Parallel Computing

雜志介紹

Parallel Computing雜志介紹

《Parallel Computing》是一本以English為主的未開放獲取國際優秀期刊，中文名稱并行計算，本刊主要出版、報道計算機科學-COMPUTER SCIENCE, THEORY & METHODS領域的研究動態以及在該領域取得的各方面的經驗和科研成果，介紹該領域有關本專業的最新進展，探討行業發展的思路和方法，以促進學術信息交流，提高行業發展。該刊已被國際權威數據庫SCIE收錄，為該領域相關學科的發展起到了良好的推動作用，也得到了本專業人員的廣泛認可。該刊最新影響因子為2，最新CiteScore 指數為3.5。

本刊近期中國學者發表的論文主要有：

• Online cost-rejection rate scheduling for resource requests in hybrid clouds

  Author: Yanhua Cao, Li Lu, Jiadi Yu, Shiyou Qian, Yanmin Zhu, Minglu Li

• Hybrid storage architecture and efficient MapReduce processing for unstructured data

  Author: Weiming Lu, Yaoguang Wang, Jingyuan Jiang, Jian Liu, Yapeng Shen, Baogang Wei

• ParConnect reproducibility report

  Author: Lei Yang, Yilong Li, Zhenxin Fu, Zhuohan Li, Wenbin Hou, Haoze Wu, Xiaolin Wang, Yun Liang

• A scalable interface-resolved simulation of particle-laden flow using the lattice Boltzmann method

  Author: Nicholas Geneva, Cheng Peng, Xiaoming Li, Lian-Ping Wang

英文介紹

Parallel Computing雜志英文介紹

Parallel Computing is an international journal presenting the practical use of parallel computer systems, including high performance architecture, system software, programming systems and tools, and applications. Within this context the journal covers all aspects of high-end parallel computing from single homogeneous or heterogenous computing nodes to large-scale multi-node systems.

Parallel Computing features original research work and review articles as well as novel or illustrative accounts of application experience with (and techniques for) the use of parallel computers. We also welcome studies reproducing prior publications that either confirm or disprove prior published results.

Particular technical areas of interest include, but are not limited to:

-System software for parallel computer systems including programming languages (new languages as well as compilation techniques), operating systems (including middleware), and resource management (scheduling and load-balancing).

-Enabling software including debuggers, performance tools, and system and numeric libraries.

-General hardware (architecture) concepts, new technologies enabling the realization of such new concepts, and details of commercially available systems

-Software engineering and productivity as it relates to parallel computing

-Applications (including scientific computing, deep learning, machine learning) or tool case studies demonstrating novel ways to achieve parallelism

-Performance measurement results on state-of-the-art systems

-Approaches to effectively utilize large-scale parallel computing including new algorithms or algorithm analysis with demonstrated relevance to real applications using existing or next generation parallel computer architectures.

-Parallel I/O systems both hardware and software

-Networking technology for support of high-speed computing demonstrating the impact of high-speed computation on parallel applications