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The rigorous coupled-wave analysis (RCWA) technique needs to obtain the exact solution of Maxwell's equations, a huge number of matrix operations may be involved in the process. The graphics process unit (GPU) has inherent advantage in large-scale parallel computation compared with CPU. In this paper, matrix operations are put on GPU using NVIDIA's Compute Unified Device Architecture (CUDA). It is...
A comparison of PGI Open ACC, FORTRAN CUDA, and Nvidia CUDA pseudospectral methods on a single GPU and GCC FORTRAN on single and multiple CPU cores is reported. The GPU implementations use CuFFT and the CPU implementations use FFTW. Porting pre-existing FORTRAN codes to utilize a GPUs is efficient and easy to implement with Open ACC and CUDA FORTRAN. Example programs are provided.
In this paper electromagnetic transient (EMT) simulation of large scale power systems using graphics processing unit (GPU) based computing is demonstrated. As the size of power system networks increases, the simulation time using conventional central processing units (CPUs) based simulation increases drastically. This paper proposes a hybrid CPU-GPU environment for fast large scale power systems simulation...
Many geophysical problems are computationally expensive owing to their iterative nature or due to the programs processing to large datasets. Such problems are challenging and have to be approached with extreme caution because a wrong parameter selection will not only lead to wrong results but will also take up a lot of time. The Compute Unified Device Architecture (CUDA) introduced by NVIDIA has enabled...
A trend that has materialized, and has given rise to much attention, is of the increasingly heterogeneous computing platforms. Recently, it has become very common for a desktop or a notebook computer to be equipped with both a multi-core CPU and a GPU. Application development for exploiting the aggregate computing power of such an environment is a major challenge today. Particularly, we need dynamic...
Graphics Processing Units (GPUs) have enabled significant improvements in computational performance compared to traditional CPUs in several application domains. Until recently, GPUs have been programmed using C/C++ based methods such as CUDA (NVIDIA) and OpenCL (NVIDIA and AMD). Using these approaches, Fortran Numerical Weather Prediction (NWP) codes would have to be completely re-written to take...
We describe computational experiments exploring the performance improvements from overlapping computation and communication on hybrid parallel computers. Our test case is explicit time integration of linear advection with constant uniform velocity in a three-dimensional periodic domain. The test systems include a Cray XT5, a Cray XE6, and two multicore Infiniband clusters with different generations...
Due to large power grid sizes, IR-drop analysis is a computationally challenging design flow step that is commonly used in integrated circuit design. Variability in silicon and circuit operating conditions makes IR-drop analysis even more challenging. We introduce a flow to take benefit of a graphical processing unit (GPU). We introduce variability for the power grid elements through Monte Carlo runs...
The state-of-art computer architecture is based on multi core processor technology. Nowadays processors contain even more than ten cores. On the other hand new technologies have emerged that enable using GPU in general propose computing. Moreover, GPUs have become easier to program, which allows developers to effectively exploit their computational power. Currently, major chip manufacturers are developing...
The main purpose of this paper is to demonstrate how we make use of the powerful graphics processor, NVIDIA GTX280, in numerical simulation with the support of double precision floating number. Apply the finite volume method in simulating the Euler equation, two well-known examples for travelling shock waves were examined in high resolution. We had achieved at best 878 times faster than a Core 2 Duo...
Simple models of major CPU-intensive MAGIC electromagnetic (EM) plasma code portions using the CUDA language run on the graphical processing unit (GPU) indicate 12x computing rate compared to the same calculations run on the CPU only. MAGIC is being modified for performance speedup of large-scale plasma-wave EM calculations using GPU processing. Results to-date from MAGIC with the particle update...
The Variable Preconditioned GVR (VPGCR) with mixed precision on Graphics Processing Unit (GPU) using Compute Unified Device Architecture (CUDA) is numerically investigated. The convergence theorem of VPGCR is guaranteed that the residual equation for the preconditioned procedure can be solved in the range of single precision operation. The results of computations show that VPGCR with mixed precision...
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