for many years, researchers have studied high accuracy methods for recognizing the handwriting and achieved many significant improvements. however, an issue that has rarely been studied is the speed of these methods. considering the computer hardware limitations, it is necessary for these methods to run in high speed. one of the methods to increase the processing speed is to use the computer pa...

Parallel computing is a form of computation in which many calculations are carried out simultaneously, operating on the principle that large problems can often be divided into smaller ones, which are then solved concurrently .Now GPU(Graphics Processor Unit) has taken a major role in high performance computing for general purpose applications. Compute Unified Device Architecture (CUDA) programm...

In this paper, we propose an approach to obtaining enhanced performance of the Linpack benchmark on a GPU-accelerated PC cluster connected via relatively slow inter-node connections. For one node with a quad-core Intel Xeon W3520 processor and a NVIDIA Tesla C1060 GPU card, we implement a CPU–GPU parallel double-precision general matrix–matrix multiplication (dgemm) operation, and achieve a per...

Kernel density estimation (KDE) is a commonly used method for spatial point pattern analysis, but it computationally demanding when analyzing large datasets. GPU-based parallel computing has been adopted to address such computational challenges. The existing GPU-parallel KDE method, however, utilizes only one GPU computing. Additionally, assumes that the input data can be held in memory all at ...

In this report we analyze the performance of the fast Fourier transform (FFT) on graphics hardware (the GPU), comparing it to the best-of-class CPU implementation FFTW. We describe the FFT, the architecture of the GPU, and how general-purpose computation is structured on the GPU.We then identify the factors that influence FFT performance and describe several experiments that compare these facto...

Glift is an abstraction and generic template library for parallel, random-access data structures on graphics processing units (GPUs). Glift simplifies the description of new and existing GPU data structures, stimulates development of complex GPU algorithms, performs equivalently to hand-coded implementations, and introduces a parallel iteration model for GPU computation.

Deep learning frameworks optimize the computation graphs and intra-operator computations to boost inference performance on GPUs, while inter-operator parallelism is usually ignored. In this paper, a unified framework, AutoGraph, proposed obtain highly optimized in favor of parallel executions GPU kernels. A novel dynamic programming algorithm, combined with backtracking search, adopted explore ...

As the usage of GPU (Graphical Processing Unit) for non-graphical computation is rising, one important area to study how device helps improve numerical calculations. In this work, we present a time performance comparison between purely CPU (serial) and GPU-assisted (parallel) programs in computation. Specifically, design implement calculation hexadecimal -digit irrational number Pi two ways: se...

Radio propagation simulation tools are important for prediction and verification of the radio signal coverage by individual transmitters or transmitter networks such as mobile phone cellular networks. In the case of a large geographic area with a relative high resolution, the simulation can become computationally demanding, taking a considerable amount of time to accomplish. Parallel processing...