This article provides a comprehensive introduction to the use guidelines for high-performance computing resources in Japan, providing valuable reference information for companies interested in entering the Japanese market. The article explores Japan’s major supercomputer facilities in detail, including Fugaku, ABCI, and Earth Simulator, and explains in depth their application processes, fee structures, and typical application cases. In addition, this guide also provides practical strategies for overseas companies, covering key issues such as resource selection, cooperation channels, and legal compliance.

Overview of Japan’s high-performance computing resources

Japan has always been at the forefront of the world in the field of high-performance computing and has multiple world-class supercomputer systems. These advanced computing resources not only support Japan’s scientific research, but also provide strong technical support for corporate innovation. This section will introduce in detail the five major high-performance computing resources in Japan. Each of them has its own characteristics and provides powerful computing capabilities for research and applications in different fields.

1.1 Fugaku supercomputer

The Fugaku Supercomputer is Japan’s proud national computing facility, developed and operated by RIKEN. As one of the world’s top supercomputers, Fugaku has a computing power of 442 petaflops, which means it can perform 442 quadrillion floating-point operations per second. Fugaku adopts the advanced ARM processor architecture, which not only performs well in computing speed, but also takes the lead in energy efficiency.

Fugaku has an extremely wide range of applications, playing an important role from basic scientific research to industrial applications to solving social problems. During the COVID-19 epidemic, Fugaku was used to simulate the spread of the virus and the effectiveness of masks, providing scientific basis for the formulation of epidemic prevention policies. In addition, it has made significant contributions in areas such as climate change prediction, new material development, and drug design.

1.2 ABCI (AI Bridging Cloud Infrastructure)

ABCI is an artificial intelligence-dedicated supercomputer operated by Japan’s Institute of Advanced Industrial Science and Technology (AIST). It was originally designed to promote the development and application of artificial intelligence technology, especially in the fields of deep learning and big data analysis. ABCI’s computing power reaches 19.88 petaflops, and it has topped the AI ​​performance rankings many times.

ABCI is unique in that it adopts the design concept of cloud infrastructure, allowing users to access high-performance computing resources as easily as using cloud services. This design greatly lowers the threshold for enterprises and research institutions to use supercomputers, and promotes the widespread application of AI technology. ABCI has outstanding performance in fields such as autonomous driving, natural language processing, and medical image analysis.

1.3 Earth Simulator

Earth Simulator is a supercomputer operated by the Japan Marine Exploration Agency (JAMSTEC) dedicated to earth science research. Although it is no longer the fastest supercomputer in the world, it still plays an important role in the field of earth science. The latest version of Earth Simulator, ES4, went live in 2020 and has a computing power of 10 petaflops.

Earth simulators are mainly used in fields such as climate change research, earthquake prediction, and marine ecosystem simulation. Its high-precision simulation capabilities provide scientists with valuable research tools to help humans better understand and predict changes in the earth system. For companies involved in environmental science, disaster prevention and other fields, the data and models provided by the Earth Simulator have important reference value.

1.4 Kyoto University Academic Information Media Center Supercomputer System

Kyoto University’s supercomputer system is one of the most powerful computing facilities among Japanese higher education institutions. The system not only serves researchers at Kyoto University, but is also open to other academic institutions and companies. The system consists of multiple subsystems, including large-scale parallel computing systems and data-intensive computing systems, which can meet different types of computing needs.

An important feature of this system is its flexibility and diversity, enabling it to support a wide range of research areas from theoretical physics to bioinformatics. For businesses looking to collaborate with academia or conduct basic research, Kyoto University’s supercomputer systems provide an ideal platform.

1.5 Supercomputer Oakforest-PACS at the University of Tokyo Information Infrastructure Center

Oakforest-PACS is a supercomputer system jointly operated by the University of Tokyo and the University of Tsukuba and is located at the University of Tokyo Kashiwa Campus. With a peak performance of 25 petaflops, this system is one of the most powerful computing facilities in Japanese academia. Oakforest-PACS uses Intel’s Xeon Phi processor, which performs well in large-scale parallel computing.

