Scalable Systems and Software Architectures for High-Performance Computing on cloud platforms
Risshab Srinivas Ramesh

TL;DR
This paper reviews scalable hardware and software architectures for high-performance computing on cloud platforms, highlighting design principles, challenges, and emerging trends to meet growing computational demands.
Contribution
It provides a comprehensive overview of HPC architecture on cloud, focusing on scalability, challenges, and recent advancements in hardware and software design.
Findings
Analysis of design principles for scalable HPC systems
Identification of key challenges like communication overhead and fault tolerance
Insights into emerging trends and solutions for cloud-based HPC
Abstract
High-performance computing (HPC) is essential for tackling complex computational problems across various domains. As the scale and complexity of HPC applications continue to grow, the need for scalable systems and software architectures becomes paramount. This paper provides a comprehensive overview of architecture for HPC on premise focusing on both hardware and software aspects and details the associated challenges in building the HPC cluster on premise. It explores design principles, challenges, and emerging trends in building scalable HPC systems and software, addressing issues such as parallelism, memory hierarchy, communication overhead, and fault tolerance on various cloud platforms. By synthesizing research findings and technological advancements, this paper aims to provide insights into scalable solutions for meeting the evolving demands of HPC applications on cloud.
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Taxonomy
TopicsDistributed and Parallel Computing Systems · Cloud Computing and Resource Management · Parallel Computing and Optimization Techniques
