Johns Hopkins University
GPU Programming Specialization
Johns Hopkins University

GPU Programming Specialization

Solve Challenges with Powerful GPUs. Develop mastery in high performance computing and apply to numerous fields.

Taught in English

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Specialization - 4 course series

Get in-depth knowledge of a subject

Intermediate level

Recommended experience

2 months at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Develop CUDA software for running massive computations on commonly available hardware

  • Utilize libraries that bring well-known algorithms to software without need to redevelop existing capabilities

Details to know

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Specialization - 4 course series

Get in-depth knowledge of a subject

Intermediate level

Recommended experience

2 months at 10 hours a week
Flexible schedule
Learn at your own pace

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  • Learn in-demand skills from university and industry experts
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Specialization - 4 course series

What you'll learn

  • Students will learn how to develop concurrent software in Python and C/C++ programming languages.

  • Students will gain an introductory level of understanding of GPU hardware and software architectures.

Skills you'll gain

Category: Cuda
Category: Python Programming
Category: Thread (Computing)
Category: C++

Introduction to Parallel Programming with CUDA

Course 221 hours3.0 (28 ratings)

What you'll learn

  • Students will learn how to utilize the CUDA framework to write C/C++ software that runs on CPUs and Nvidia GPUs.

  • Students will transform sequential CPU algorithms and programs into CUDA kernels that execute 100s to 1000s of times simultaneously on GPU hardware.

Skills you'll gain

Category: Cuda
Category: Algorithms
Category: GPU
Category: C/C++
Category: Nvidia

What you'll learn

  • Students will learn to develop software that can be run in computational environments that include multiple CPUs and GPUs.

  • Students will develop software that uses CUDA to create interactive GPU computational processing kernels for handling asynchronous data.

  • Students will use CUDA, hardware memory capabilities, and algorithms/libraries to solve programming challenges including image processing.

Skills you'll gain

Category: Cuda
Category: Algorithms
Category: GPU
Category: C/C++
Category: Nvidia

CUDA Advanced Libraries

Course 425 hours

What you'll learn

  • You will learn to develop software that performs high-level mathematics operations using libraries such as cuFFT and cuBLAS.

  • You will learn to use the Thrust library to perform a number of data manipulation and data structures that abstract away memory management.

  • You will learn to develop machine learning software for a variety of purposes using neural networks modeled using the cuTensor and cuDNN libraries.

Skills you'll gain

Category: Data Science
Category: Artificial Neural Network
Category: C++
Category: Machine Learning
Category: Linear Algebra

Instructor

Chancellor Thomas Pascale
Johns Hopkins University
4 Courses11,175 learners

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