Summary
Exascale computing refers to computing systems capable of calculating at least "1018 IEEE 754 Double Precision (64-bit) operations (multiplications and/or additions) per second (exaFLOPS)"; it is a measure of supercomputer performance. Exascale computing is a significant achievement in computer engineering: primarily, it allows improved scientific applications and better prediction accuracy in domains such as weather forecasting, climate modeling and personalised medicine. Exascale also reaches the estimated processing power of the human brain at the neural level, a target of the Human Brain Project. There has been a race to be the first country to build an exascale computer, typically ranked in the TOP500 list. In 2022, the world's first public exascale computer, Frontier, was announced. , it is the world's fastest supercomputer. Floating point operations per second (FLOPS) are one measure of computer performance. FLOPS can be recorded in different measures of precision, however the standard measure (used by the TOP500 supercomputer list) uses 64 bit (double-precision floating-point format) operations per second using the High Performance LINPACK (HPLinpack) benchmark. Whilst a distributed computing system had broken the 1 exaFLOPS barrier before Frontier, the metric typically refers to single computing systems. Supercomputers had also previously broken the 1 exaFLOPS barrier using alternative precision measures; again these do not meet the criteria for exascale computing using the standard metric. It has been recognised that HPLinpack may not be a good general measure of supercomputer utility in real world application, however it is the common standard for performance measurement. It has been recognized that enabling applications to fully exploit capabilities of exascale computing systems is not straightforward. Developing data-intensive applications over exascale platforms requires the availability of new and effective programming paradigms and runtime systems.
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.