Scientists, engineers, and researchers leverage high-performance computing (HPC) systems to perform complex computations and process large amounts of data. Designing, developing, and operating HPC systems have a steep...
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ISBN:
(纸本)9798400702532
Scientists, engineers, and researchers leverage high-performance computing (HPC) systems to perform complex computations and process large amounts of data. Designing, developing, and operating HPC systems have a steep learning curve, thus making it crucial to train a highly skilled and knowledgeable workforce in order to keep up with the rapidly evolving field, drive innovation, and meet the increasing demand for HPC across various sectors. Limited access to HPC educational resources is the main deterrent to training HPC talent. This paper addresses two primary culprits for the limited access: the high cost of production systems and the lack of realistic full-stack HPC training. Cutting-edge hardware is usually expensive and requires specialized facilities. Moreover, large HPC facilities typically discourage experimenting with the systems since they run production computation workloads and require minimal disturbance. Furthermore, HPC training often does not reflect the scale or complexity of production systems. This lack of realistic training support makes education in this area particularly difficult and ineffective. This paper proposes an educational framework for HPC that includes the development of a low-cost and flexible platform design for users in diverse fields. It allows study and experimentation with multiple realistic elements involved in a production HPC ecosystem. DEMAC, the Delaware Modular Assembly Cluster, is a set of 3D-printable frames designed to house embedded systems and auxiliary systems in a way that emulates HPC platforms. The teaching framework focuses on practical training as an education model in which learners reinforce theoretical knowledge with hands-on experience. If successful, this effort will contribute fundamentally to scientific research, technological advancements, HPC workforce development, and economic growth.
Due to the increase of the diversity of parallel architectures, and the increasing development time for parallel applications, performance portability has become one of the major considerations when designing the next...
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Due to the increase of the diversity of parallel architectures, and the increasing development time for parallel applications, performance portability has become one of the major considerations when designing the next generation of parallel program executionmodels, APIs, and runtime system software. This paper analyzes both code portability and performance portability of parallel programs for fine-grained multi-threaded execution and architecture models. We concentrate on one particular event-driven fine-grained multi-threaded executionmodel-EARTH, and discuss several design considerations of the EARTH model and runtime system that contribute to the performance portability of parallel applications. We believe that these are important issues for future high end computing system software design. Four representative benchmarks were conducted on several different parallel architectures, including two clusters listed in the 23rd supercomputer TOP500 list. The results demonstrate that EARTH based programs can achieve robust performance portability across the selected hardware platforms without any code modification or tuning
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