Converging High-Performance Computing, Artificial Intelligence, and Intelligent Workflows for Next-Generation Innovation

The increasing intricacy of scientific simulations and industrial activity processes along with their accompanying datasets demand ecosystems outside the capabilities of traditional High-Performance Computing (HPC) systems [1]–[6], [11]. The requirements of contemporary research and industries based on data are multidisciplinary, as computations using traditional HPC await a solution. Recently, attention has been drawn towards harnessing the computational power of AI facilities to relieve HPC systems as the fusion of intelligence reveals new adaptive workflows that integrate HPC and AI capabilities. This evolution in thinking gives rise not only to an emergent paradigm for an AI-powered HPC but also to the transforma- tional approach of the HPC-AI Workflow Platform that incor- porates synergistic and intelligent orchestration workflows. In this paper, we introduce the HPC-AI Workflow Platform, which catalyzes collaborative innovation with its innovative Workflow- as-a-Service (WaaS) model, facilitating effortless cross-domain sharing and reuse of workflows, boosting operational efficiency. They are further enabled with AI for real-time decision-making and optimization, smart resource allocation, big data analytics, and seamless data flow for the timely and energy-efficient execution of complex simulations, enhancing HPC productivity. This not only demonstrates the efficacy of the HPC-AI Workflow Platform in resourceful workflow optimization and management but also strengthens its position as a future- ready paradigm to advance HPC application relevance in science and industry.

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Publication Details

Published
2025-05-14
DOI
https://doi.org/10.38124/ijisrt/25apr1850
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
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article

Converging High-Performance Computing, Artificial Intelligence, and Intelligent Workflows for Next-Generation Innovation

Yejun Son, Son Dang, Brandon Kim
Scientific Computing and Data Management
article

Converging High-Performance Computing, Artificial Intelligence, and Intelligent Workflows for Next-Generation Innovation

Yejun Son, Son Dang, Brandon Kim
article en

Abstract

The increasing intricacy of scientific simulations and industrial activity processes along with their accompanying datasets demand ecosystems outside the capabilities of traditional High-Performance Computing (HPC) systems [1]–[6], [11]. The requirements of contemporary research and industries based on data are multidisciplinary, as computations using traditional HPC await a solution. Recently, attention has been drawn towards harnessing the computational power of AI facilities to relieve HPC systems as the fusion of intelligence reveals new adaptive workflows that integrate HPC and AI capabilities. This evolution in thinking gives rise not only to an emergent paradigm for an AI-powered HPC but also to the transforma- tional approach of the HPC-AI Workflow Platform that incor- porates synergistic and intelligent orchestration workflows. In this paper, we introduce the HPC-AI Workflow Platform, which catalyzes collaborative innovation with its innovative Workflow- as-a-Service (WaaS) model, facilitating effortless cross-domain sharing and reuse of workflows, boosting operational efficiency. They are further enabled with AI for real-time decision-making and optimization, smart resource allocation, big data analytics, and seamless data flow for the timely and energy-efficient execution of complex simulations, enhancing HPC productivity. This not only demonstrates the efficacy of the HPC-AI Workflow Platform in resourceful workflow optimization and management but also strengthens its position as a future- ready paradigm to advance HPC application relevance in science and industry.

Openalex Percentile: Top 89%
Scientific Computing and Data Management
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