EXA SCALE COMPUTING: THE ENGINE OF DISCOVERY

SAI CHANDANA SIRISHA GORASA

III B.Tech, Pragati Engineering College, ADB Road, Surampalem, East Godavari Dt. E-mail: [email protected]

Abstract - This paper presents a detailed information about one of the levels of High Performance Computing namely . Computer architectures are expected to change to extend their support to Exa-scale computing in the near future. Exascale computing will have a profound impact on everyday life in the coming decades. It originated from petascale computing. It is simply considered as a transformation of petascale computing. One exaflop equals 1000 petaflops(1018flops per second)which is also known as a quintillion. Exascale computing is a milestone in the history of high performance computing.

Keywords - High speed, Large scale, High Performance Computing, Floating point operations(Flops),Super Computers, Energy Consumption

I. INTRODUCTION similar to the development of the human brain project.It could equate with the processing power of Computing is the act or the process of calculating the human brain. An Exascale computer can predict something using or connected with computers. climate change and thereby can withstand drought.It Exascale computing is the capability of computing could even be used to predict crime precisely and systems to perform at least one exaflops i.e., a billion with more accuracy than the current predictive billion calculations per second. Flop is the unit of policing systems. Drought-resistant plants and measurement of performance of computing. The first biofuels can be created. More sustainable future can petascale computer came into operation in the year be engineered with the help of stronger computers. 2008.Exascale super computer represents a vast Many problems can be overcome with ease with the increase in the performance of computing over the development of an Exascale computer. peta scale super computer. At a super computing Exascale computing is the term we use for the next conference in 2009, it is expected to be implemented 50- to 100-fold increase in speed over the fastest by 2018.Exascale super computer is assumed to be which are in broad use today. An powerful enough to predict the future. Exascale super computer is a trillion times faster than the gigascale super computer.Achievement of such speeds is not an easy task.Several efforts are being carried out by different countries of the world to bring an exascale super computer into operation because of the benefits it brings to the performance of computing.

III. DEVELOPMENT BY DIFFERENT COUNTRIES

China: The two fastest super computers in the world Sunway TaihuLight and Tianhe-2(Milkyway-2) are owned by China and clock in at 93 and 33 petaflops. But the countries like US,Japan and other competing nations wanted to build the world’s first exascale super Figure 1: Different scales for measuring performance of computer.There is no computer in the world as computing powerful as the exascale super computer.According

to the national plan for the next generation of high II. WHY EXA SCALE…??? performance computers, China will develop an

exascale computer during the 13th Five-Year-Plan The more powerful and capable is the computer, the period (2016-2020).The exascale super computer is more realistic models it can create. Weather and planned to be named as Tianhe-3 by China. earthquakes are already predicted by the super Taiwan: computers we have. Complex biological systems The largest global center for the research and cannot be modelled with the current computing development of industrial and electronics technology power.Current super computers cannot equate the as well as the center of manufacturing for at least computing power of an Exascale super computer.It is 80% of all computer hardware technology in the

