A Fast Poisson Solver for Hybrid Reconfigurable System

Gomes, Vitor Conrado Faria; Velho, Haroldo Campos; Charão, Andrea Schwertner

doi:10.1007/978-3-642-36812-7_5

Cited by 2 publications

(1 citation statement)

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“…Another example is Hu [5], who examined, among other numerical algorithms, the conjugate gradient (CG) method on reconfigurable hardware. The solution of Poisson's equation on a hybrid reconfigurable system consisting of a CPU and an FPGA is described by Gomes et al [6].…”

Section: Related Workmentioning

confidence: 99%

Reconfigurable Hardware Generation of Multigrid Solvers with Conjugate Gradient Coarse-Grid Solution

Schmitt

Schmid

Kuckuk

et al. 2018

Parallel Process. Lett.

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Not only in the field of high-performance computing (HPC), field programmable gate arrays (FPGAs) are a soaringly popular accelerator technology. However, they use a completely different programming paradigm and tool set compared to central processing units (CPUs) or even graphics processing units (GPUs), adding extra development steps and requiring special knowledge, hindering widespread use in scientific computing. To bridge this programmability gap, domain-specific languages (DSLs) are a popular choice to generate low-level implementations from an abstract algorithm description. In this work, we demonstrate our approach for the generation of numerical solver implementations based on the multigrid method for FPGAs from the same code base that is also used to generate code for CPUs using a hybrid parallelization of MPI and OpenMP. Our approach yields in a hardware design that can compute up to 11 V-cycles per second with an input grid size of 4096 × 4096 and solution on the coarsest using the conjugate gradient (CG) method on a mid-range FPGA, beating vectorized, multi-threaded execution on an Intel Xeon processor.

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Section: Related Workmentioning

confidence: 99%