Oakforest-PACS is mainly used to support cutting-edge research in fields such as high-energy physics, materials science, and life sciences. One of its important features is its powerful data processing capabilities, which makes it perform well in big data analysis and artificial intelligence applications. For enterprises that need to perform complex simulations or large-scale data analysis, Oakforest-PACS provides valuable computing resources.

Through these five high-performance computing resources, Japan has established a comprehensive and powerful supercomputing ecosystem. These resources not only promote the development of scientific research, but also provide strong technical support for corporate innovation. Understanding the characteristics and advantages of these resources is of great strategic significance for companies that plan to enter the Japanese market or hope to take advantage of Japan’s technological advantages.

Detailed explanation of application process

In Japan, there is a specific application process to access and use high-performance computing resources. Different supercomputer systems may have slightly different application requirements, but generally follow strict review standards. This section will analyze in detail the application process for major high-performance computing resources and provide clear guidance for enterprises and research institutions.

2.1 Fugaku Supercomputer Application Process

As Japan’s national supercomputer, Fugaku’s application process is relatively complex but very standardized. The Institute of Physics and Chemistry has established a special application system and review process for this purpose.

Applicants need to be familiar with Fugaku’s online application system. This system is a comprehensive platform that is not only used to submit applications, but also provides services such as resource usage and technical support. Applicants need to create an account in the system and fill in basic information before starting the formal application process.

Applying for the right to use Fugaku requires preparing a series of documents. Core documents include detailed research plans, resource requirements descriptions, expected results reports, etc. The research proposal should clearly state the project goals, research methods, and why Fugaku’s computing power is needed. The resource requirement description needs to detail specific requirements such as computing time and storage space. In addition, it is also necessary to provide qualification certificates of the research team, such as resumes of members, relevant past research results, etc.

Fugaku’s evaluation criteria are very strict, mainly considering the project’s scientific value, technological innovation, social impact, and actual demand for Fugaku’s computing resources. The review process is usually divided into two stages: preliminary review and review. The preliminary review mainly examines the completeness of the application materials and the basic feasibility of the project. Projects that pass the preliminary review will enter the review stage and be evaluated in depth by an expert committee. The entire review process usually takes 2-3 months.

When applying for Fugaku, there are several key points that require special attention: First, the quality of the application is crucial, and it needs to be clear, specific, and persuasive. Secondly, it is necessary to fully demonstrate the match between the project and Fugaku’s unique computing capabilities. Furthermore, if it is a corporate application, it is best to demonstrate the commercial potential and social benefits of the project. Finally, communicating with Fugaku’s technical support team in advance to understand the system’s features and limitations can greatly improve the application success rate.

2.2 ABCI usage application steps

ABCI’s application process is relatively simplified and more oriented to corporate users, but it also requires strict review.

ABCI account registration is the first step in the application. Applicants need to create an account on the ABCI official website and provide basic personal or institutional information. It is worth noting that ABCI is also open to overseas users, but additional identity verification steps may be required.

The project proposal is the core document for ABCI application. A good proposal should include a project overview, technical solutions, resource requirement estimates, expected results, etc. Especially for AI projects, it is necessary to detail the algorithms used, the size of the data set, the specific requirements for training or inference, etc. The ABCI official website provides a proposal template. Applicants should refer to it carefully and fill it in as required.

ABCI’s review process is usually faster than Fugaku’s, generally completed within 4-6 weeks. The review focuses on the technical feasibility, innovation and rational use of ABCI resources of the project. After passing the review, the applicant will need to sign a usage agreement and may be required to pay an upfront fee.

