TY - JOUR
AU - Westermann, Rüdiger
AB -  Linear Algebra Operators for GPU Implementation of Numerical Algorithms Jens Kr¨ ger and R¨ diger Westermann u u Computer Graphics and Visualization Group, Technical University Munich — Figure 1: We present implementations of techniques for solving sets of algebraic equations on graphics hardware. In this way, numerical simulation and rendering of real-world phenomena, like 2D water surfaces in the shown example, can be achieved at interactive rates. 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 ef cient communication on modern GPUs. Besides performance gains due to improved numerical computations, graphics algorithms bene t from this model in that the transfer of computation results to the graphics processor for display is avoided. We demonstrate 
TI - Linear algebra operators for GPU implementation of numerical algorithms
DO - 10.1145/1198555.1198795
DA - 2005-07-31
UR - https://www.deepdyve.com/lp/association-for-computing-machinery/linear-algebra-operators-for-gpu-implementation-of-numerical-12qiF0RgTA
DP - DeepDyve
ER -