Clusters of heterogeneous nodes composed of multi-core CPUs and GPUs are increasingly being used for High Performance Computing (HPC) due to the benefits in peak performance and energy efficiency. In order to fully harvest the computational capabilities of such architectures, …
May 9, 2013 by hgpu
The use of Population Balance Models (PBM) for simulating dynamics of particulate systems are inevitably limited at some point by the demands they place on computational resources. PBMs are widely used to describe the time evolutions and distributions of many …
April 26, 2013 by hgpu
Over the last decades parallel-distributed computing becomes most popular than traditional centralized computing. In distributed computing performance up-gradation is achieved by distributing workloads across the participating nodes. One of the most important factors for improving the performance of this type …
January 26, 2013 by hgpu
The main advantage of a distributed computing system over standalone computer is an ability to share the workload between cores, processors and computers. In our paper we present a hybrid cluster system – a novel computing architecture with multi-core CPUs …
October 19, 2012 by hgpu
This paper addresses issues associated with distributed computing systems and the application of mixed GPU&CPU technology to data encryption and decryption algorithms. We describe a heterogenous cluster HGCC formed by two types of nodes: Intel processor with NVIDIA graphics processing …
October 4, 2012 by hgpu
MapReduce is an efficient distributed computing model on large data sets. The data processing is fully distributed on huge amount of nodes, and a MapReduce cluster is of highly scalable. However, single-node performance is gradually to be a bottleneck in …
August 28, 2012 by hgpu
It is possible to purchase, for as little as $10,000, a cluster of computers with the capability to rival the supercomputers of only a few years ago. Now, users that have little to no experience developing distributed applications or managing …
July 16, 2012 by hgpu
This paper presents a framework that extends OpenCL by distributing computing process to many computing resources connected via network and enables the computing resources to run in parallel. Using JSON RPC (Remote Procedure Call technique relying on JavaScript Object Notation) …
July 15, 2012 by hgpu
Scheduling on heterogeneous parallel and distributed computing environment has been studied for decades. Based on different assumptions, researchers have proposed several algorithms and heuristics aiming to improve the performance of parallel applications. Most of these works focus on clusters of …
June 30, 2012 by hgpu
One of the major drawbacks of computing with graphics adapters is the limited available memory for relevant problem sizes. To overcome this limitation for the ViennaCL library, we investigate a partitioning approach for one of the standard benchmark problems in …
June 1, 2012 by hgpu
This module is largely stand-alone. It is "Part II" only in the sense that it does not contain the overview of dynamic programming seen in Part I, and does not recapitulate the introduction to CUDA. We will continue to refer …
April 10, 2012 by hgpu
Graphics processing units (GPU) had evolved from a specialized hardware capable to render high quality graphics in games to a commodity hardware for effective processing blocks of data in a parallel schema. This evolution is particularly interesting for scientific groups, …
March 23, 2012 by hgpu
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