When applying for ABCI, common questions include how to estimate resource requirements, how to deal with data security issues, how to optimize code to adapt to the ABCI architecture, etc. ABCI provides detailed FAQs and technical documents, which applicants should read carefully. In addition, ABCI also holds regular user training sessions. Participating in these trainings can greatly improve the efficiency of application and use.

2.3 Comparison of application methods for other high-performance computing resources

In addition to Fugaku and ABCI, other high-performance computing resources in Japan also have their own application characteristics.

The Earth Simulator application process is more focused on earth science-related projects. Applicants are required to detail the environmental impact and scientific merit of the research. Similar to Fugaku, applications for the Earth Simulator also need to undergo rigorous expert review.

The application process for supercomputer systems at Kyoto University and the University of Tokyo is relatively simple, especially for academic users. These systems are more focused on supporting diverse research needs, so applications need to clearly demonstrate the academic value of the research. For enterprise users, it may be necessary to apply for use by working with university research teams.

The application processes of these systems have the following common characteristics:

• Both require a detailed project description and resource requirement estimate.
• The review process attaches great importance to the innovation of the project and the actual demand for computing resources.
• Applicants are encouraged to communicate with the technical support team before submitting a formal application.
• There are strict requirements for data security and intellectual property protection.

When enterprises choose which high-performance computing resources to apply for, they should carefully compare the advantages and application difficulty of different systems based on the characteristics and needs of their own projects. At the same time, it is recommended to communicate with institutions or researchers who have successfully used these resources to obtain first-hand application experience.

Fee structure and payment methods

Although the use of high-performance computing resources in Japan can greatly improve research and development efficiency, corresponding costs also need to be considered. Different supercomputer systems have unique fee structures and payment methods. This section will introduce the cost of major high-performance computing resources in detail to help users make the most appropriate choice.

3.1 Fugaku supercomputer usage fee

As the world’s top supercomputer, Fugaku’s usage fee structure is relatively complex and is mainly divided into two categories: academic research and commercial use.

For academic research, Fugaku offers preferential policies. Domestic academic institutions in Japan can obtain free or low-cost access through competitive applications. This policy aims to promote basic scientific research and technological innovation. But even if it is free to use, it still needs to pass strict project review. International academic cooperation projects may also receive similar benefits, but they need to have a Japanese research institution as the main applicant.

The pricing structure for commercial use is more clear. Fugaku’s commercial usage fees are usually calculated based on three dimensions: computing time, storage space and technical support. Specific prices will vary depending on the scale and duration of use. For example, basic compute time might be charged per core hour, while large-scale storage might be charged TB/month. Technical support fees are usually included in the base usage fee, but premium support may cost extra.

For long-term partners, Fugaku offers discount programs. This usually applies to companies or research institutions that commit to continuous use of Fugaku resources for a long period of time (such as more than one year). Discounts may increase with usage, encouraging users to more fully utilize Fugaku’s computing power. In addition, special price concessions may be available for projects that demonstrate significant social benefits or technological innovation.

3.2 ABCI billing model

ABCI’s billing model is more flexible and is mainly divided into two methods: pay-as-you-go and pre-paid to meet the needs of different users.

The pay-as-you-go model is suitable for users with unstable needs or short-term projects. In this model, users only pay for the resources they actually use. ABCI’s on-demand payment is usually billed by the hour, including GPU usage time, CPU usage time, storage space, etc. The advantage of this model is high flexibility, and users can adjust resource usage at any time according to the progress of the project. But the disadvantage is that the cost per unit time may be higher.

The prepaid package is suitable for users who use ABCI stably for a long time. Users can purchase a certain amount of computing resources in advance, usually in units of months or years. Prepaid plans often offer better prices, especially for large-scale users. ABCI offers a variety of prepaid package options, and users can choose the most suitable plan according to their needs.

For academic users, ABCI also provides special preferential policies. This includes reducing usage rates and offering a limited amount of free trial resources. Such policies aim to encourage wider adoption of AI and big data technologies in academia. However, it should be noted that even academic users need to go through project application and review to obtain these benefits.

