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Learning Outcomes

Subject Specific Practical Skills

Having successfully completed this module you will be able to:

• Use C++ to accelerate a given function using threads and SIMD
• Use CUDA or OpenCL to accelerate a given function using a GPU or FPGA

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• Analyse a given program and identify opportunities for parallelism
• Analyse a parallel algorithm and choose an appropriate programming paradigm and hardware target
• Identify data-races in a program and use locking or synchronisation to remove them

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

• Explain parallelism using the concept of an iteration space
• Describe the types of parallelism provided by contemporary hardware platforms
• Explain how parallelism can speed-up programs, and why this speed-up is often limited

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.