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An overview of GPUs and their use in supercomputers. This workshop will explain what GPUs are, and cover the basic ideas of GPU use in scientific computing. We will introduce several GPU programming frameworks, and demonstrate how to accelerate a solution of a science problem using a GPU. Prior knowledge of programming (in any language) is recommended to be able to follow the exercise part of the workshop.

This is an introductory course covering programming and computing on GPUs (graphics processing unit) which are an increasingly common presence in massively parallel computing architectures. The basics of GPU programming will be covered, and students will work through a number of hands on examples. The structuring of data and computations that makes full use of the GPU will be discussed in detail. This year the course will expand to cover the new features available on the GPUs installed on the Graham supercomputer at the University of Waterloo. Students should be able to leave the course with the knowledge necessary to begin developing their own GPU applications. -- Prerequisites: C/C++ scientific programming, experience editing and compiling code in a Linux environment. Some experience with CUDA and/or OpenMP a plus.

Part of the 2017 Ontario Summer School.

The goal is for students, new to GPGPU but familiar with programming in C, to leave being able to write simple kernels for their own problems, and understand the tools and techniques needed to improve the results.

The goal is for students, new to GPGPU but familiar with programming in C, to leave being able to write simple kernels for their own problems, and understand the tools and techniques needed to improve the results.

Part of the Ontario Summer School on High Performance Computing 2013 -Toronto