Conceptual and Technical Challenges for High Performance Computing
Claude Tadonki

TL;DR
This paper discusses the challenges in achieving high performance in supercomputing, emphasizing the importance of efficient algorithms, programming skills, and scalability to meet the demands of large-scale scientific problems.
Contribution
It provides an overview of the conceptual and technical challenges in HPC, highlighting the need for scalable algorithms and effective programming strategies for exascale computing.
Findings
Processing speed alone is insufficient for large-scale problems
Efficient code design and scalability are critical for high performance
Achieving high utilization of peak performance remains challenging
Abstract
High Performance Computing (HPC) aims at providing reasonably fast computing solutions to scientific and real life problems. The advent of multicore architectures is noticeable in the HPC history, because it has brought the underlying parallel programming concept into common considerations. At a larger scale, there is a keen interest in building or hosting frontline supercomputers; the Top500 ranking is a nice illustration of this (implicit) racing. Supercomputers, as well as ordinary computers, have fallen in price for years while gaining processing power. We clearly see that, what commonly springs up in mind when it comes to HPC is computer capability. However, when going deeper into the topic, especially on large-scale problems, it appears that the processing speed by itself is no longer sufficient. Indeed, the real concern of HPC users is the time-to-output. Thus, we need to study…
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Taxonomy
TopicsParallel Computing and Optimization Techniques · Distributed and Parallel Computing Systems · Advanced Data Storage Technologies
