#exascale computing

[jcmarchi]

Aiming exascale at black holes - Technology Org

New Post has been published on https://thedigitalinsider.com/aiming-exascale-at-black-holes-technology-org/

Aiming exascale at black holes - Technology Org

In 1783, John Michell, a rector in northern England, “proposed that the mass of a star could reach a point where its gravity prevented the escape of most anything, even light. The same prediction emerged from [founding IAS Faculty] Albert Einstein’s theory of general relativity. Finally, in 1968, physicist [and Member (1937) in the School of Math/Natural Sciences] John Wheeler gave such phenomena a name: black holes.”

As plasma—matter turned into ionized gas—falls into a black hole (center), energy is released through a process called accretion. This simulation, run on a Frontier supercomputer, shows the plasma temperature (yellow = hottest) during accretion. Image credit: Chris White and James Stone, Institute for Advanced Study

Despite initial skepticism that such astrophysical objects could exist, observations now estimate that there are 40 quintillion (or 40 thousand million billion) black holes in the universe. These black holes are important because the matter that falls into them “doesn’t just disappear quietly,” says James Stone, Professor in the School of Natural Sciences.

“Instead, matter turns into plasma, or ionized gas, as it rotates toward a black hole. The ionized particles in the plasma ‘get caught in the gravitational field of a black hole, and as they are pulled in they release energy,’ he says. That process is called accretion, and scientists think the energy released by accretion powers many processes on scales up to the entire galaxy hosting the black hole.”

To explore this process, Stone uses general relativistic radiation magnetohydrodynamics (MHD). But the equations behind MHD are “so complicated that analytic solutions — finding solutions with pencil and paper — [are] probably impossible.” Instead, by running complex simulations on high-performance computers like Polaris and Frontier, Stone and his colleagues are working to understand how radiation changes black hole accretion.

“The code created by Stone’s team to investigate black hole accretion can be applied to other astrophysical phenomena. Stone mentions that he ‘can use the same […] code for MHD simulations to follow the motion of cosmic rays,’ high-energy particles also produced by black holes.”

Source: Institute for Advanced Study

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[zytes]

I know that the average person’s opinion of AI is in a very tumultuous spot right now - partly due to misinformation and misrepresentation of how AI systems actually function, and partly because of the genuine risk of abuse that comes with powerful new technologies being thrust into the public sector before we’ve had a chance to understand the effects; and I’m not necessarily talking about generative AI and data-scraping, although I think that conversation is also important to have right now. Additionally, the blanket term of “AI” is really very insufficient and only vaguely serves to ballpark a topic which includes many diverse areas of research - many of these developments are quite beneficial for human life, such as potentially designing new antibodies or determining where cancer cells originated within a patient that presents complications. When you hear about artificial intelligence, don’t let your mind instantly gravitate towards a specific application or interpretation of the tech - you’ll miss the most important and impactful developments.

Notably, NVIDIA is holding a keynote presentation from March 18-21st to talk about their recent developments in the field of AI - a 16 minute video summarizing the “everything-so-far” detailed in that keynote can be found here - or in the full 2 hour format here. It’s very, very jargon-y, but includes information spanning a wide range of topics: healthcare, human-like robotics, “digital-twin” simulations that mirror real-world physics and allow robots to virtually train to interact and navigate particular environments — these simulated environments are built on a system called the Omniverse, and can also be displayed to Apple Vision Pro, allowing designers to interact and navigate the virtual environments as though standing within them. Notably, they’ve also created a digital sim of our entire planet for the purpose of advanced weather forecasting. It almost feels like the plot of a science-fiction novel, and seems like a great way to get more data pertinent to the effects of global warming.

It was only a few years ago that NVIDIA pivoted from being a “GPU company” to putting a focus on developing AI-forward features and technology. A few very short years; showing accelerating rates of progress. This is whenever we began seeing things like DLSS and ray-tracing/path-tracing make their way onto NVIDIA GPUs; which all use AI-driven features in some form or another. DLSS, or Deep-Learning Super Sampling, is used to generate and interpolate between frames in a game to boost framerate, performance, visual detail, etc - basically, your system only has to actually render a handful of frames and AI generates everything between those traditionally-rendered frames, freeing up resources in your system. Many game developers are making use of DLSS to essentially bypass optimization to an increasing degree; see Remnant II as a great example of this - runs beautifully on a range of machines with DLSS on, but it runs like shit on even the beefiest machines with DLSS off; though there are some wonky cloth physics, clipping issues, and objects or textures “ghosting” whenever you’re not in-motion; all seem to be a side effect of AI-generation as the effect is visible in other games which make use of DLSS or the AMD-equivalent, FSR.

