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• W4313260042 endingPage "53" @default.
• W4313260042 startingPage "53" @default.
• W4313260042 abstract "Big data has revolutionized science and technology leading to the transformation of our societies. High-performance computing (HPC) provides the necessary computational power for big data analysis using artificial intelligence and methods. Traditionally, HPC and big data had focused on different problem domains and had grown into two different ecosystems. Efforts have been underway for the last few years on bringing the best of both paradigms into HPC and big converged architectures. Designing HPC and big data converged systems is a hard task requiring careful placement of data, analytics, and other computational tasks such that the desired performance is achieved with the least amount of resources. Energy efficiency has become the biggest hurdle in the realization of HPC, big data, and converged systems capable of delivering exascale and beyond performance. Data locality is a key parameter of HPDA system design as moving even a byte costs heavily both in time and energy with an increase in the size of the system. Performance in terms of time and energy are the most important factors for users, particularly energy, due to it being the major hurdle in high-performance system design and the increasing focus on green energy systems due to environmental sustainability. Data locality is a broad term that encapsulates different aspects including bringing computations to data, minimizing data movement by efficient exploitation of cache hierarchies, reducing intra- and inter-node communications, locality-aware process and thread mapping, and in situ and transit data analysis. This paper provides an extensive review of cutting-edge research on data locality in HPC, big data, and converged systems. We review the literature on data locality in HPC, big data, and converged environments and discuss challenges, opportunities, and future directions. Subsequently, using the knowledge gained from this extensive review, we propose a system architecture for future HPC and big data converged systems. To the best of our knowledge, there is no such review on data locality in converged HPC and big data systems." @default.
• W4313260042 created "2023-01-06" @default.
• W4313260042 creator A5022780651 @default.
• W4313260042 creator A5036614024 @default.
• W4313260042 creator A5045587553 @default.
• W4313260042 creator A5077619272 @default.
• W4313260042 date "2022-12-23" @default.
• W4313260042 modified "2023-09-30" @default.
• W4313260042 title "Data Locality in High Performance Computing, Big Data, and Converged Systems: An Analysis of the Cutting Edge and a Future System Architecture" @default.
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