GPU computing is a relatively nascent technology. Nonetheless, its potential to greatly accelerate program performance is well known. However, so too is its complexity. For the GPU is a specialized processor with niche applications - a program’s suitability for GPU-based execution can only truly be determined following extensive prerequisite analysis. Furthermore, the porting and tuning process is highly involved, requiring an intimate understanding of the target hardware. Consequently, development times can become prolonged. For organisations with extensive legacy codes, the challenge is greater still. They cannot necessarily afford to rewrite their software using the latest Application Programming Interfaces or Domain Specific Languages, no matter how simplified they might be. Such organisations might consider the likes of NVIDIA’S OpenACC compiler, theoretically enabling them to quickly leverage the benefits of GPU computing today by way of program annotations. But how can such a compiler enable their serial programmers to prepare for the parallel programming of tomorrow? The answer - as a black-box, it cannot. But what if there were a development environment that provided the benefits of such a compiler - acceleration in a timely, cost effective manner - and yet at the same time, provided programmers with the tools to understand how the accelerated program was derived? In this way, programmers could learn “on the job” and become the experts that their organisations will need tomorrow. This thesis describes the inception, development and evaluation of such an environment, namely Paralysis - an extensible guidance environment for program PARALIelization and analYSIS, tiered for varying programmer competencies. Ultimately, Paralysis achieves in minutes what took months to achieve when coding manually. Furthermore, Paralysis is not only found to provide better insight than NVIDIA’s OpenACC compiler, it is also found to outperform it in three out of nine evaluation case-studies and to achieve comparable performance in the remaining six.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:727745 |
| Date | January 2017 |
| Creators | McCool, Stuart |
| Publisher | Queen's University Belfast |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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