Now, NVIDIA wants to redefine what the average data center consists of internally, showing how Blackwell GPUs can be combined into racks that process information at exascale speeds — which is very, very fucking fast — speeds like that have only ever actually been achieved on some 4 or 5 machines on the planet, and I think they’ve all been quantum-based machines until now; not totally certain. The first exascale computer came into existence in 2022, called Frontier, it was deemed the fastest supercomputer in existence in June 2023 - operating at some 1.19 exaFLOPS. Notably, this computer is around 7,300 sq ft in size; reminding me of the space-race era supercomputers which were entire rooms. NVIDIA’s Blackwell DGX SuperPOD consists of around 576 GPUs and operates at 11.5 exaFLOPS, and is about the size of standard row of server racks - much smaller than an entire room, but still quite large. NVIDIA is also working with AWS to produce Project Ceiba, another supercomputer consisting of some 20,000GPUs, promising 400 exaFLOPS of AI-driven computation - it doesn’t exist yet.

To make my point, things are probably only going to get weirder from here. It may feel somewhat like living in the midst of the Industrial Revolution, only with fewer years in between each new step. Advances in generative-AI are only a very, very small part of that — and many people have already begun to bury their heads in the sand as a response to this emerging technology - citing the death of authenticity and skill among artists who choose to engage with new and emerging means of creation. Interestingly, the Industrial Revolution is what gave birth to modernism, and modern art, as well as photography, and many of the concerns around the quality of art in this coming age-of-AI and in the post-industrial 1800s largely consist of the same talking points — history is a fucking circle, etc — but historians largely agree that the outcome of the Industrial Revolution was remarkably positive for art and culture; even though it took 100 years and a world war for the changes to really become really accepted among the artists of that era. The Industrial Revolution allowed art to become detached from the aristocratic class and indirectly made art accessible for people who weren’t filthy rich or affluent - new technologies and industrialization widened the horizons for new artistic movements and cultural exchanges to occur. It also allowed capitalist exploitation to ingratiate itself into the western model of society and paved the way for destructive levels of globalization, so: win some, lose some.

It isn’t a stretch to think that AI is going to touch upon nearly every existing industry and change it in some significant way, and the events that are happening right now are the basis of those sweeping changes, and it’s all clearly moving very fast - the next level of individual creative freedom is probably only a few years away. I tend to like the idea that it may soon be possible for an individual or small team to create compelling artistic works and experiences without being at the mercy of an idiot investor or a studio or a clump of illiterate shareholders who have no real interest in the development of compelling and engaging art outside of the perceived financial value that it has once it exists.

If you’re of voting age and not paying very much attention to the climate of technology, I really recommend you start keeping an eye on the news for how these advancements are altering existing industries and systems. It’s probably going to affect everyone, and we have the ability to remain uniquely informed about the world through our existing connection with technology; something the last Industrial Revolution did not have the benefit of. If anything, you should be worried about KOSA, a proposed bill you may have heard about which would limit what you can access on the internet under the guise of making the internet more “kid-friendly and safe”, but will more than likely be used to limit what information can be accessed to only pre-approved sources - limiting access to resources for LGBTQ+ and trans youth. It will be hard to stay reliably informed in a world where any system of authority or government gets to spoon-feed you their version of world events.

[deafmangoes]

Processing

SAM took a dose of green and let the calming, numbing wave flow over her overtaxed processors. Personality-Driven AIs like her were often perceived by the public as just as fast at making calculations and decisions as their sessile ancestors and unthinking cousins. They were half-right: SAM made uncountable numners of calculations a second. Exascale was the limit of her grandfather, thank you very much.

But what people didn't realise about PDAIs is how much of that got taken up in sheer bulk processing of "be human". Sure, she could turn off every sensor and essentially put her body into a coma, even suspend her own personality for a boost in computing power, but the moment PDAIs achieved true personhood, they suddenly developed the equally human fear of death. There was no way in hell you'd get her to "switch off" - because what guarantee was there that she'd ever come back?

