computer science

Zettascale computing

Zettascale computing is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Zettascale computing rather than just read about it. In short: Zettascale computing refers to computing systems capable of calculating at least "1021 IEEE 754 Double Precision (64-bit) operations (multiplications and/or additions) per second (zettaFLOPS)". It is a measure of supercomputer performance, and as of July 2022 is a hypothetical performance barrier.

Key takeaways

Zettascale computing belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Zettascale computing to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Zettascale computing from memory before moving on to harder problems.

Reference excerpt

Zettascale computing refers to computing systems capable of calculating at least "1021 IEEE 754 Double Precision (64-bit) operations (multiplications and/or additions) per second (zettaFLOPS)". It is a measure of supercomputer performance, and as of July 2022 is a hypothetical performance barrier. A zettascale computer system could generate more single floating point data in one second than was stored by the total digital means on Earth in the first quarter of 2011.

Definitions

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.

Forecasts In 2018, Chinese scientists predicted that the first zettascale system will be assembled in 2035. This forecast looks plausible from a historical point of view as it took some 12 years to progress from the terascale machines (1012) to petascale systems (1015) and then 14 more years to move to exascale computers (1018). Scientists forecast that the zettascale systems are likely to be data-centric; this proposition means that the system components will move to the data, not vice versa, as the data volumes in the future are anticipated to be so large that moving data will be too expensive. It is also forecasted that zettascale systems are expected to be decentralized—because such a model can be the shortest route to achieving zettascale performance, with millions of less powerful components linked and working together to form a collective hypercomputer that is more powerful than any single machine. Such decentralized systems may be designed to mimick complex biologic systems, and the next cybernetic paradigm may be based on liquid cybernetic systems with embodied intelligence solutions.

Potential configuration China's National University of Defense Technology propose the following metrics:

Power consumption: 100 MW Power efficiency: 10 teraflops/watt Peak performance per node: 10 petaflops Communication bandwidth between nodes: 1.6 terabits/second I/O bandwidth: 10 to 100 petabytes/second Storage capacity: 1.0 zettabyte Floor space: 1000 square meters

Problems As Moore's law nears its natural limits, supercomputing will face serious physical problems in moving from exascale to zettascale systems, making the decade after 2020 a vital period to develop key high-performance computing techniques. Many forecasters, including Gordon Moore himself, expect Moore's law to end by around 2025. Another challenge for reaching zettascale performance can be enormous energy consumption.

Applications Zettascale computers will be able to accurately forecast global weather for 2 weeks in the future. Zettascale computers will also be able to significantly reduce the time required for astrophysical simulations of rare phenomena such as black holes, neutron star mergers, and supernovae. For example, calculating a 3D model of shock wave instability from a collapsing supernova core, which takes 1 million hours on petascale computers and 1000 hours on exascale machines, can be done in just one hour on zettascale systems. Zettascale or yottascale systems might be able to accurately model the whole human brain.

See also Computer performance by orders of magnitude Exascale computing Petascale computing List of hypothetical technologies

References

External links Perspectives on High-Performance Computing in a Big Data World Towards Zettascale Computing on Exascale Platforms

Worked examples

Example 1 — a first encounter with Zettascale computing

Start with the simplest possible case. Write down what Zettascale computing claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Zettascale computing before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Zettascale computing ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Zettascale computing

In research: Zettascale computing appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Zettascale computing in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Zettascale computing is common in secondary-school and first-year university syllabi. It links to neighbouring topics Supercomputing, so understanding it makes those chapters shorter.
In everyday life: Look for Zettascale computing outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Zettascale computing in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Zettascale computing means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Zettascale computing out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Zettascale computing in simple terms?

Why does Zettascale computing matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Zettascale computing?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Zettascale computing.