The University of Sheffield
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COM6521   Parallel Computing with Graphical Processing Units (GPUs)   (15 credits)

 
Year Running: 2018/2019
Credit level: F7
Additional Information   This module has a large amount of practical programming. Only students with a strong programming background should participate. The maximum number of students allowed on the module is 65.

Description

Accelerator architectures are discrete processing units which supplement a base processor with the objective of providing advanced performance at lower energy cost. Performance is gained by a design which favours a high number of parallel compute cores at the expense of imposing significant software challenges. This module looks at accelerated computing from multi-core central processing units (CPUs) to graphics processing unit (GPU) accelerators with many TFlops of theoretical performance. The module will give insight into how to write high performance code with specific emphasis on GPU programming with NVIDIA CUDA GPUs. A key aspect of the module will be understanding what the implications of program code are on the underlying hardware so that it can be optimised. Students should be aware that there are limited places available on this course. 

 

Reading List


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Teaching Methods

Delivery Type Hours
Independent 105.0
Lecture 19.0
Problem Solving 2.0
Tutorial 24.0
 

Methods of assessment

Assessment Type Duration % of formal assessment Semester
Course Work 0.0 80 % S2
Other 0.0 20 % S2
 

Teaching methods and assessment displayed on this page are indicative for 2023-24.