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Exascale computing
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Exascale computing
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 now defunct 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. As of November 2024[update], Lawrence Livermore National Laboratory's El Capitan is the world's fastest exascale supercomputer.
A new exascale supercomputer, JUPITER, was inaugurated in Germany in 2025. Although it is the 4th in the world ranking at the moment, it has the number‑one position on the Green500 ranking, because the system runs entirely on renewable energy and features cutting-edge cooling and energy reuse, making it the world's most energy-efficient 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. The Folding@home project, the first to break this barrier, relied on a network of servers sending pieces of work to hundreds of thousands of clients using a client–server model network architecture.
The first petascale (1015 FLOPS) computer entered operation in 2008. At a supercomputing conference in 2009, Computerworld projected exascale implementation by 2018. In June 2014, the stagnation of the Top500 supercomputer list had observers question the possibility of exascale systems by 2020.
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Exascale computing
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 now defunct 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. As of November 2024[update], Lawrence Livermore National Laboratory's El Capitan is the world's fastest exascale supercomputer.
A new exascale supercomputer, JUPITER, was inaugurated in Germany in 2025. Although it is the 4th in the world ranking at the moment, it has the number‑one position on the Green500 ranking, because the system runs entirely on renewable energy and features cutting-edge cooling and energy reuse, making it the world's most energy-efficient 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. The Folding@home project, the first to break this barrier, relied on a network of servers sending pieces of work to hundreds of thousands of clients using a client–server model network architecture.
The first petascale (1015 FLOPS) computer entered operation in 2008. At a supercomputing conference in 2009, Computerworld projected exascale implementation by 2018. In June 2014, the stagnation of the Top500 supercomputer list had observers question the possibility of exascale systems by 2020.
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