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.

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Intermediate level

Recommended experience

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

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Taught in English

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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++

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

CUDA at Scale for the Enterprise

Course 328 hours3.2 (11 ratings)

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 Courses15,014 learners

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