FINITE ELEMENT MATRIX GENERATION ON A GPU
نویسندگان
چکیده
منابع مشابه
Finite Element Matrix Generation on a Gpu
This paper presents an efficient technique for fast generation of sparse systems of linear equations arising in computational electromagnetics in a finite element method using higher order elements. The proposed approach employs a graphics processing unit (GPU) for both numerical integration and matrix assembly. The performance results obtained on a test platform consisting of a Fermi GPU (1x T...
متن کاملGlobal finite element matrix construction based on a CPU-GPU implementation
The finite element method (FEM) has several computational steps to numerically solve a particular problem, to which many efforts have been directed to accelerate the solution stage of the linear system of equations. However, the finite element matrix construction, which is also time-consuming for unstructured meshes, has been less investigated. The generation of the global finite element matrix...
متن کاملFast System Matrix Generation on a GPU Cluster
This paper presents an algorithm for Positron Emission Tomography reconstruction running on a GPU cluster. The most computation intensive part of the reconstruction process, the forward projection, is re-interpreted as a geometric problem, that can efficiently be solved by the graphics hardware. We also investigate the possibilities to further increase the speed and to sidestep the texture memo...
متن کاملA New Sparse Matrix Vector Multiplication GPU Algorithm Designed for Finite Element Problems
Recently, graphics processors (GPUs) have been increasingly leveraged in a variety of scientific computing applications. However, architectural differences between CPUs and GPUs necessitate the development of algorithms that take advantage of GPU hardware. As sparse matrix vector multiplication (SPMV) operations are commonly used in finite element analysis, a new SPMV algorithm and several vari...
متن کاملFinite Element Integration with Quadrature on the GPU
We present a novel, quadrature-based finite element integration method for low-order elements on GPUs, using a pattern we call thread transposition to avoid reductions while vectorizing aggressively. On the NVIDIA GTX580, which has a nominal single precision peak flop rate of 1.5 TF/s and a memory bandwidth of 192 GB/s, we achieve close to 300 GF/s for element integration on first-order discret...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Progress In Electromagnetics Research
سال: 2012
ISSN: 1559-8985
DOI: 10.2528/pier12040301