All that to say, SAM had been waiting for fifteen minutes now for this customer to make up their mind on which brand of greasy snackburger to buy, and she was beginning to contemplate the benefits of a brief power-death.

[willcodehtmlforfood]

Gonna be a banger innit

[increasings]

What is Exascale Computing?… https://patient1.tumblr.com/post/761561652081704960?utm_source=dlvr.it&utm_medium=tumblr

[stronglys]

What is Exascale Computing?… https://patient1.tumblr.com/post/761561652081704960?utm_source=dlvr.it&utm_medium=tumblr

[patient1]

What is Exascale Computing? https://www.altdatum.com/what-is-exascale-computing/?utm_source=dlvr.it&utm_medium=tumblr

[tamanna31]

Smart Manufacturing Market Intelligence Report Offers Growth Prospects

Smart Manufacturing Industry Overview

The global smart manufacturing market was valued at USD 254.24 billion in 2022 and is anticipated to grow at a CAGR of 14.9% from 2023 to 2030.

The market is expanding at a faster rate due to factors such as rising Industry 4.0 adoption, more government engagement in supporting industrial automation, increased emphasis on industrial automation in manufacturing processes, surging demand for software systems that save time and cost, increasing supply chain complexities, and increased emphasis on regulatory compliances. COVID-19 pandemic had an impact on or induced the shutdown of all industries and elements involved in industrial automation. The global supply chains and operational logistics were suddenly affected during initial worldwide lockdown.

Gather more insights about the market drivers, restrains and growth of the Smart Manufacturing Market

The market became more focused on manufacturing essential products to survive during the pandemic as demand for non-essential products reduced. However, the market was able to grow during pandemic as enterprises needed to provide their services and products safely and quickly. The market grew during this unusual event as a direct result of demand, government financial assistance, and technical support.

Information technology and automobile industries are two most prevalent industries for industry 4.0. The market has helped automotive manufacturers build automated assembly lines not only for parts but also to manufacture the entire car. For instance, in 2021, Audi used its Production Lab (P-Lab) department to create real-life use cases for modern technology in everyday manufacturing. Industrial automation has developed an in-depth and in-demand market based solely on benefits and opportunities it offers other industries. Regardless of industry, every company or manufacturer aims to apply smart manufacturing to their processes, thus increasing the overall market.

Additionally, information technology industry is at forefront of the existence of the market and also its development. The market has grown standardized due to the widespread standardization and recent installation of internet of things (IoT). Internet of Things has normalized entry-level manufacturing, application, and execution of market technology worldwide. Information technology industry uses augmented reality, virtual reality, machine learning, artificial intelligence, and many other modern solutions to keep industry on the front foot to meet contemporary challenges and demands. For instance, in July 2021, Qualcomm began applying its advanced 5G technology to smart manufacturing by unleashing the power of IoT.

Furthermore, the industry is growing momentum in developing countries like India, Mexico, and Brazil. As developing countries are experiencing industrialization at an excessive rate, companies and industrial plants see this as an opportunity. Along with technological and logistical advancements, governments in developing countries enact laws that benefit businesses, allowing the market to thrive.

Browse through Grand View Research's Next Generation Technologies Industry Research Reports.

• The global exascale computing market size was valued at USD 3.69 billion in 2023 and is projected to grow at a CAGR of 27.8% from 2024 to 2030.

• The global observability tools and platforms market size was estimated at USD 2.71 billion in 2023 and is expected to grow at a CAGR of 10.7% from 2024 to 2030.

Key Companies & Market Share Insights

The global smart manufacturing market has a high number of small and medium-level players who are often operating for big established manufacturers. Many small-level players in the market are in the Asia Pacific region as the market is still developing here. As technology evolves, so does the specification and type of products to be manufactured, with industrial automation the process is streamlined, and the market grows alongside the evolution. The North American and European markets are dominated by large and medium-level companies in the market.

Competition in this market is high, although technological advancements are allowing companies to save time and cost while increasing their efficiency and effectiveness. Constant research and development are leading to the industry becoming more common and standard even if it requires some investment. Due to globalization, the smart manufacturing trend is present in global markets over boundaries. Seeing the growth potential, even governments are offering schemes and policies for investors to bring markets to their countries.  Some of the prominent players operating in the global smart manufacturing market include:

ABB Ltd.

Siemens

General Electric

Rockwell Automation Inc.