Proceedings of IRAJ International Conference, 10th June, 2018, Hyderabad, India 17 Exa Scale Computing: The Engine of Discovery world is Taiwan.It initiated a lot of efforts by its the ARMv8 architecture with extensions it was co- various scientific organizations belonging to both designing with ARM Limited. government and private industries to build an Europe: exascale computer. Taiwan's National Center for European Union have already started building several High-Performance Computing took a first step projects which aimed at developing technologies and towards building the first Taiwanese exascale software for exascale computing in 2011.The projects by funding construction of a new are the CRESTA project (Collaborative Research into intermediary supercomputer based on a full Exascale System ware, Tools and Applications), the technology transfer from Fujitsu corporation of Japan DEEP project (Dynamical Exascale Entry Platform), in June 2017..Taiwanese Foxconn and the project Mont-Blanc. A crucial and major Corporationrecently designed and built the largest European project which is based and concentrated on and fastest supercomputer in whole of Taiwan. This the transition of exascale is the MaX (Materials at the new Foxconn supercomputer is designed and built to Exascale) project.In 2015 the Scalable, Energy- serve as a wonderful invention in research and Efficient, Resilient and Transparent Software development towards the design and building of a Adaptation (SERT) project, a major research project state of the art Taiwanese exascale supercomputer. between the University of Manchester and the United States: Science and Technology Facilities Council (STFC). Because of the reason that building an exascale Daresbury Laboratory in Cheshire, was awarded c. computer is a national-level project,theU.S. £1million from the UK’s Engineering and Physical Department of Energy shelled out $258 million to six Sciences Research Council. The SERT project was different companies namely Hewlett-Packard, Intel, kept due to start in March 2015 andit will be funded Nvidia, Advanced Micro Devices, Cray, and IBM.All by Engineering and Physical Sciences Research these are currently working on the components that Council (EPSRC) under the Software for the Future II would one day go into building such a programme and the project will coordinate and system.Funding to the Institute for Advanced collaborate with the Numerical Analysis Group Architecturesto develop an exascale supercomputer (NAG), Cluster Vision and the STFC. was provided by the two United States of America India: governmental organizations within the US Government of India has proposed to commit 2.5 Department of Energy,the Office of Science and the billion USD in 2012for supercomputing research National Nuclear Security Administration in during the 12th five-year plan period (2012–2017). 2008.Sandia NationalLaboratory and the Oak Ridge The project will be handled by Indian Institute of National Laboratory also wanted to collaborate on Science (IISc), Bangalore.It was later known that exascale designs. Intel promised to develop an India attempts and is planning to develop a exascale technology by 2018.In order to fulfill its supercomputer with processing power in therange of promise,it purchased the InfiniBand product line from exaflops. Within the subsequent 5 years of approval,it QLogic for US $125million in January 2012.By 2012 will be handed over to C-DAC (Centre for the United States had allotted $126 million for Development of Advanced Computing) and will be exascale computing development.President Obama developed further. signed an executive order creating a National Strategic Computing Initiative calling for the The nation that developsan exascale super computer accelerated development of an exascale system and first will unlock all kinds of ways of predicting the funding research into post-semiconductor computing future and understanding the present. The country can on 29 July,2015. The Exascale Computing Project be far ahead of the rest of the world in terms of hopes to build an exascale computer by 2021. As part scientific and technological achievement, which in of the Department of Energy’s larger exascale turn translates to economic power. project, the NREL (National Renewable Energy Laboratory) located in Golden,Colorado is working to The following tables give information about the build predictive wind energy models that can work on fastest super computers developed as of November, an exascale-level machine by 2022. 2016 and take towards the exascale hardware: Japan: The RIKEN Advanced Institute for Computational Rank Name Country Type Science of Japan in the year 2013 began planning an Sunway 1 China Sunway26010 exascale system for 2020.Its main intension was to TaihuLight consume less than 30 megawatts. Later in Tianhe-2 2014,Fujitsu was awarded a contract by RIKEN.It Intel 2 (Milky China was to develop a next-generation supercomputer to Xeon/Xeon Phi succeed the K computer. In 2015, Fujitsu announced way -2) Opteron/Nvidia at the International Supercomputing Conference that 3 Titan USA this supercomputer will use processors implementing Kepler

Proceedings of IRAJ International Conference, 10th June, 2018, Hyderabad, India 18 Exa Scale Computing: The Engine of Discovery

IBM Power Reduction of Pollution: Exascale computing is 4 USA BQC capable enough to reduce pollution caused by burning fossil fuels which is detrimental to our health. The Intel Xeon Phi 5 Cori USA environmental impact of burning fossil fuels is global warming. Carbon dioxide traps the heat in the Table 1: Fastest Super Computers as of November, 2016 atmosphere. It is emitted during fossil fuel burning. Approximately, 85 percent of the world’s energy is Peta Power Name Cores generated by burning fossil fuels. The only way to (MW) minimize pollution and optimize is by understanding Sunway and controlling the chemical process of combustion. 10,649,600 93 15 TaihuLight With the help of exascale computing, we expect it Tianhe-2 will be possible to increase the efficiency of (Milky 3,120,000 33.86 18 combustion systems in engines and gas turbines for way -2) transportation and power generation by potentially Titan 560,000 18 8 25-50%and to lower emissions. Sequoia 1,572,864 17 8 Cori 622,336 14 4 Table2: Hardware of the super computers mentioned

From table2, the following observations are made:  There is an increase in core counts.  Energy consumption is an issue.  It trends towards many core architectures. They can reduce energy consumption. Less consumption of energy is essential to preserve energy for future generations. The power of computing should reach from petascale to exascale as fast as possible for better performance and more accurate predictions of weather conditions and many more.Exascale super computer can solve many sophisticated problems.

