Fast electromagnetic integral-equation solvers on graphics processing units

Shaojing Li*, Ruinan Chang, Amir Boag, Vitaliy Lomakin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


A survey of electromagnetic integral-equation solvers, implemented on graphics processing units (GPUs), is presented. Several key points for efficient GPU implementations of integral-equation solvers are outlined. Three spatial-interpolation-based algorithms, including the Nonuniform-Grid Interpolation Method (NGIM), the box Adaptive-Integral Method (B-AIM), and the fast periodic interpolation method (FPIM), are described to show the basic principles for optimizing GPU-accelerated fast integral-equation algorithms. It is shown that proper implementations of these algorithms lead to very high computational performance, with GPU-CPU speed-ups in the range of 100-300. Critical points for these accomplishments are (i) a proper arrangement of the data structure, (ii) an on-the-fly approach, trading excessive memory usage with increased arithmetic operations and data uniformity, and (iii) efficient utilization of the types of GPU memory. The presented methods and their GPU implementations are geared towards creating efficient electromagnetic integral-equation solvers. They can also find a wide range of applications in a number of other areas of computational physics.

Original languageEnglish
Article number6348120
Pages (from-to)71-87
Number of pages17
JournalIEEE Antennas and Propagation Magazine
Issue number5
StatePublished - 2012


FundersFunder number
United States - Israel Binational Science Foundation2008077


    • Computational electromagnetics
    • electromagnetic analysis
    • graphics processing units
    • high performance computing
    • integral equations


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