Exascale computing

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Exascale computing refers to computing systems capable of calculating at least 1018 floating point operations per second (1 exaFLOPS). The terminology generally refers to the performance of supercomputer systems and although no single machine has reached this goal as of June 2020, there are systems being designed to reach this milestone. In April 2020, the distributed computing Folding@home network attained one exaFLOPS of computing performance.[1][2][3][4]

Exascale computing would be a significant achievement in computer engineering. Primarily it will allow improved scientific applications and better prediction such as in weather forecasting and personalised medicine.[5] Exascale also reaches the estimated processing power of the human brain at the neural level, a target of the Human Brain Project.[6] As in the TOP500 list there is also a race to be the first country to build an exascale computer.[7][8][9][10]


Floating point operations per second (FLOPS) are a measure of computer performance. FLOPS can be recorded in different measures of precision, however the standard measure used by the TOP500 supercomputer list ranks computers by 64 bit (double-precision floating-point format) operations per second using the LINPACK benchmark.[11]

Technological challenges[edit]

It has been recognized that enabling applications to fully exploit capabilities of exascale computing systems is not straightforward.[12] Developing data-intensive applications over exascale platforms requires the availability of new and effective programming paradigms and runtime systems. [13] 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.[14][15]


The first petascale (1015 FLOPS) computer entered operation in 2008.[16] At a supercomputing conference in 2009, Computerworld projected exascale implementation by 2018.[17] In June 2014, the stagnation of the Top500 supercomputer list had observers question the possibility of exascale systems by 2020.[18]

Although exascale computing was not achieved by 2018, in the same year the Summit OLCF-4 supercomputer performed 1.8×1018 calculations per second using an alternative metric (i.e. not FLOPS) whilst analysing genomic information.[19] The team performing this won the Gordon Bell Prize at the 2018 ACM/IEEE Supercomputing Conference.[citation needed]

The exaFLOPS barrier was first broken in March 2020 by the distributed Folding@home project.[20][15]



As of June 2020, China has two of the five fastest supercomputers in the world.[21] China's first exascale supercomputer will enter service after mid-2020 according to the head of the school of computing at the National University of Defense Technology (NUDT). According to the national plan for the next generation of high performance computers, China will develop an exascale computer during the 13th Five-Year-Plan period (2016–2020). The government of Tianjin Binhai New Area, NUDT and the National Supercomputing Center in Tianjin are working on the project. After Tianhe-1 and Tianhe-2, the exascale successor is planned to be named Tianhe-3.[22]

United States[edit]

In 2008, two United States of America governmental organisations within the US Department of Energy, the Office of Science and the National Nuclear Security Administration, provided funding to the Institute for Advanced Architectures for the development of an exascale supercomputer; Sandia National Laboratory and the Oak Ridge National Laboratory were also to collaborate on exascale designs.[23] The technology was expected to be applied in various computation-intensive research areas, including basic research, engineering, earth science, biology, materials science, energy issues, and national security.[24]

In January 2012, Intel purchased the InfiniBand product line from QLogic for US $125 million in order to fulfill its promise of developing exascale technology by 2018.[25]

By 2012, the United States had allotted $126 million for exascale computing development.[26]

In February 2013,[27] the Intelligence Advanced Research Projects Activity started Cryogenic Computer Complexity (C3) program which envisions a new generation of superconducting supercomputers that operate at exascale speeds based on superconducting logic. In December 2014 it announced a multi-year contract with International Business Machines, Raytheon BBN Technologies and Northrop Grumman to develop the technologies for C3 program.[28]

On 29 July 2015, Barack Obama signed an executive order creating a National Strategic Computing Initiative calling for the accelerated development of an exascale system and funding research into post-semiconductor computing.[29] The Exascale Computing Project hopes to build an exascale computer by 2021.[30]

On 18 March 2019, the United States Department of Energy and Intel announced the first exaFLOPS supercomputer would be operational at Argonne National Laboratory by the end of 2021. The computer, named "Aurora" is to be delivered to Argonne by Intel and Cray (now Hewlett Packard Enterprise), and is expected to use Intel Xe GPGPUs alongside a future Xeon Scalable CPU, and cost US$600 Million. [31]