( performance in pflops )

10,000 Figure 3: Various applications of exascale computing 1,000 TITAN SUNWAY TAIHULIGHT(China, 93pflops) 100 (United States, 17 PFLOPS ) New Energy Solutions: 10 TIANHE-2 ( China, 33.9 pflops) The sun is the source of all energy either in the form 1 of fossil fuels or wood. After all,these substances 0.1

0.01 BLUEGENE/L (United States, 0.28pflops) have been made from the energy of the sun and have

0.001 EARTH SIMULATOR ( Japan, 0.04 pflops ) stored its energy.However,the heat of the sun can be 0.0001 used directly in the form of solar energy,Solar cells 0.00001 and giant solar plants are used for generating 0.000001 electricity.Solar energy will also be made more cost- 0.0000001 effective through discovery of materials that convert 1995 2000 2005 2010 2015 2020 ( Years ) the sun’s rays to electricity more efficiently. Computer based design of blades came into existence by which the wind turbines can be made more Figure 2:Annual increase in the performance of super efficient and quieter. Simulations can also optimize computers the locations of individual wind turbines in wind IV. APPLICATIONS OF EXASCALE farms to yield substantially more energy from the COMPUTING same number of turbines.

Every time, computing power increases by large Another important challenge faced in the use of factors, new benefits open before us. The benefits of alternative energy sources is managing the electric exascale computing range from creating novel, more power grid. In some situations such as when the wind efficient combustion engines and new energy dies down in the area of a wind farm, for example. solutions to advances in healthcare, biology, storm The electric power grid is complex, and adjustments prediction and could potentially impact every person. such as firing up a fossil fuel generator have to be made quickly to avert problems; it is not possible to

Proceedings of IRAJ International Conference, 10th June, 2018, Hyderabad, India 19 Exa Scale Computing: The Engine of Discovery predict accurately such events far ahead of time. It is Applications in Biology: quite difficult. In such cases, computationally Biological sciences are undergoing a revolution. intensive optimization methods can provide the In biology, the challenges of modeling at large needed guidance, but to get the results in time to be multiple scalesfrom atomic, through genomic and cell useful requires fast computers. ular, to ecosystemsis driving the need for exascalecomputing and a new set of algorithms an Advances in Materials Science: d approaches. Hence, it is said that Exascale Materials Science is defined as the scientific study of computing also has some of its applications in the properties and applications of materials of biology. They might enable the prediction of feasible construction or manufacture (such as ceramics, parameter values for dynamic models of metabolism metals, polymers, and composites).In simpler words, that would help scientists to design organisms that it is the study of all materials, from those we see and would perform a variety of tasks. These models might use every day. For example, a glass or a piece of also contribute to the development of treatments for sport equipment to those which are in wide use in emerging types of infections. aerospace and medicine. For the creation of certain Improving quality of life: new technologies and inventions, we need to discover Exascale computing is widely used in urban science. new materials with specific properties. These Health hazards can be mitigated. Crime can be discoveries can be made possible by complex reduced and hence it improves the quality of life in calculations that simulate how materials behave in cities by optimizing infrastructure (such as nature and the use of massive databases of known transportation, energy, housing, healthcare) access compounds to identify combinations that have the and usage choices. Gathering and analysis of desired properties. Deep learning techniques and numerous types of data from databases, sensors and classical simulation are in use today in this field. simulation results and conducting thousands of Deep Learning is a subfield of machine learning potential scenarios is necessary for such optimization. concerned with algorithms inspired by the structure The resulting analyses will be useful for planning and function of the brain called artificial neural new cities or neighborhoods.They can also be used networks. Simulation is the imitation of the operation for restructuring the infrastructure in large urban of a real-world process or system. Exascale areas already existing. computing will enable faster and more complex Additional important applications are advanced by designs. For example, much more efficient, less exascale computing but will require even more expensive and longer-lived batteries will be computing power to accomplish such as reverse developed through discovery of new materials. engineering the human brain to understand complex Batteries are very important.These are essential not neural systems; providing new methods to integrate only for portable consumer electronics and electric large-scale data; information and simulation automobiles but to store energy from variable energy dynamics and ultimately providing societal benefits sources such as wind and solar to use when they’re for health.Exascale super computers will more needed. realistically simulate the processes involved in precision medicine, regional climate, additive Exascale computing extends its scope in other vital manufacturing etc. areas such as medicine, biology, weather forecasting etc. It is worth realizing that many planned uses of exascale computing address fundamental scientific Advances in Health Care : Exascale Deep Learning questions in a lot of fields such as high-energy and Simulation Enabled Precision Medicine for physics and chemistry. Though they are not explicitly Cancer focuses on building a scalable deep neural aimed at results that immediately benefit society, network code called the CANcer Distributed historically they have a track record of making Learning Environment (CANDLE) that addresses the discoveries that have major impacts in everyday life top challenges of the National Cancer Institute and of mankind. The obvious and lively example is the there by the Cancer research can be accelerated by world wide web(WWW), which was invented to assisting scientists to understand the molecular basis support certain aspects of particle physics research. of key protein interactions and by automating the Exascale computing will benefit society in a large analysis of information from millions of cancer number of ways. Novel discoveries, new materials patient records to determine optimal treatment and solutions to problems that impact everyday life strategies. Exascale computing is of a great use to the will be possible through new capabilities of exascale doctors to predict the right treatments for the patient computing systems. In addition to benefits to society, by modeling drug responses. These tasks are very key technological advances also hold the promise of difficult to deal with: for example, drug combination maintaining economic security.Future development in response prediction might sometimes require the the direction of high performance computing can be search of one trillion drug combinations. enhanced with exascale super computers.

