Scientific Programming

HPC Software and Programming Environments for Big Data Applications


Status
Published

Lead Editor

1Sogang University, Seoul, Republic of Korea

2Oak Ridge National Laboratory, Oak Ridge, USA

3Peking University, Beijing, China

4Beijing University of Posts and Telecommunications, Beijing, China


HPC Software and Programming Environments for Big Data Applications

Description

Latest survey and studies identified that 90% of today’s data is just generated in the past two years. In reality, data being produced today is quite large in scale, that is, Petabytes. With the data generated at high speed, the complexity of scientific and engineering problems has increased significantly. Traditional HPC system has begun to provide a big data processing infrastructure for high performance big data processing. In particular, the HPC software and programming environment provides a rich computing framework for previously unresolved big data problems. However, the existing HPC system software and programming models were not designed and developed for big data applications and were difficult to use. Therefore, this special issue focuses on how the HPC software and programming environment should be developed for high performance big data processing.

Potential topics include but are not limited to the following:

  • HPC software and programming model for big data
  • Algorithms and programming techniques for big data
  • Storage, sharing, and transfer challenges for big data
  • Networking challenges for big data
  • Clustering and classification of big data with HPC
  • Big data modeling and simulation for HPC systems
  • Reliable parallel and distributed algorithms for big data with HPC
  • High performance scientific and graph databases for big data
  • Big data visualization with HPC

Articles

  • Special Issue
  • - Volume 2018
  • - Article ID 6015685
  • - Editorial

HPC Software and Programming Environments for Big Data Applications

Youngjae Kim | Sungyong Park | ... | Shangguang Wang
  • Special Issue
  • - Volume 2018
  • - Article ID 6860359
  • - Research Article

Resource Scheduling Based on Improved Spectral Clustering Algorithm in Edge Computing

Guangshun Li | Shuzhen Xu | ... | Heng Ding
  • Special Issue
  • - Volume 2018
  • - Article ID 7306837
  • - Research Article

SEDC-Based Hardware-Level Fault Tolerance and Fault Secure Checker Design for Big Data and Cloud Computing

Zahid Ali Siddiqui | Jeong-A Lee | Unsang Park
  • Special Issue
  • - Volume 2018
  • - Article ID 3287065
  • - Research Article

Research on the Prewarning Method for the Safety of South-to-North Water Transfer Project Driven by Monitoring Data

Yang Liu | Yaoling Fan | ... | Bin Yang
  • Special Issue
  • - Volume 2018
  • - Article ID 5418679
  • - Review Article

Big Data in Cloud Computing: A Resource Management Perspective

Saeed Ullah | M. Daud Awan | M. Sikander Hayat Khiyal
  • Special Issue
  • - Volume 2018
  • - Article ID 4120561
  • - Research Article

NUMA-Aware Thread Scheduling for Big Data Transfers over Terabits Network Infrastructure

Taeuk Kim | Awais Khan | ... | Scott Atchley
  • Special Issue
  • - Volume 2018
  • - Article ID 3907513
  • - Research Article

Deployment Strategy for Car-Sharing Depots by Clustering Urban Traffic Big Data Based on Affinity Propagation

Zhihan Liu | Yi Jia | Xiaolu Zhu
  • Special Issue
  • - Volume 2018
  • - Article ID 7548527
  • - Research Article

Mitigating Interference between Scientific Applications in OS-Level Virtualized Environments

Theodora Adufu | Yoonhee Kim
  • Special Issue
  • - Volume 2018
  • - Article ID 2181974
  • - Research Article

Cultural Distance-Aware Service Recommendation Approach in Mobile Edge Computing

Yan Li | Yan Guo
  • Special Issue
  • - Volume 2018
  • - Article ID 4230185
  • - Research Article

Nonmetric Correction of Lens Distortion Based on Entropy Measure

Tianfei Chen | Lijun Sun | ... | Defeng Wu
Scientific Programming
 Journal metrics
Acceptance rate27%
Submission to final decision66 days
Acceptance to publication33 days
CiteScore2.300
Impact Factor0.963
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