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The connection and eventual integration of High-Performance Computing (HPC) with Quantum Computing (QC) represents a transformative advancement in computational technology, promising significant enhancements in solving complex, previously…

This paper presents a comprehensive software stack architecture for integrating quantum computing (QC) capabilities with High-Performance Computing (HPC) environments. While quantum computers show promise as specialized accelerators for…

Increasing data volumes in scientific experiments necessitate the use of high-performance computing (HPC) resources for data analysis. In many scientific fields, the data generated from scientific instruments and supercomputer simulations…

分布式、并行与集群计算 · 计算机科学 2021-03-25 Sam Nickolay , Eun-Sung Jung , Rajkumar Kettimuthu , Ian Foster

Containers offer an array of advantages that benefit research reproducibility and portability across groups and systems. As container tools mature, container security improves, and High-performance computing (HPC) and cloud system tools…

分布式、并行与集群计算 · 计算机科学 2023-08-24 Tiziano Müller , Nina Mujkanovic , Juan J. Durillo , Nicolay Hammer

MapReduce, the popular programming paradigm for large-scale data processing, has traditionally been deployed over tightly-coupled clusters where the data is already locally available. The assumption that the data and compute resources are…

分布式、并行与集群计算 · 计算机科学 2012-07-31 Benjamin Heintz , Abhishek Chandra , Ramesh K. Sitaraman

Scientific discovery increasingly depends on middleware that enables the execution of heterogeneous workflows on heterogeneous platforms One of the main challenges is to design software components that integrate within the existing…

分布式、并行与集群计算 · 计算机科学 2024-07-17 Aymen Alsaadi , Shantenu Jha , Matteo Turilli

Hybrid workflows combining traditional HPC and novel ML methodologies are transforming scientific computing. This paper presents the architecture and implementation of a scalable runtime system that extends RADICAL-Pilot with service-based…

分布式、并行与集群计算 · 计算机科学 2025-03-18 Andre Merzky , Mikhail Titov , Matteo Turilli , Ozgur Kilic , Tianle Wang , Shantenu Jha

Hadoop is a popular MapReduce framework for developing parallel applications in distributed environments. Several advantages of MapReduce such as programming ease and ability to use commodity hardware make the applicability of soft…

分布式、并行与集群计算 · 计算机科学 2018-02-13 Güngör Yildirim , İbrahim R Hallac , Galip Aydin , Yetkin Tatar

Many important computational problems require utilization of high performance computing (HPC) systems that consist of multi-level structures combining higher and higher numbers of devices with various characteristics. Utilizing full power…

分布式、并行与集群计算 · 计算机科学 2018-09-21 Paweł Rościszewski

The convergence of IoT, Edge, Cloud, and HPC technologies creates a compute continuum that merges cloud scalability and flexibility with HPC's computational power and specialized optimizations. However, integrating cloud and HPC resources…

分布式、并行与集群计算 · 计算机科学 2025-05-20 Aasish Kumar Sharma , Christian Boehme , Patrick Gelß , Ramin Yahyapour , Julian Kunkel

Hardware support for high-performance computing (HPC) has so far been subject to significant advances. The pervasiveness of HPC systems, mainly made up with parallel computing units, makes it crucial to spread and vivify effective HPC…

分布式、并行与集群计算 · 计算机科学 2018-02-06 Claude Tadonki

In this paper, a technology for massive data storage and computing named Hadoop is surveyed. Hadoop consists of heterogeneous computing devices like regular PCs abstracting away the details of parallel processing and developers can just…

网络与互联网体系结构 · 计算机科学 2022-03-01 Ameneh Zarei , Shahla Safari , Mahmood Ahmadi , Farhad Mardukhi

The evolving landscape of scientific computing requires seamless transitions from experimental to production HPC environments for interactive workflows. This paper presents a structured transition pathway developed at OLCF that bridges the…

The integration of quantum computers within classical High-Performance Computing (HPC) infrastructures is receiving increasing attention, with the former expected to serve as accelerators for specific computational tasks. However, combining…

Distributed data processing platforms for cloud computing are important tools for large-scale data analytics. Apache Hadoop MapReduce has become the de facto standard in this space, though its programming interface is relatively low-level,…

分布式、并行与集群计算 · 计算机科学 2018-03-30 Bilal Akil , Ying Zhou , Uwe Röhm

Analyzing and working with big data could be very diffi cult using classical means like relational database management systems or desktop software packages for statistics and visualization. Instead, big data requires large clusters with…

分布式、并行与集群计算 · 计算机科学 2018-02-09 Bogdan Oancea , Raluca Mariana Dragoescu

AI integration is revolutionizing the landscape of HPC simulations, enhancing the importance, use, and performance of AI-driven HPC workflows. This paper surveys the diverse and rapidly evolving field of AI-driven HPC and provides a common…

分布式、并行与集群计算 · 计算机科学 2025-06-26 Wes Brewer , Ana Gainaru , Frédéric Suter , Feiyi Wang , Murali Emani , Shantenu Jha

Scientific applications in HPC environment are more com-plex and more data-intensive nowadays. Scientists usually rely on workflow system to manage the complexity: simply define multiple processing steps into a single script and let the…

分布式、并行与集群计算 · 计算机科学 2018-05-17 Dong Dai , Robert Ross , Dounia Khaldi , Yonghong Yan , Matthieu Dorier , Neda Tavakoli , Yong Chen

The advent of experimental science facilities-instruments and observatories, such as the Large Hadron Collider, the Laser Interferometer Gravitational Wave Observatory, and the upcoming Large Synoptic Survey Telescope-has brought about…

分布式、并行与集群计算 · 计算机科学 2019-02-12 E. A. Huerta , Roland Haas , Shantenu Jha , Mark Neubauer , Daniel S. Katz

Output-intensive scientific applications are highly sensitive to low storage throughput. While existing scientific application stacks are optimized for traditional High-Performance Computing (HPC) environments with high remote storage and…

分布式、并行与集群计算 · 计算机科学 2025-10-22 Steven W. D. Chien , Kento Sato , Artur Podobas , Niclas Jansson , Stefano Markidis , Michio Honda