Del Conte Alessio, Ghafouri Hamidreza, Clementel Damiano, Mičetić Ivan, Piovesan Damiano, Tosatto Silvio C E, Monzon Alexander Miguel
Department of Biomedical Sciences, University of Padova, Padova 35131, Italy.
Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR-IBIOM), Bari 70126, Italy.
Bioinform Adv. 2025 May 15;5(1):vbaf112. doi: 10.1093/bioadv/vbaf112. eCollection 2025.
The accessibility and usability of high-performance computing (HPC) resources remain significant challenges in bioinformatics, particularly for researchers lacking extensive technical expertise. While Distributed Resource Managers (DRMs) optimize resource utilization, the complexities of interfacing with these systems often hinder broader adoption. DRMAAtic addresses these challenges by integrating the Distributed Resource Management Application API (DRMAA) with a user-friendly RESTful interface, simplifying job management across diverse HPC environments. This framework empowers researchers to submit, monitor, and retrieve computational jobs securely and efficiently, without requiring deep knowledge of underlying cluster configurations.
We present DRMAAtic, a flexible and scalable tool that bridges the gap between web interfaces and HPC infrastructures. Built on the Django REST Framework, DRMAAtic supports seamless job submission and management via HTTP calls. Its modular architecture enables integration with any DRM supporting DRMAA APIs and offers robust features such as role-based access control, throttling mechanisms, and dependency management. Successful applications of DRMAAtic include the RING web server for protein structure analysis, the CAID Prediction Portal for disorder and binding predictions, and the Protein Ensemble Database deposition server. These deployments demonstrate DRMAAtic's potential to enhance computational workflows, improve resource efficiency, and facilitate open science in life sciences.
https://github.com/BioComputingUP/DRMAAtic, https://drmaatic.biocomputingup.it/.
高性能计算（HPC）资源的可访问性和可用性在生物信息学中仍然是重大挑战，特别是对于缺乏广泛技术专长的研究人员而言。虽然分布式资源管理器（DRM）可优化资源利用，但与这些系统进行交互的复杂性常常阻碍其更广泛的采用。DRMAAtic通过将分布式资源管理应用程序编程接口（DRMAA）与用户友好的RESTful接口集成，解决了这些挑战，简化了跨各种HPC环境的作业管理。该框架使研究人员能够安全、高效地提交、监控和检索计算作业，而无需深入了解底层集群配置。
我们展示了DRMAAtic，这是一个灵活且可扩展的工具，弥合了Web界面与HPC基础设施之间的差距。基于Django REST框架构建，DRMAAtic支持通过HTTP调用进行无缝作业提交和管理。其模块化架构允许与任何支持DRMAA API的DRM集成，并提供诸如基于角色的访问控制、节流机制和依赖项管理等强大功能。DRMAAtic的成功应用包括用于蛋白质结构分析的RING网络服务器、用于无序和结合预测的CAID预测门户以及蛋白质集合数据库沉积服务器。这些部署展示了DRMAAtic在增强计算工作流程、提高资源效率以及促进生命科学中的开放科学方面的潜力。
https://github.com/BioComputingUP/DRMAAtic，https://drmaatic.biocomputingup.it/。
