 years, specializing in the Computer Science department. He earned his undergraduate degree in Computer Science from Drexel University and a Master’s degree from Johns Hopkins University. With over 15 years of experience in software and service development, he focuses on web applications, AI/ML for image and language translation, and network management. Chancellor Pascale was awarded the Fulbright-Nehru Fellowship, where he led a three-week workshop on Linux API development at Stella Maris College in Chennai, India.
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3.4 course rating
10 ratings
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