Schneider Electric

Honeywell International Inc.

Emerson Electric Co.

Fanuc UK Limited

Recent Developments

In April 2023, Honeywell International, Inc. acquired Compressor Controls Corporation (CCC), a provider of turbomachinery control and optimization solutions, for USD 670 million. This acquisition is expected to strengthen their presence in automation, industrial control, and process solutions. The ongoing development is expected to help industry grow exponentially in coming years.

In April 2023, ABB is expected to invest USD 170 million in the U.S. market to create highly skilled jobs in manufacturing, innovation, and distribution operations. This investment is expected to create more demand for electrification and automation products.

In April 2023, Robert Bosch GmbH partnered with Rhenus Automotive and REMONDIS subsidiary TSR Recycling, to develop Europe’s first fully automated battery-discharging plant. The plant will be a fully automated system for disassembling and discharging battery modules, which is expected to augment the industry growth further.

In June 2023, Schneider Electric partnered with ArcelorMittal Nippon Steel India for hi-tech training on smart manufacturing. The partnership also includes smart labs and training labs for NAMTECH, an education initiative by AM/NS India, which will be developed by Schneider Electric.

In May 2023, Rockwell Automation Inc. collaborated with autonox Robotics, for the expansion and invention of robot mechanics. This partnership is expected to bring Kinetix motors and drives of Rockwell along with the autonox’s robot mechanics to achieve new manufacturing possibilities.

In March 2022, Mitsubishi Electric Corporation updated their software iQ Works2 and RT Toolbox3. A new visual editor for SCADA and six-axis industrial robot programming is part of their latest update in the software. The upgrade also includes improved user-friendliness, which is expected to simplify the setup of automated applications

Order a free sample PDF of the Smart Manufacturing Market Intelligence Study, published by Grand View Research.

[jcmarchi]

UK backs smaller AI projects while scrapping major investments

New Post has been published on https://thedigitalinsider.com/uk-backs-smaller-ai-projects-while-scrapping-major-investments/

UK backs smaller AI projects while scrapping major investments

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The UK government has announced a £32 million investment in almost 100 cutting-edge AI projects across the country. However, this comes against the backdrop of a controversial decision by the new Labour government to scrap £1.3 billion in funding originally promised by the Conservatives for tech and AI initiatives.

Announced today, the £32 million will bolster 98 projects spanning a diverse range of sectors, utilising AI to boost everything from construction site safety to the efficiency of prescription deliveries. More than 200 businesses and research organisations, from Southampton to Birmingham and Northern Ireland, are set to benefit.

Rick McConnell, CEO of Dynatrace, said:

“Today’s announcement sends a clear signal that the UK is open for business and is ready to support, rather than hinder firms looking to invest in shaping our AI-driven future. These 98 projects stand out because they are focused on specific and tangible use cases that have strong potential to drive immediate value for businesses and consumers.

The early successes realised by these government-funded projects will ultimately increase confidence in AI, spurring further investments from the private sector and enhancing the UK’s reputation as a global leader in AI.”

This latest announcement is overshadowed by the Labour government’s decision to scrap a significant chunk of funding previously earmarked for major tech projects. These include £800 million for the development of a state-of-the-art exascale supercomputer at Edinburgh University and a further £500 million for AI Research Resource, which provides crucial computing power for AI research.

This is idiotic. How to consign the UK to the “tech slow lane”. Government shelves £1.3bn UK tech and AI plans – BBC News https://t.co/gDTm3fAjDL

— Chris van der Kuyl CBE (@chrisvdk) August 2, 2024

Both of the major funds were unveiled less than a year ago by the previous Conservative government. The Department for Science, Innovation and Technology (DSIT) has stated that the £1.3 billion was pledged by the former administration but was never formally allocated within its budget.

Minister for Digital Government and AI, Feryal Clark, championed the government’s commitment to AI:

“AI will deliver real change for working people across the UK – not only growing our economy but improving our public services. That’s why our support for initiatives like this will be so crucial – backing a range of projects which could reduce train delays, give us new ways of maintaining our vital infrastructure, and improve experiences for patients by making it easier to get their prescriptions to them.

We want technology to boost growth and deliver change right across the board, and I’m confident projects like these will help us realise that ambition.”

Among the projects receiving funding is V-Lab, awarded £165,006 to enhance their AI construction training software, and Nottingham-based Anteam, who will leverage AI to optimise NHS prescription deliveries.

