LU-GPU: Efficient Algorithms for Solving Dense Linear Systems on Graphics Hardware Session: High End Computing Technologies Event Type: Paper Time: 11:30am - 12:00pm Session Chair: John L Gustafson Speaker(s): Nico Galoppo, Naga K. Govindaraju, Michael Henson, Dinesh Manocha Location: 606-607 Abstract: We present a novel algorithm to solve dense linear systems using graphics processors (GPUs). We reduce matrix decomposition and row operations to a series of rasterization problems on the GPU. These include new techniques for streaming index pairs, swapping rows and columns and parallelizing the computation to utilize multiple vertex and fragment processors. We also use appropriate data representations to match the rasterization order and cache technology of graphics processors. We have implemented our algorithm on different GPUs and compared the performance with optimized CPU implementations. In particular, our implementation on a NVIDIA GeForce 7800 GPU outperforms a CPU-based ATLAS implementation. Moreover, our results show that our algorithm is cache and bandwidth efficient and scales well with the number of fragment processors within the GPU and the core GPU clock rate. We use our algorithm for fluid flow simulation and demonstrate that the commodity GPU is a useful co-processor for many scientific applications. This paper can be found in the ACM and IEEE Digital Libaries Click here for ACM Click here for IEEE Chair/Speaker Details: John L Gustafson (Chair) ClearSpeed Technology, Inc. Nico Galoppo UNC Naga K. Govindaraju UNC Michael Henson UNC Dinesh Manocha UNC