From Science Node: “The race to exascale”

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From Science Node

30 Jan, 2018
Alisa Alering

Who will get the first exascale machine – a supercomputer capable of 10^18 floating point operations per second? Will it be China, Japan, or the US?

When it comes to computing power you can never have enough. In the last sixty years, processing power has increased more than a trillionfold.

Researchers around the world are excited because these new, ultra-fast computers represent a 50- to 100-fold increase in speed over today’s supercomputers and promise significant breakthroughs in many areas. That exascale supercomputers are coming is pretty clear. We can even predict the date, most likely in the mid-2020s. But the question remains as to what kind of software will run on these machines.

Exascale computing heralds an era of ubiquitous massive parallelism, in which processors perform coordinated computations simultaneously. But the number of processors will be so high that computer scientists will have to constantly cope with failing components.

The high number of processors will also likely slow programs tremendously. The consequence is that beyond the exascale hardware, we will also need exascale brains to develop new algorithms and implement them in exascale software.

In 2011, the German Research Foundation established a priority program “Software for Exascale Computing”( SPPEXA ) to addresses fundamental research on various aspects of high performance computing (HPC) software, making the program the first of its kind in Germany.

SPPEXA connects relevant sub-fields of computer science with the needs of computational science and engineering and HPC. The program provides the framework for closer cooperation and a co-design-driven approach. This is a shift from the current service-driven collaboration of groups focusing on fundamental HPC methodology (computer science or mathematics) on the one side with those working on science applications and providing the large codes (science and engineering) on the other side.

Despite exascale computing still being several years away, SPPEXA scientists are well ahead of the game, developing scalable and efficient algorithms that will make the best use of resources when the new machines finally arrive. SPPEXA drives research towards extreme-scale computing in six areas: computational algorithms, system software, application software, data management and exploration, programming, and software tools.

Some major projects include research on alternative sources of clean energy; stronger, lighter weight steel manufacturing; and unprecedented simulations of the earth’s convective processes:

EXAHD supports Germany’s long-standing research into the use of plasma fusion as a clean, safe, and sustainable carbon-free energy source. One of the main goals of the EXAHD project is to develop scalable and efficient algorithms to run on distributed systems, with the aim of facilitating the progress of plasma fusion research.

EXASTEEL is a massively parallel simulation environment for computational material science. Bringing together experts from mathematics, material and computer sciences, and engineering, EXASTEEL will serve as a virtual laboratory for testing new forms of steel with greater strengths and lower weight.

TerraNeo addresses the challenges of understanding the convection of Earth’s mantle – the cause of most of our planet’s geological activity, from plate tectonics to volcanoes and earthquakes. Due to the sheer scale and complexity of the models, the advent of exascale computing offers a tremendous opportunity for greater understanding. But in order to take full advantage of the coming resources, TerraNeo is working to design new software with optimal algorithms that permit a scalable implementation.

Exascale hardware is expected to have less consistent performance than current supercomputers due to fabrication, power, and heat issues. Their sheer size and unprecedented number of components will likely increase fault rates. Fast and Fault-Tolerant Microkernel-based Operating System for Exascale Computing (FFMK) aims to address these challenges through a coordinated approach that connects system software, computational algorithms, and application software.

Mastering the various challenges related to the paradigm shift from moderately to massively parallel processing will be the key to any future capability computing application at exascale. It will also be crucial for learning how to effectively and efficiently deal with near-future commodity systems smaller-scale or capacity computing tasks. No matter who puts the first machine online, exascale supercomputing is coming. SPPEXA is making sure we are prepared to take full advantage of it.

See the full article here .

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