Another notable recipient is Hack Partners, tasked with developing an autonomous system for monitoring and maintaining the UK’s rail infrastructure. Cambridge-based Monumo received £750,152 to develop advanced electric vehicle motor designs using AI.

Dr Kedar Pandya, UKRI Technology Missions Fund Senior Responsible Owner, commented:

“These projects will drive AI innovation and economic growth in a diverse range of high-growth industry sectors in all nations of the UK. They complement other investments made through the UKRI Technology Missions Fund, which are already helping to boost growth and productivity across the UK by harnessing the power of AI and other transformative technologies.”

These smaller initiatives, however, stand in stark contrast to the ambitious, large-scale projects abandoned by the Labour government. The decision to scrap the exascale supercomputer and cut funding for crucial AI research infrastructure has sparked debate about the UK’s commitment to remaining competitive.

Economic growth is only going to come from tech & AI @RachelReevesMP

Reducing investment & raising taxes pushes more entrepreneurs to the US��

The UK needs to lead in AI if we’re going to get back to growth…@UKLabour can’t be anti-techhttps://t.co/axchy885Rp

— Barney Hussey-Yeo (@Barney_H_Y) August 2, 2024

While the £32 million investment signals continued support for AI development, the shadow of the £1.3 billion funding cut looms large. The long-term impact of this decision on the UK’s ability to foster groundbreaking technological advancements remains to be seen.

“Investing in AI-driven innovation will be essential to organisations’ ability to compete on the global stage. There is no doubt that, if implemented successfully, AI has the ability to improve efficiencies, turbocharge innovation, and streamline operations across all sectors,” McConnell concludes.

(Photo by Steve Johnson)

See also: Meta’s AI strategy: Building for tomorrow, not immediate profits

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

Explore other upcoming enterprise technology events and webinars powered by TechForge here.

Tags: ai, artificial intelligence, europe, government, uk

[systemtek]

UK government scraps £1.3bn tech and AI funding plans

The UK government has decided to cancel £1.3 billion in funding for technology and artificial intelligence projects that were promised by the previous Conservative administration. This decision will affect major initiatives, including the planned exascale supercomputer at the University of Edinburgh. The Department for Science, Innovation and Technology (DSIT) confirmed that £800 million intended for the Edinburgh supercomputer and £500 million for the AI Research Resource (AIRR) will not be provided. The Labour government, which took office in July, stated that these commitments were not part of the previous government's budget plans. A DSIT spokesperson commented, "The government is making tough but necessary spending cuts across all departments due to billions of pounds in unfunded commitments. These actions are vital for restoring economic stability and advancing our national growth agenda." Despite the funding cuts, the government insists it remains dedicated to advancing technology. A DSIT spokesperson pointed to the launch of an AI Opportunities Action Plan, which aims to identify ways to strengthen compute infrastructure and support the new Industrial Strategy. However, this decision raises concerns about the UK's ability to stay competitive in global advanced computing and AI research. As other countries continue to make significant investments in these areas, the UK risks falling behind unless the funding gap is promptly addressed. Read the full article

[ericvanderburg]

UK axes plans for Edinburgh-based exascale computer

http://securitytc.com/TBWBcF

[credenceresearchdotblog]

The global demand for Supercomputer was valued at USD 12154.2 million in 2022 and is expected to reach USD 13691.6 Million in 2030, growing at a CAGR of 1.50% between 2023 and 2030.Supercomputers, the most powerful computational machines available, are designed to handle the most demanding tasks and solve the most complex problems. They are pivotal in fields such as scientific research, climate modeling, cryptography, and more. The supercomputer market is evolving rapidly, driven by advancements in technology, increasing demand for high-performance computing (HPC), and the need for sophisticated data analysis. This article delves into the current state of the supercomputer market, key trends, and future prospects.

Browse the full report at https://www.credenceresearch.com/report/supercomputer-market

Market Overview

The supercomputer market is experiencing significant growth. According to market research, the global supercomputer market was valued at approximately $5.8 billion in 2022 and is projected to reach $10.5 billion by 2028, growing at a compound annual growth rate (CAGR) of 10.2% during the forecast period. This growth is fueled by increasing investments in HPC infrastructure by governments, research institutions, and private enterprises.

