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| Content Provider | ACM Digital Library |
|---|---|
| Author | Krüger, Jens Westermann, Rüdiger |
| Copyright Year | 2003 |
| Abstract | In this work, the emphasis is on the development of strategies to realize techniques of numerical computing on the graphics chip. In particular, the focus is on the acceleration of techniques for solving sets of algebraic equations as they occur in numerical simulation. We introduce a framework for the implementation of linear algebra operators on programmable graphics processors (GPUs), thus providing the building blocks for the design of more complex numerical algorithms. In particular, we propose a stream model for arithmetic operations on vectors and matrices that exploits the intrinsic parallelism and efficient communication on modern GPUs. Besides performance gains due to improved numerical computations, graphics algorithms benefit from this model in that the transfer of computation results to the graphics processor for display is avoided. We demonstrate the effectiveness of our approach by implementing direct solvers for sparse matrices, and by applying these solvers to multi-dimensional finite difference equations, i.e. the 2D wave equation and the incompressible Navier-Stokes equations. |
| Starting Page | 908 |
| Ending Page | 916 |
| Page Count | 9 |
| File Format | |
| ISSN | 07300301 |
| e-ISSN | 15577368 |
| DOI | 10.1145/882262.882363 |
| Volume Number | 22 |
| Issue Number | 3 |
| Journal | ACM Transactions on Graphics (TOG) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2003-07-01 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Graphics hardware Numerical simulation |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Graphics and Computer-Aided Design |
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