high performance computing on graphics processing units: hgpu.org

The main purpose of this work is to show the clear advantages of using modern parallel tools in solving the SLAE. The BiCGStab method was used for solving system of the linear equations. This paper contains some details about this method. To accelerate computations on the GPU several technologies (such as CUBLAS, OpenACC) were used. […]

Many of the heterogeneous resources available to modern computers are designed for different workloads. In order to efficiently use GPU resources, the workload must have a greater degree of parallelism than a workload designed for multicore-CPUs. And conceptually, the Intel Xeon Phi coprocessors are capable of handling workloads somewhere in between the two. This multitude […]

Publication All papers, both invited and contributed, will be reviewed by two or three experts from the PC. After a careful reviewing process, all accepted paper will be publishedin WIT Transactions on Information and Communication Technologies (ISSN: 1743-3517), which will be indexed by EI Compendex, Scopus and ISI. Topics: The topics of ICOCE2014 are included […]

The exponential growth in user and application data entails new means for providing fault tolerance and protection against data loss. High Performance Computing (HPC) storage systems, which are at the forefront of handling the data deluge, typically employ hardware RAID at the backend. However, such solutions are costly, do not ensure end-to-end data integrity, and […]

In recent years Graphics Processing Unit (GPU) has evolved as a high performance data processing technology allowing users to compute large blocks of parallel data using an array of low complexity processors. This paper proposes the implementation of compute intensive portions of 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE) physical layer using GPU. […]

The next-generation sequencing technologies are pouring big data and pushing the frontier of life sciences toward new territories that were never imagined before. However, such big data impose great computational challenges to statistical analysis of these data. It is important to utilize Graphics Processing Unit (GPU)’s large throughput and massive parallelism to process large data […]

Data mining tools may be computationally demanding, so there is an increasing interest on parallel computing strategies to improve their performance. The popularization of Graphics Processing Units (GPUs) increased the computing power of current desktop computers, but desktop-based data mining tools do not usually take full advantage of these architectures. This paper exploits an approach […]

Computation outsourcing is an increasingly successful paradigm today. Private and public organizations, as well as common users, can access a large number of economically viable resources to perform the desired computations or access data. The cloud approach allows outsourcers to offer on-demand scalable services to third parties or to perform large computations without high server […]

Publication: All papers, both invited and contributed, will be reviewed by two or three experts from the PC. After a careful reviewing process, all accepted paper will be publishedin WIT Transactions on Information and Communication Technologies (ISSN: 1743-3517), which will be indexed by EI Compendex, Scopus and ISI. Topics (not limited to): ■ Modern and […]

With Extensive use of wireless sensor network is drawing increasing attention to the research on data-driven processing but it is a challenge to construct a system of concurrent processing for large-scale data streams (LCDS), a typical model of data-driven process. As Graphic Processing Unit (GPU) has good characteristics of SPMD (Single Program Multiple Data) while […]

Small-scale computations usually cannot fully utilize the compute capabilities of modern GPGPUs. With the Fermi GPU architecture Nvidia introduced the concurrent kernel execution feature allowing up to 16 GPU kernels to execute simultaneously on a shared GPU device for a better utilization of the respective resources. Insufficient scheduling capabilities in this respect, however, can significantly […]

Currently, state of the art libraries, like MAGMA, focus on very large linear algebra problems, while solving many small independent problems, which is usually referred to as batched problems, is not given adequate attention. In this paper, we proposed a batched Cholesky factorization on a GPU. Three algorithms – nonblocked, blocked, and recursive blocked – […]