We propose the new framework of the distributed tabu search metaheuristic designed to be executed using a multi-GPU cluster, i.e. cluster of nodes equipped with GPU computing units. We propose a hybrid single-walk parallelization of the tabu search, where hybridization consists in examining a number of solutions from a neighborhood concurrently by several GPUs (multi-GPU). The methodology is de...

GPU parallelism for real applications can achieve enormous performance gain. CPU-GPU Communication is one of the major bottlenecks that limit this performance gain. Among several libraries developed so far to optimize this communication, DyManD (Dynamically Managed Data) provides better communication optimization strategies and achieves better performance on a single GPU. SmithWaterman is a wel...

The paper presents a multi-GPU implementation of the preconditioned conjugate gradient algorithm with an algebraic multigrid preconditioner (PCG-AMG) for an elliptic model problem on a 3D unstructured grid. An efficient parallel sparse matrix-vector multiplication scheme underlying the PCG-AMG algorithm is presented for the manycore GPU architecture. A performance comparison of the parallel sol...

Graph processing has always been a challenge, as there are inherent complexities in it. These include scalability to larger data sets and clusters, dependencies between vertices in the graph, irregular memory accesses during processing and traversals, minimal locality of reference, etc. In literature, there are several implementations for parallel graph processing on single GPU systems but only...

Writing and optimizing programs for high performance on systems with GPUs remains a challenging task even for expert programmers. One promising optimization technique is to evaluate parts of the program upfront on the CPU and embed the computed results in the GPU code allowing for more aggressive compiler optimizations. This technique is known as multi-stage programming and has proven to allow ...

BACKGROUND MRI physics simulators have been developed in the past for optimizing imaging protocols and for training purposes. However, these simulators have only addressed motion within a limited scope. The purpose of this study was the incorporation of realistic motion, such as cardiac motion, respiratory motion and flow, within MRI simulations in a high performance multi-GPU environment. ME...

The Frisch-Hasslacher-Pomeau (FHP) model is a lattice gas cellular automaton designed to simulate fluid flows using the exact, purely Boolean arithmetic, without any round-off error. Here we investigate the problem of its efficient porting to clusters of Fermi-class graphic processing units. To this end two multi-GPU implementations were developed and examined: one using the NVIDIA CUDA and GPU...

Previous the 3D model texture generation from multi-view images and mapping algorithms has issues in the texture chart generation which are the self-intersection and the concentration of the texture in texture space. Also we may suffer from some problems due to the occluded areas, such as inside parts of thighs. In this paper we propose a texture mapping technique for 3D models using multi-view...

We present Lux, a distributed multi-GPU system that achieves fast graph processing by exploiting the aggregate memory bandwidth of multiple GPUs and taking advantage of locality in the memory hierarchy of multi-GPU clusters. Lux provides two execution models that optimize algorithmic efficiency and enable important GPU optimizations, respectively. Lux also uses a novel dynamic load balancing st...