With the increase in data-driven analytics, the demand for high performing computing resources has risen. There are many high-performance computing centers providing cyberinfrastructure (CI) for academic research. However, there exists access barriers in bringing these resources to a broad range of users. Users who are new to data analytics field are not yet equipped to take advantage of the tools offered by CI. In this paper, we propose a framework to lower the access barriers that exist in bringing the high-performance computing resources to users that do not have the training to utilize the capability of CI. The framework uses divide-and-conquer (DC) paradigm for data-intensive computing tasks. It consists of three major components - user interface (UI), parallel scripts generator (PSG) and underlying cyberinfrastructure (CI). The goal of the framework is to provide a user-friendly method for parallelizing data-intensive computing tasks with minimal user intervention. Some of the key design goals are usability, scalability and reproducibility. The users can focus on their problem and leave the parallelization details to the framework.
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This content will become publicly available on July 17, 2025
COMPLECS: COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure
The needs of cyberinfrastructure (CI) Users are different from those of CI Contributors. Typically, much of the training in advanced CI addresses developer topics such as MPI, OpenMP, CUDA and application profiling, leaving a gap in training for these users. To remedy this situation, we developed a new program: COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure (COMPLECS). COMPLECS focuses exclusively on helping CI Users acquire the skills and knowledge they need to efficiently accomplish their compute- and data-intensive research, covering topics such as parallel computing concepts, data management, batch computing, cybersecurity, HPC hardware overview, and high throughput computing.
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- Award ID(s):
- 2320934
- NSF-PAR ID:
- 10533766
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400704192
- Page Range / eLocation ID:
- 1 to 4
- Subject(s) / Keyword(s):
- Computing education workforce development advanced cyberinfrastructure
- Format(s):
- Medium: X
- Location:
- Providence RI USA
- Sponsoring Org:
- National Science Foundation
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