Proceedings of IRAJ International Conference, 10th June, 2018, Hyderabad, India 20 Exa Scale Computing: The Engine of Discovery  Challenges in programming and runtime environments: The parallelism of exascale computers would reach to millions or ten to millions of calculations in future. Such huge parallelism would bring several problems related to programming and debugging issues. Hence to overcome this problem, the programming model which is used for exascale computing must be able to express inherent parallelism and locality of all heterogenous hierarchies. Programming interfaces must also be provided for power and reliability management. Simultaneously, the programming paradigm should Figure 4: Stepping into the future of computing be in a position to use the features provided by the architectures by which the system performance can V. CHALLENGES OF EXA SCALE be optimized. Apart from the traditional checkpoint COMPUTING approaches, exascale fault tolerance methods are to be developed further. Making the transition to exascale poses numerous unavoidable scientific and technological CONCLUSION challenges.Grand challenge problems such as regional extreme weather forecasting in The great frontier of computational physics and meteorology,3D fusion simulations in new energy engineering is in the challenge posed by high-fidelity development,solutions to high density 3D wave simulations of real world systems., in truly equations in oil exploration,protein folding in transforming computational science into a fully biology,first principles simulations in materials and predictive science.In order to make our computers nanoscience,real time multiphase complex system more predictive, we need faster computers. But simulations in process engineering and hypersonic reaching the exascale regime is a tremendous flow simulations for vehicle re-entry in aerospace technological challenge.The effort to push high- applications etc. can be solved easily with exascale performance computing to the next level i.e., from the computer systems.The overall strength of the national petascale to exascale right now is forcing a technology is represented by high performance transformation in how supercomputers are designed computer systems. Exascale super computers are and their performance measured. Different countries facing more and more severe challenges when have expected different years to design and publish compared with petascale and tera scale super exascale super computers which would come into computers. The challenges include the following: existence in the future. Computational power is a  Challenges in applicability and vitally important tool that enables scientific discovery application efficiency: The first challenge is how to and assists us in finding solutions to some of our most use exascale super computer more efficiently so that difficult problems. The quest to achieve capable they play an appropriate role in developments in exascale computing is a technological challenge that economics, society and other high-technology areas will serve to enable a new generation of insights into which is a long-term issue. such discoveries. EXASCALE COMPUTING IS A  Challenges in power efficiency: The power NEW ERA OF COMPUTING. efficiency goal that has been set for exascale super computers is 50 gigaflops per second. Shoubu REFERENCES computer in Japan, which is the number one super computer which achieves only 7 gigaflops per second [1] National Research Council (U.S.) (2008). The potential is very far away from the goal of exascale super impact of high-end capability computing on four illustrative computer. International Academia and industry have fields of science and engineering. The National Academies. p. 11. mainly focused on new low power devices and [2] Johnson, R. Colin (4 May 2008), "U.S. launches exaflop components to address this issue. supercomputer initiative”  Challenges in reliability: Reliability issues [3] Thibodeau, Patrick (November 22, 2013). "Why the U.S. may could become more challenging when the system lose the race to exascale". [4] C-DAC and Supercomputers in India reaches the exascale level.The mean time between [5] Anthony, Sebastian (June 24, 2014). "Supercomputer failures(MTBF) is only 5 hrs. for the current 10 stagnation: New list of the world's fastest computers casts petaflop systems.The development of effective shadow over exascale by 2020". resilience techniques for high performance computer [6] "U.S. Bumps Exascale Timeline, Focuses on Novel Architectures for 2021". The Next Platform. 2016-12-08. systems is one of the major challenges to be [7] "China's Exascale Supercomputer Operational by 2020--- addressed to improve the likely availability of the Chinese Academy of Sciences". exascale super computers.

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