Search · four archives
Search · four archives
20 papers · ranked by Valyu relevance
Łukasz Świerczewski
—Paper describes the theoretical and practical aspects of the proposed model that uses distributed computing to a global network of Internet communication. Distributed computing are widely used in modern solutions such as research, where the requirement is very high processing power, which can not be placed in one…
Aneesh Khole, Atharva Thakar, Avadhoot Kulkarni, Hrithik Jadhav + 2 more
'Shreyas Shende' 'Varad Karajkhede'] Abstract— Computer systems have evolved over the years starting from sizable, single-user, slow, and expensive machines to multi-user, fast, cheaper, and small-sized machines. The use of multi-user computer networks has given rise to a new paradigm of computing known as Distributed…
Brijender Kahanwal, T. P. Singh
The distributed computing is done on many systems to solve a large scale problem. The growing of high-speed broadband networks in developed and developing countries, the continual increase in computing power, and the rapid growth of the Internet have changed the way. In it the society manages information and…
Sachin Lakra, Deepak Kumar Sharma
Distributed Software Development today is in its childhood and not too widespread as a method of developing software in the global IT Industry. In this context, Petrinets are a mathematical model for describing distributed systems theoretically, whereas AttNets are one of their offshoots. But development of true…
Tsolak Ghukasyan, Vahagn Altunyan, Aram Bughdaryan, Tigran Aghajanyan + 3 more
This paper presents the Smart Distributed Data Factory (SDDF), an AI-driven distributed computing platform designed to address challenges in drug discovery by creating comprehensive datasets of molecular conformations and their properties. SDDF uses volunteer computing, leveraging the processing power of personal…
Martin Werner
This paper provides an abstract analysis of parallel processing strategies for spatial and spatio-temporal data. It isolates aspects such as data locality and computational locality as well as redundancy and locally sequential access as central elements of parallel algorithm design for spatial data. Furthermore, the…
Geunsik Lim, Minho Lee, R.J.W.E. Lahaye, Young Ik Eom
— Idle times of personal computers have increased steadily due to the generalization of computer usage and cloud computing. Clustering research aims at utilizing idle computer resources for processing a variable work-load on a large number of computers. The work-load is processed continually despite of the volatile…
Tiffany Leung, Alissa Brauneck, Predrag Mitrovic, Aiguo Wang + 41 more
Background Machine learning and artificial intelligence have shown promising results in many areas and are driven by the increasing amount of available data. However, these data are often distributed across different institutions and cannot be easily shared owing to strict privacy regulations. Federated learning (FL)…
Shantenu Jha, Daniel S. Katz, André Luckow, Omer Rana + 2 more
'Yogesh Simmhan' 'Neil Chue Hong'] A common feature across many science and engineering applications is the amount and diversity of data and computation that must be integrated to yield insights. Data sets are growing larger and becoming distributed; and their location, availability and properties are often…
Cláudia Brito, Pedro Ferreira, João Paulo
Breakthroughs in sequencing technologies led to an exponential growth of genomic data, providing unprecedented biological in-sights and new therapeutic applications. However, analyzing such large amounts of sensitive data raises key concerns regarding data privacy, specifically when the information is outsourced to…
Maxim Lippeveld, Daniel Peralta, Andrew Filby, Yvan Saeys
Due to high resolution and throughput of modern image cytometry platforms, morphologically profiling generated datasets poses a significant computational challenge. Here, we present Scalable Cytometry Image Processing (SCIP), an image processing software aimed at running on distributed high performance computing…
Yizi Shang, Ling Shang, Chuanchang Gao, Guiming Lu + 2 more
'Dongdong Jia'] This paper is to make further research on facilitating the large-scale scientific computing on the grid and the desktop grid platform. The related issues include the programming method, the overhead of the high-level program interface based middleware, and the data anticipate migration. The block based…
Jacob M. Luber, Braden T. Tierney, Evan M. Cofer, Chirag J. Patel + 1 more
Across biology we are seeing rapid developments in scale of data production without a corresponding increase in data analysis capabilities. Here, we present Aether (http://aether.kosticlab.org), an intuitive, easy-to-use, cost-effective, and scalable framework that uses linear programming (LP) to optimally bid on and…
Pau Andrio, Adam Hospital, Cristian Ramon-Cortes, Javier Conejero + 4 more
The usage of workflows has led to progress in many fields of science, where the need to process large amounts of data is coupled with difficulty in accessing and efficiently using High Performance Computing platforms. On the one hand, scientists are focused on their problem and concerned with how to process their data.…
Jamie Alnasir, Hugh P. Shanahan
The paper reviews the use of the Hadoop platform in Structural Bioinformatics applications. Specifically, we review a number of implementations using Hadoop of high-throughput analyses, e.g. ligand-protein docking and structural alignment, and their scalability in comparison with other batch schedulers and MPI. We find…
Authors not listed
Machine learning models are transforming data-driven research across scientific disciplines, yet their deployment as accessible and reliable web services remains a significant challenge. We introduce the NERDD framework, a scalable, maintainable, and secure microservices platform designed to support the sustainable…
António Luís Lopes, Luís Miguel Botelho, Olaf Sporns
In this paper, we describe a distributed coordination system that allows agents to seamlessly cooperate in problem solving by partially contributing to a problem solution and delegating the subproblems for which they do not have the required skills or knowledge to appropriate agents. The coordination mechanism relies…
Noa Zilberman, Andrew W. Moore, Jon A. Crowcroft
Computer architectures have entered a watershed as the quantity of network data generated by user applications exceeds the data-processing capacity of any individual computer end-system. It will become impossible to scale existing computer systems while a gap grows between the quantity of networked data and the…
Authors not listed
Computing electrostatic interactions remains the bottleneck of molecular dynamics (MD) simulations despite more than a century of effort in developing methods to accelerate the calculation. Previously we have developed the Spherical Grid and Treecode (SGT) and Gauss-Legendre-Spherical-t (GLST) algorithms for…
Klaithem Al Nuaimi, Nader Mohamed, Mariam Al Nuaimi, Jameela Al-Jaroodi
'Jameela Al-Jaroodi'] We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files…