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micro-module

GPU Architectures and Programming

GPU Architectures and Programming

Providing you with hands-on experience in solving computationally intensive tasks faster and with lower energy consumption
Closed for application

Description

The course begins by providing a broad motivation for the design of multi- and many-core processors such as graphics processing units (GPUs). The first phase covers basic GPU concepts, including the evolution of GPU computing, a high-level overview of GPU architecture, and key differences from CPU architecture. Supplementary material is provided for students without a background in computer architecture fundamentals. Once a basic understanding is established, the module introduces the programming of GPUs using CUDA. The curriculum then delves into advanced concepts from both an architectural and programming perspective. To reinforce the theoretical knowledge gained in the lectures, students will engage in progressively more complex exercises throughout the module.

Study format
Hybrid
Application period
23 February – 22 March 2024
Study period
2 April – 10 July 2024
Credits
3 ECTS
Pace
20%
Hosting university
Hamburg University of Technology
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Learning outcomes

Understanding of the architecture of massively parallel GPUs

At the end of the course learner will gained a comprehensive understanding of the underlying architecture of massively parallel Graphics Processing Units (GPUs).

ESCO SKILLS

Effective GPU programming

By the end of the course lerners will be equiped with the skills necessary for effective GPU programming and be able to do programming.

ESCO SKILLS

Solve computationally intensive tasks faster and with lower energy consumption

By the end of the course students will be able to solve computationally intensive tasks faster and with lower energy consumption.

ESCO SKILLS

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Information

The course begins by providing a broad motivation for the design of multi- and many-core processors such as graphics processing units (GPUs). The first phase covers basic GPU concepts, including the evolution of GPU computing, a high-level overview of GPU architecture, and key differences from CPU architecture. Supplementary material is provided for students without a background in computer architecture fundamentals. Once a basic understanding is established, the module introduces the programming of GPUs using CUDA. The curriculum then delves into advanced concepts from both an architectural and programming perspective. To reinforce the theoretical knowledge gained in the lectures, students will engage in progressively more complex exercises throughout the module.

Hosting university

Hamburg University of Technology

Hamburg University of Technology