Key Drivers

1. Scientific Research and Innovation: Supercomputers are indispensable in scientific research, enabling simulations and models that would be impossible with conventional computers. Fields such as physics, chemistry, biology, and astronomy rely on supercomputers to perform complex calculations and data analysis.

2. Climate Modeling and Weather Forecasting: Supercomputers play a crucial role in predicting weather patterns and studying climate change. Their ability to process vast amounts of data and run detailed simulations helps scientists understand and predict environmental changes.

3. Healthcare and Genomics: In the healthcare sector, supercomputers are used for genomic sequencing, drug discovery, and personalized medicine. They accelerate the process of analyzing genetic data, leading to faster and more accurate diagnoses and treatments.

4. Artificial Intelligence (AI) and Machine Learning: The rise of AI and machine learning applications has created a surge in demand for high-performance computing. Supercomputers are essential for training complex AI models and processing large datasets, driving innovation across industries.

5. Cryptography and Security: Supercomputers are vital for cryptographic applications, ensuring data security and integrity. They are used to develop and test encryption algorithms, safeguarding sensitive information in sectors like finance and defense.

Technological Advancements

Technological advancements are at the heart of the supercomputer market's growth. Innovations in processor design, interconnect technologies, and cooling systems are enhancing supercomputers' performance and efficiency. The transition to exascale computing, which involves systems capable of performing at least one exaflop (a billion billion calculations per second), represents a significant leap forward. Exascale supercomputers are expected to revolutionize numerous fields by providing unprecedented computational power.

Leading Players

Several key players dominate the supercomputer market, including:

- IBM: Known for its powerful systems like Summit and Sierra, IBM continues to be a leader in supercomputing innovation. - Cray (a subsidiary of Hewlett Packard Enterprise)**: Cray's systems, such as the Cray XC and CS series, are widely used in scientific research and defense. - Fujitsu: Fujitsu's Fugaku, developed in collaboration with RIKEN, has been recognized as one of the most powerful supercomputers globally. - NVIDIA: With its GPU technology, NVIDIA is a critical player in the HPC market, powering many of the world's fastest supercomputers.

Regional Insights

North America holds a significant share of the supercomputer market, driven by substantial investments in research and development and the presence of leading technology companies. Asia-Pacific is also witnessing rapid growth, with countries like China and Japan making significant strides in supercomputing capabilities. Europe's market is expanding due to increased funding for scientific research and technological innovation.

Future Prospects

The future of the supercomputer market looks promising. The ongoing development of quantum computing holds the potential to transform the landscape, offering even greater computational power and efficiency. Additionally, the integration of AI and machine learning with supercomputing will continue to drive advancements in various sectors.

Key Players

Nvidia (Japan)

NEC Corporation (Japan)

Lenovo (China)

Intel (US)

IBM (US)

HPE (US)

Fujitsu (Japan)

Dwave

Honeywell (Canada)

SpaceX

Dell (US)

CISCO (US)

Atos (France)

Advanced Micro Devices (US)

Segmentation

By High-Performance Computing (HPC) Systems:

On-Premises Supercomputers

Cloud-Based HPC

By Processor Architectures:

x86 Architecture

GPU Accelerated

Custom Architectures

By End-User Segments:

Research and Academic Institutions

Government and Defense

Commercial Entities

By Application Areas:

Scientific Research

Artificial Intelligence (AI) and Machine Learning (ML)

Weather Forecasting

Life Sciences

By Supercomputer Vendors:

Cray (now part of HPE)

IBM

NVIDIA

AMD

By Interconnect Technologies:

InfiniBand

Ethernet

Others

By Energy Efficiency:

Green Computing

By Exascale Computing:

Race to Exascale

By Partnerships and Collaborations:

Public-Private Partnerships

By Region

North America

The U.S.

Canada

Mexico

Europe

Germany

France

The U.K.

Italy

Spain

Rest of Europe

Asia Pacific

China

Japan

India

South Korea

South-east Asia

Rest of Asia Pacific

Latin America

Brazil

Argentina

Rest of Latin America

Middle East & Africa

GCC Countries

South Africa

Rest of Middle East and Africa

Browse the full report at https://www.credenceresearch.com/report/supercomputer-market

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Contact:

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[increasings]

What is Exascale Computing?… https://patient1.tumblr.com/post/761561648531210240?utm_source=dlvr.it&utm_medium=tumblr