Some aspects of the parallel and distributed iterative algorithms—a survey
Automatica (Journal of IFAC)
An FPGA implementation and performance evaluation of the Serpent block cipher
FPGA '00 Proceedings of the 2000 ACM/SIGDA eighth international symposium on Field programmable gate arrays
Design and Implementation of the MorphoSys Reconfigurable ComputingProcessor
Journal of VLSI Signal Processing Systems - Special issue on VLSI on custom computing technology
A multigrid tutorial: second edition
A multigrid tutorial: second edition
Reconfigurable computing: a survey of systems and software
ACM Computing Surveys (CSUR)
Embedded System Design: A Unified Hardware/Software Introduction
Embedded System Design: A Unified Hardware/Software Introduction
A multigrid solver for boundary value problems using programmable graphics hardware
Proceedings of the ACM SIGGRAPH/EUROGRAPHICS conference on Graphics hardware
Sparse matrix solvers on the GPU: conjugate gradients and multigrid
ACM SIGGRAPH 2003 Papers
Practical fpga programming in c
Practical fpga programming in c
Journal of Real-Time Image Processing
| Hi-index | 7.29 |
The problem of finding the solution of partial differential equations (PDEs) plays a central role in modeling real world problems. Over the past years, Multigrid solvers have showed their robustness over other techniques, due to its high convergence rate which is independent of the problem size. For this reason, many attempts for exploiting the inherent parallelism of Multigrid have been made to achieve the desired efficiency and scalability of the method. Yet, most efforts fail in this respect due to many factors (time, resources) governed by software implementations. In this paper, we present a hardware implementation of the V-cycle Multigrid method for finding the solution of a 2D-Poisson equation. We use Handel-C to implement our hardware design, which we map onto available field programmable gate arrays (FPGAs). We analyze the implementation performance using the FPGA vendor's tools. We demonstrate the robustness of Multigrid over other similar iterative solvers, such as Jacobi and successive over relaxation (SOR), in both hardware and software. We compare our findings with a C++ version of each algorithm. The obtained results show better performance when compared to existing software versions.