Using GPU With CUDA to Accelerate MoM-Based Electromagnetic Simulation of Wire-Grid Models

Topa, T.; Karwowski, A.; Нога, А.

doi:10.1109/lawp.2011.2144557

Cited by 39 publications

(24 citation statements)

References 8 publications

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“…A noticeable feature of this latter is that the two most computationally intensive phases of MoM, that is, the assembly of the system matrix and the solution of the matrix equation have been accelerated by employing the GPU device. The CPU sequential procedures for computing the elements of the system matrix have been mapped to parallel GPU platform as described in [20]. To enable the solution of relatively large-size problems with MoM-generated matrix exceeding the amount of memory available on the device, a hybrid out-of-GPU memory CULA-panel-based LU decomposition algorithm have been implemented [21].…”

Section: Hybrid Cpu/gpu Implementationmentioning

confidence: 99%

See 1 more Smart Citation

An Efficient Framework for Analysis of Wire-Grid Shielding Structures over a Broad Frequency Range

Karwowski¹,

Нога²,

Topa³

2016

RADIOENGINEERING

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Section: Hybrid Cpu/gpu Implementationmentioning

confidence: 99%

“…1 explains how the CPU/GPU computations are organized. The interested reader is referred to [20], [21] and [23] for more details. …”

Section: Hybrid Cpu/gpu Implementationmentioning

confidence: 99%

An Efficient Framework for Analysis of Wire-Grid Shielding Structures over a Broad Frequency Range

Karwowski¹,

Нога²,

Topa³

2016

RADIOENGINEERING

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“…Parallelism is the future of computing [9] and the interest of the Antennas and Propagation community in topics of high performance computing and, in particular, of parallel programming on GPUs to face computationally burdened problems has been remarkable, as witnessed by [2][3][4][5][6][7] and by other electromagnetic numerical methods which have benefitted from GPU computing [10][11][12][13][14][15][16][17]. From this starting point, it is clear that the electromagnetic community can take advantage of this technological evolution to employ ever-more sophisticated numerical methods.…”

Section: Introductionmentioning

confidence: 99%

Fast, Phase-Only Synthesis of Aperiodic Reflectarrays Using Nuffts and Cuda

Capozzoli¹,

Curcio²,

Liseno³

et al. 2016

PIER

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Abstract-We deal with one of the computationally most critical steps of the Phase-Only synthesis of aperiodic reflectarrays, namely the fast evaluation of the radiation operator. We present an approach exploiting the use of a fast numerical algorithm using 2D Non-Uniform FFTs (NUFFTs) of NED (NonEquispaced Data) and NER (Non-Equispaced Results) type and of parallel processing on Graphics Processing Units (GPUs). We extend the approach in K. Fourmont, J. Fourier Anal. Appl., Vol. 9, No. 5, 431-540, 2013 for implementing NUFFT routines to the 2D case and illustrate the parallel strategies to accelerate the approach. In particular, we show how the two levels of parallelism intrinsic in the interpolation step of the 2D NED-NUFFT can be fruitfully exploited by adopting dynamic parallelism, a feature made available in one of the latest architecture of NVIDIA cards. The presented synthesis results show that the introduction of further degrees of freedom (positions) allows improving the performance with respect to periodic reflectarrays. Also, the possibility of adopting aperiodic reflectarrays of reduced number of elements for fixed performance is demonstrated.

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“…In [8], FDTD (Finite Different Time Domain) and its optimization technique on GPU are reported. An adapting MoM (Method of Moment) with RWG basis functions on GPU is detailedly considered in [9]. In [10], fast multipole method on GPU is analyzed.…”

Section: Introductionmentioning

confidence: 99%

Parallel implementation of physical optics by using GPU with CUDA

Pang

Dong

2013

IET International Radar Conference 2013

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A parallel implementation of physical optics (PO) is presented on the graphic card NVIDIA GTX480. Taking the advantage of the characteristic of visible surface detection in PO, an improved Z-buffer detection algorithm for triangle meshes is developed, which can significantly decrease the amount of float point computation. By using reduction operation, we design a fast parallel summing method for the physical optics integrals over illuminated triangles. The numerical examples show that the PO algorithm proposed in this paper has high precision, and the efficiency is much higher (more than an order of magnitude) in comparison with the serial computing program. So it can serve as a good support for radar target characteristics simulation computation and scattering characteristics analysis of complicated target.

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Using GPU With CUDA to Accelerate MoM-Based Electromagnetic Simulation of Wire-Grid Models

Cited by 39 publications

References 8 publications

An Efficient Framework for Analysis of Wire-Grid Shielding Structures over a Broad Frequency Range

An Efficient Framework for Analysis of Wire-Grid Shielding Structures over a Broad Frequency Range

Fast, Phase-Only Synthesis of Aperiodic Reflectarrays Using Nuffts and Cuda

Parallel implementation of physical optics by using GPU with CUDA

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