Runtime prediction of parallel applications with workload-aware clustering
Traditionally, many science fields require great support for a massive workflow, which utilizes multiple cores simultaneously. In order to support such large-scale scientific workflows, high-capacity parallel systems such as supercomputers are widely ...
Prioritizing the solution of cloud service selection using integrated MCDM methods under Fuzzy environment
Cloud service selection plays a crucial role in terms of on-demand service selection on a subscription basis. As a result of wide-range availability of cloud services with similar functionalities, it is very crucial to determine which service best ...
CCFinder: using Spark to find clustering coefficient in big graphs
Networks with billions of vertices introduce new challenges to perform graph analysis in a reasonable time. Clustering coefficient is an important analytical measure of networks such as social networks and biological networks. To compute clustering ...
Reconstructing permutation table to improve the Tabu Search for the PFSP on GPU
General-purpose computing on graphics processing unit (GPGPU) has been adopted to accelerate the running of applications which require long execution time in various problem domains. Tabu Search belonging to meta-heuristics optimization has been used to ...
Soft error resilience of Big Data kernels through algorithmic approaches
As the volume of data generated each day continues to increase, more and more interest is put into Big Data algorithms and the insight they provide.? Since these analyses require a substantial amount of resources, including physical machines, power, and ...
Unsupervised text feature selection technique based on hybrid particle swarm optimization algorithm with genetic operators for the text clustering
The text clustering technique is an appropriate method used to partition a huge amount of text documents into groups. The documents size affects the text clustering by decreasing its performance. Subsequently, text documents contain sparse and ...
A multi-parameter scheduling method of dynamic workloads for big data calculation in cloud computing
Workload scheduling in cloud computing is currently an active research field. Scheduling plays an important role in cloud computing performance, especially when the platform is used for big data analysis and as less predictable workloads dynamically ...
A fast Hough Transform algorithm for straight lines detection in an image using GPU parallel computing with CUDA-C
The Hough Transform (HT) is a digital image processing method for the detection of shapes which has multiple uses today. A disadvantage of this method is its sequential computational complexity, particularly when a single processor is used. An optimized ...
Novel parity-preserving reversible logic array multipliers
Reversible logic as a new promising design domain can be used for DNA computations, nanocomputing, and especially constructing quantum computers. However, the vulnerability to different external effects may lead to deviation from producing correct ...
An online valuation-based sealed winner-bid auction game for resource allocation and pricing in clouds
Cloud computing is able to allocate different resources as virtual machines (VMs) to users, who need only pay for the amount of resources used. Two of the challenges in clouds are resource allocation and pricing in such a way to satisfy both cloud ...
Real-time workflows oriented online scheduling in uncertain cloud environment
Workflow scheduling has become one of the hottest topics in cloud environments, and efficient scheduling approaches show promising ways to maximize the profit of cloud providers via minimizing their cost, while guaranteeing the QoS for users' ...
Security analysis of a publicly verifiable data possession scheme for remote storage
As an essential technology of cloud computing, the cloud storage can exactly satisfy the demand of users with the service of scalability, ubiquitous access and low maintenance cost. However, moving data to the cloud servers will bring some significant ...
A parallel multigrid solver for incompressible flows on computing architectures with accelerators
An efficient parallel multigrid pressure correction algorithm is proposed for the solution of the incompressible Navier---Stokes equations on computing architectures with acceleration devices. The pressure correction procedure is based on the numerical ...
Barrier coverage of WSNs with the imperialist competitive algorithm
Barrier coverage in wireless sensor networks has been used in many applications such as intrusion detection and border surveillance. Barrier coverage is used to monitor the network borders to prevent intruders from penetrating the network. In these ...
Improvement of workload balancing using parallel loop self-scheduling on Intel Xeon Phi
In recent years, Intel promotes its new product Xeon Phi coprocessor, which is similar to the x86 architecture coprocessor. It has about 60 cores and can be regarded as a single computing node, with the computing power that cannot be ignored. This work ...
Memory allocation algorithm for cloud services
Memory allocation has a major influence on multiuser systems, cloud-based services, virtual machines, and other computer systems. Memory allocation is a process that assigns physical or virtual memory space to programs and services as efficiently and ...
The cost-effective fault detection and fault location approach for communication channels in NoC
In the current paper, we propose a new online search, fault detection, and fault location approach for short faults in network on chip communication channels. The approach proposed consists of a built-in self-test as well as a packet/flit comparings ...
Efficient exploitation of the Xeon Phi architecture for the Ant Colony Optimization (ACO) metaheuristic
In recent years, the use of compute-intensive coprocessors has been widely studied in the field of Parallel Computing to accelerate sequential processes through a Graphic Processing Unit (GPU). Intel has recently released a GPU-type coprocessor, the ...
Exploring correlation for fast skyline computation
Scaling skyline queries over high-dimensional datasets remains to be challenging due to the fact that most existing algorithms assume dimensional independence when establishing the worst-case complexity by discarding correlation distribution. In this ...