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Data-Parallel Programming on the Cell BE and the GPU using the RapidMind Development Platform
| Content Provider | Semantic Scholar |
|---|---|
| Author | McCool, Michael D. |
| Copyright Year | 2006 |
| Abstract | The Cell BE processor is capable of achieving very high levels of performance via parallel computation. The processors in video accelerators, known as GPUs, are also high performance parallel processors. The RapidMind Development Platform provides a simple data-parallel model of execution that is easy to understand and learn, is usable from any ISO standard C++ program without any special extensions, maps efficiently onto the capabilities of both the Cell BE processor and GPUs, and can be extended to other multicore processors in the future. The RapidMind platform acts as an embedded programming language inside C++. It is built around a small set of types that can be used to capture and specify arbitrary computations. Arbitrary functions, including control flow, can be specified dynamically. Parallel execution is primarily invoked by applying these functions to arrays, generating new arrays. Access patterns on arrays allow data to be collected and redistributed. Collective operations, such as scatter, gather, and programmable reduction, support other standard parallel communication patterns and complete the programming model. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://web.cs.ucla.edu/~palsberg/course/cs239/papers/mccool.pdf |
| Alternate Webpage(s) | http://www.rapidmind.net/dprm.pdf |
| Alternate Webpage(s) | http://www.cs.ucla.edu/~palsberg/course/cs239/F07/papers/mccool.pdf |
| Alternate Webpage(s) | http://www.cs.ucla.edu/~palsberg/course/cs239/papers/mccool.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
