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vivien-chu committed Mar 25, 2023
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<p>In the past decade, high-end computing (HEC) architectures have become an important tool in all aspects of scientific discovery. Having ushered in an era where HEC-enabled simulation is considered a third pillar of science along with theory and experiment, HEC architectures have quickly become a credible direction of focused and long-term research. Rapid advances are taking place in different aspects of HEC architectures in an effort to improve performance. Multi- and many-core systems (e.g., Intel, AMD), accelerators (e.g., GPGPUs), high-speed network architectures (e.g., InfiniBand), and integrated computing platforms (Blue Gene, Cray) have been introduced along this effort. Reconfigurable architectures (e.g., FPGAs) have shown dramatic gains in performance and energy for some types of high-performance applications. Recent advances in quantum computers and quantum computing systems further offer powerful solvers to a wide range of scientific applications. The growing convergence of HEC and data-driven AI computing is also bringing efficient Application Specific Integrated Circuit (ASIC) architectures into the HEC world. </p>

<p>These advances in the fundamental architecture of HEC architectures mean little, however, without appropriate software components that enable high-performance applications to take advantage of these architectures. System software plays a crucial role in exposing the raw performance of the underlying hardware in an efficient manner. Equally important are productive, expressive, portable, and high-performance Parallel Programming models that enable scientists to express parallel algorithms so that they can execute efficiently on various HEC architectures. </p>
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