DRMAAtic: dramatically improve your cluster potential.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Bioinformatics advances Pub Date : 2025-05-15 eCollection Date: 2025-01-01 DOI:10.1093/bioadv/vbaf112
Alessio Del Conte, Hamidreza Ghafouri, Damiano Clementel, Ivan Mičetić, Damiano Piovesan, Silvio C E Tosatto, Alexander Miguel Monzon
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引用次数: 0

Abstract

Motivation: 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.

Results: 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.

Availability and implementation: https://github.com/BioComputingUP/DRMAAtic, https://drmaatic.biocomputingup.it/.

戏剧性:显著提高集群潜力。
动机:高性能计算(HPC)资源的可及性和可用性仍然是生物信息学的重大挑战,特别是对于缺乏广泛技术专长的研究人员。尽管分布式资源管理器(drm)优化了资源利用,但与这些系统交互的复杂性往往阻碍了更广泛的采用。通过将分布式资源管理应用程序API (DRMAA)与用户友好的RESTful接口集成,简化了不同HPC环境中的作业管理,DRMAAtic解决了这些挑战。该框架使研究人员能够安全有效地提交、监控和检索计算作业,而不需要深入了解底层集群配置。结果:我们提出了一个灵活的、可扩展的工具,它弥合了web界面和HPC基础设施之间的差距。基于Django REST框架,DRMAAtic支持通过HTTP调用无缝提交和管理作业。它的模块化体系结构支持与任何支持DRMAA api的DRM集成,并提供诸如基于角色的访问控制、节流机制和依赖关系管理等健壮的特性。成功的应用包括用于蛋白质结构分析的RING web服务器,用于无序和结合预测的CAID预测门户,以及蛋白质集成数据库沉积服务器。这些部署证明了dramatic在增强计算工作流程、提高资源效率和促进生命科学领域开放科学方面的潜力。可用性和实现:https://github.com/BioComputingUP/DRMAAtic, https://drmaatic.biocomputingup.it/。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.60
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0.00%
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