In real applications, massive data with graph structures are often incomplete due to various restrictions. Therefore, imputation algorithms have been widely used in the fields of social networks, sensor and MRI solve completion problem. To keep relevant, a structure is represented by graph-tensor, which each matrix vertex value weighted graph. The convolutional algorithm has proposed low-rank g...

We implement Monte Carlo algorithms for the simulation of spin-glass systems and optimize our codes for recent multi-core CPU and GPU architectures. We consider both the Ising (binary) and Heisenberg (floating-point) spin-glass models. We provide performance figures for the Intel Nehalem and the IBM Cell/BE CPUs and the Nvidia Tesla C1060 GPU; we also draw a comparison with the performance of d...

This paper presents CUDA-based parallelization of implicit incompressible SPH (IISPH) on the GPU. Along with the detailed exposition of our implementation, we analyze various components involved for their costs. We show that our CUDA version achieves near linear scaling with the number of particles and is faster than the multi-core parallelized IISPH on the CPU. We also present a basic comparis...

The k nearest neighbor (kNN) search is a computationally intensive application critical to fields such as image processing, statistics, and biology. Recent works have demonstrated the efficacy of k-d tree based implementations on multi-core CPUs. It is unclear, however, whether such tree based implementations are amenable for execution in high-density processors typified today by the graphics p...

GRAPES (Global and Regional Assimilation and Prediction System) is a new generation of numerical weather prediction (NWP) system of China. As the system processes amount of data and requires high real-time,so it is always a hot research field of parallel computing.This is the first time that we use GPU (Graphics Processor Unit) general-purpose computing and CUDA technology on RRTM (Rapid Radiat...

Spatial operations such as spatial join combine two objects on spatial predicates. It is different from relational join because objects have multi dimensions and spatial join consumes large execution time. Recently, many researches tried to find methods to improve the execution time. Parallel spatial join is one method to improve the execution time. Comparison between objects can be done in par...

v 1 Background and Motivation 1 1.1 Benchmarks 3 1.2 Breadth-First Search Framework 4 1.3 Approach 7 2 Implementations 8 2.1 Single CPU, List 8 2.1.1 Kernel 1 8 2.1.2 Kernel 2 10 2.2 Single CPU, Compressed Sparse Row 10 2.2.1 Kernel 1 10 2.2.2 Kernel 2 12 2.3 Single GPU, CSR 13 2.3.1 Kernel 1 13 2.3.2 Kernel 2 14 2.4 Single GPU, Out-of-Core CSR 15 2.4.1 Kernel 1 15 2.4.2 Kernel 2 17 2.5 Multi-C...

Modified Moving Particle Semi-implicit (MMPS) is a particle-based method used to simulate pore-scale fluid flow through disordered porous media. We present a multi-GPU implementation of MMPS for hybrid CPU–GPU clusters using NVIDIA’s Compute Unified Device Architecture (CUDA). Message Passing Interface (MPI) functions are used to communicate between different nodes of the cluster and hence thei...