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Grid is an infrastructure that involves the integrated and collaborative use of computers, networks, databases and scientific instruments owned and managed by multiple organizations. Grid applications often involve large amounts of data…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Parvin Asadzadeh , Rajkumar Buyya , Chun Ling Kei , Deepa Nayar , Srikumar Venugopal

Programming a distributed system, such as a cluster, requires extended use of low-level communication libraries and can often become cumbersome and error prone for the average developer. In this work, we consider each node of a cluster as a…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-05-24 Ilias Keftakis , Vassilios V. Dimakopoulos

PaPy, which stands for parallel pipelines in Python, is a highly flexible framework that enables the construction of robust, scalable workflows for either generating or processing voluminous datasets. A workflow is created from user-written…

Programming Languages · Computer Science 2014-07-17 Marcin Cieslik , Cameron Mura

UCX is a communication framework that enables low-latency, high-bandwidth communication in HPC systems. With its unified API, UCX facilitates efficient data transfers across multi-node CPU-GPU clusters. UCX is widely used as the transport…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-02-24 Emir Gencer , Mohammad Kefah Taha Issa , Ilyas Turimbetov , James D. Trotter , Didem Unat

One critical value microgrids bring to power systems is resilience, the capability of being able to island from the main grid under certain conditions and connect back when necessary. Once islanded, a microgrid must be synchronized to the…

Systems and Control · Computer Science 2017-06-20 Di Shi , Xi Chen , Zhiwei Wang , Xiaohu Zhang , Zhe Yu , Xinan Wang , Desong Bian

Computational Grids, coupling geographically distributed resources such as PCs, workstations, clusters, and scientific instruments, have emerged as a next generation computing platform for solving large-scale problems in science,…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 David Abramson , Rajkumar Buyya , Jonathan Giddy

We describe a family of MPI applications we call the Parallel Unix Commands. These commands are natural parallel versions of common Unix user commands such as ls, ps, and find, together with a few similar commands particular to the parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 E. Ong , E. Lusk , W. Gropp

The implicit 2D3V particle-in-cell (PIC) code developed to study the interaction of ultrashort pulse lasers with matter [G. M. Petrov and J. Davis, Computer Phys. Comm. 179, 868 (2008); Phys. Plasmas 18, 073102 (2011)] has been parallelized…

Plasma Physics · Physics 2016-08-24 George M. Petrov , Jack Davis

We present a single-node, multi-GPU programmable graph processing library that allows programmers to easily extend single-GPU graph algorithms to achieve scalable performance on large graphs with billions of edges. Directly using the…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-03-02 Yuechao Pan , Yangzihao Wang , Yuduo Wu , Carl Yang , John D. Owens

This paper presents a comprehensive comparison of three dominant parallel programming models in High Performance Computing (HPC): Message Passing Interface (MPI), Open Multi-Processing (OpenMP), and Compute Unified Device Architecture…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-06-19 Nizar ALHafez , Ahmad Kurdi

The Message-Passing Interface (MPI) and C++ form the backbone of high-performance computing, but MPI only provides C and Fortran bindings. While this offers great language interoperability, high-level programming languages like C++ make…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-11-13 Tim Niklas Uhl , Matthias Schimek , Lukas Hübner , Demian Hespe , Florian Kurpicz , Christoph Stelz , Peter Sanders

Deployment of distributed applications on large systems, and especially on grid infrastructures, becomes a more and more complex task. Grid users spend a lot of time to prepare, install and configure middleware and application binaries on…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-06-21 Areski Flissi , Philippe Merle

Modern heterogeneous supercomputing systems are comprised of compute blades that offer CPUs and GPUs. On such systems, it is essential to move data efficiently between these different compute engines across a high-speed network. While…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-08-10 Naveen Namashivayam , Krishna Kandalla , Trey White , Nick Radcliffe , Larry Kaplan , Mark Pagel

We present advances in the software engineering design and implementation of the multi-tier run-time system for the General Intensional Programming System (GIPSY) by further unifying the distributed technologies used to implement the Demand…

Software Engineering · Computer Science 2010-07-09 Bin Han , Serguei A. Mokhov , Joey Paquet

Asynchronous Many-Task (AMT) systems offer a potential solution for efficiently programming complicated scientific applications on extreme-scale heterogeneous architectures. However, they exhibit different communication needs from…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-18 Jiakun Yan , Hartmut Kaiser , Marc Snir

With the advent of hundreds of cores on a chip to accelerate applications, the operating system (OS) needs to exploit the existing parallelism provided by the underlying hardware resources to determine the right amount of processes to be…

Operating Systems · Computer Science 2025-01-07 Yao Xiao , Nikos Kanakaris , Anzhe Cheng , Chenzhong Yin , Nesreen K. Ahmed , Shahin Nazarian , Andrei Irimia , Paul Bogdan

We introduce Diffuse, a system that dynamically performs task and kernel fusion in distributed, task-based runtime systems. The key component of Diffuse is an intermediate representation of distributed computation that enables the necessary…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-12-17 Rohan Yadav , Shiv Sundram , Wonchan Lee , Michael Garland , Michael Bauer , Alex Aiken , Fredrik Kjolstad

We present HiCR, a model to represent the semantics of distributed heterogeneous applications and runtime systems. The model describes a minimal set of abstract operations to enable hardware topology discovery, kernel execution, memory…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-09-03 Sergio Miguel Martin , Luca Terracciano , Kiril Dichev , Noah Baumann , Jiashu Lin , Albert-Jan Yzelman

Parallel algorithms relying on synchronous parallelization libraries often experience adverse performance due to global synchronization barriers. Asynchronous many-task runtimes offer task futurization capabilities that minimize or remove…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-06-05 Alexander Strack , Christopher Taylor , Patrick Diehl , Dirk Pflüger

The rapid development in computing technology has paved the way for directive-based programming models towards a principal role in maintaining software portability of performance-critical applications. Efforts on such models involve a least…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-04-28 Kazuaki Matsumura , Simon Garcia De Gonzalo , Antonio J. Peña
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