1999/06/08 by T. Kuberka, A. Kugel, Kuberka, T. +10
Computer Science · Engineering · Mathematics · Physics and Astronomy · #Advanced Data Storage Technologies #Algorithm #Algorithms and Data Compression #Astrophysics (astro-ph) #Computation #Computational science #Computer science #Embedded system #Engineering #FLOPS #FOS: Physical sciences #Field-programmable gate array #Flexibility (engineering) #Host (biology) #Mathematics #Operating system #Parallel Computing and Optimization Techniques #Parallel computing #Range (aeronautics) #Scalability #Workstation #astro-ph
paper · pdf · doi:10.48550/arxiv.astro-ph/9906153
7 pages, 3 figures, to appear in Procs. of The 1999 International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA 99), Las Vegas, USA
arxiv created 1999/06/08 · openalex publication_date 1999/06/08 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In astrophysics numerical star cluster simulations and hydrodynamical methods like SPH require computational performance in the petaflop range. The GRAPE family of ASIC-based accelerators improves the cost-performance ratio compared to general purpose parallel computers, however with limited flexibility. The AHA-GRAPE architecture adds a reconfigurable FPGA-processor to accelerate the SPH computation. The basic equations of the algorithm consist of three parts each scaling with the order of O(N), O(N*Nn), and O(N**2) respectively, where N is in the range of 10**4 to 10**7 and Nn approximately 50. These equations can profitably be distributed across a host workstation, an FPGA processor, and a GRAPE subsystem. With the new ATLANTIS FPGA processor we expect a scalable SPH performance of 1.5 Gflops per board. The first prototype AHA-GRAPE system will be available in mid-2000. This 3-layered system will deliver an increase in performance by a factor of 10 as compared to a pure GRAPE solution.