On 7 May 2019, the U.S. Department of Energy announced a contract with Cray Inc. (now Hewlett Packard Enterprise) to build the Frontier supercomputer at Oak Ridge National Laboratory. Frontier is anticipated to be operational in 2021 and, with a performance of greater than 1.5 exaFLOPS, should then be the world’s most powerful computer.[32]

On 4 March, 2020, The U.S. Department of Energy (DOE) announced a contract with Hewlett Packard Enterprise and AMD, to build the El Capitan supercomputer at a cost of US$600 Million, to be installed at the Lawrence Livermore National Laboratory (LLNL). It is expected to be used primarily (but not exclusively) for nuclear weapons modeling. It was first announced in August 2019, when the DOE and LLNL announced the purchase of a Shasta supercomputer from Cray. It should be operational in early 2023 and have a performance of 2 exaFLOPS. It will use AMD CPUs and GPUs, with 4 Radeon Instinct GPUs per EPYC Zen 4 CPU, to speed up Artificial Intelligence tasks. It should consume around 40 MW of electric power. [33][34]


In June 2017, Taiwan's National Center for High-Performance Computing initiated the effort towards designing and building the first Taiwanese exascale supercomputer by funding construction of a new intermediary supercomputer based on a full technology transfer from Fujitsu corporation of Japan, which is currently building the fastest and most powerful A.I. based supercomputer in Japan.[35][36][37][38][39] Additionally, numerous other independent Taiwanese efforts have been made in Taiwan with the focus on the rapid development of exascale supercomputing technology, such as the Taiwanese Foxconn Corporation which recently designed and built the largest and fastest supercomputer in all of Taiwan. This new Foxconn supercomputer is designed to serve as a stepping stone in research and development towards the design and building of a state of the art Taiwanese exascale supercomputer.[40][41][42][43]

European Union[edit]

See also Supercomputing in Europe

In 2011, several projects aiming at developing technologies and software for exascale computing were started in the EU. The CRESTA project (Collaborative Research into Exascale Systemware, Tools and Applications),[44] the DEEP project (Dynamical ExaScale Entry Platform),[45] and the project Mont-Blanc.[46] A major European project based on exascale transition is the MaX (Materials at the Exascale) project.[47] The Energy oriented Centre of Excellence (EoCoE) exploits exascale technologies to support carbon-free energy research and applications.[48]

In 2015, the Scalable, Energy-Efficient, Resilient and Transparent Software Adaptation (SERT) project, a major research project between the University of Manchester and the STFC Daresbury Laboratory in Cheshire, was awarded c. £1million from the UK’s Engineering and Physical Sciences Research Council. The SERT project was due to start in March 2015. It will be funded by EPSRC under the Software for the Future II programme, and the project will partner with the Numerical Analysis Group (NAG), Cluster Vision and the Science and Technology Facilities Council (STFC).[49]

On 28 September 2018, the European High-Performance Computing Joint Undertaking (EuroHPC JU) was formally established by the EU. The EuroHPC JU aims to build an exascale supercomputer by 2022/2023. The EuroHPC JU will be jointly funded by its public members with a budget of around €1 billion. The EU's financial contribution is €486 million.[50][51]


In Japan, in 2013, the RIKEN Advanced Institute for Computational Science began planning an exascale system for 2020, intended to consume less than 30 megawatts.[52] In 2014, Fujitsu was awarded a contract by RIKEN to develop a next-generation supercomputer to succeed the K computer. The successor is called Fugaku, and aims to have a performance of at least 1 exaFLOPS, and be fully operational in 2021. It was partially put into operation in June 2020.[53] In 2015, Fujitsu announced at the International Supercomputing Conference that this supercomputer will use processors implementing the ARMv8 architecture with extensions it was co-designing with ARM Limited.[54]


In 2012, the Indian Government proposed to commit US$2.5 billion to supercomputing research during the 12th five-year plan period (2012–2017). The project was to be handled by Indian Institute of Science (IISc), Bangalore.[55] Additionally, it was later revealed that India plans to develop a supercomputer with processing power in the exaFLOPS range.[56] It will be developed by C-DAC within the subsequent five years of approval.[57]

See also[edit]


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