3.3 Cost comparison of other high-performance computing resources

The cost structures of other high-performance computing resources in Japan vary, and users need to make detailed comparisons and analyzes when choosing.

Earth Simulator’s fee structure is geared toward supporting environmental science research. For directly related academic projects, significant discounts or even free access may be available. Commercial use requires full payment, and the price may be higher, but for specific environmental simulation tasks, its professional performance may bring higher cost performance.

The supercomputer systems of Kyoto University and the University of Tokyo mainly serve academic users, and there are usually significant cost discounts for on-campus users. Off-campus academic users and commercial users can also apply for use, but the fee will be relatively high. The advantage of these systems is that they may be better suited for certain types of scientific computing tasks.

When choosing the most suitable computing resources, users need to consider the following factors:

• Project Requirements: Different supercomputers may have significant advantages in handling specific types of tasks. For example, ABCI may be more efficient at AI tasks, while Earth Simulator is more specialized at environmental simulation.
• Budget constraints: Consider the overall budget of the project and choose the option that best balances performance and cost.
• Duration and frequency of use: For long-term, stable use, prepaid plans are usually more economical. For short-term or unstable needs, pay-as-you-go may be more appropriate.
• Technical support needs: Some systems offer more comprehensive technical support, which may be important for teams that lack relevant experience.
• Data security and privacy requirements: Different systems may have different policies on data processing and storage, which need to be ensured to meet the security needs of the project.
• Collaboration Opportunities: Choosing systems from certain academic institutions may lead to greater opportunities for research collaborations, which may be valuable for certain projects.

To sum up , the fee structure design of Japan’s high-performance computing resources takes into account both support for scientific research and the needs of commercial use. Users need to carefully weigh various options based on the characteristics of their own projects to find the most suitable solution. At the same time, it is recommended to maintain communication with the managers of these systems to understand the latest preferential policies and usage conditions, so as to better optimize resource usage strategies and improve investment returns.

Typical use case analysis

Japan’s high-performance computing resources play an important role in various fields, from basic scientific research to commercial applications, with impressive results. This section will use specific cases to show how these supercomputers promote technological innovation and social development.

4.1 Fugaku Supercomputer Application Case

As the world’s top supercomputer, Fugaku has an extremely wide range of applications, covering many fields from life sciences to materials science. The following are several representative application cases:

The new coronavirus research project is an outstanding application of Fugaku in the biomedical field. In the early days of the global epidemic, Japan’s RIKEN used Fugaku’s powerful computing power to conduct in-depth research on the structure and transmission mechanism of the new coronavirus. The research team used Fugaku to simulate the molecular dynamics of viral proteins to help scientists better understand the infection mechanism of the virus. At the same time, Fugaku is also used to simulate the spread of viruses in different environments, providing a scientific basis for formulating epidemic prevention policies. This project fully demonstrates the critical role of supercomputers in responding to global public health crises.

Fugaku has also played an important role in artificial intelligence drug development. A typical case is the cooperation between Japanese pharmaceutical companies and RIKEN to use Fugaku for large-scale drug screening. The research team used Fugaku to build complex protein-drug interaction models and conduct virtual screening of millions of potential compounds. This approach greatly speeds up the new drug development process, reducing work that would have taken years with traditional methods to just a few months. This not only improves the efficiency of drug development, but also significantly reduces costs.

In the field of materials science, Fugaku is used to conduct simulation studies of nanomaterials. One high-profile project involves quantum mechanical simulations of two-dimensional materials such as graphene. The researchers used Fugaku’s parallel computing capabilities to simulate large-scale systems containing tens of thousands of atoms to explore how the properties of these materials change under different conditions. These studies provide important guidance for the development of new electronic materials and energy materials and are expected to promote the development of next-generation electronic devices and renewable energy technologies.

4.2 Application of ABCI in enterprises

As a supercomputer focused on AI and big data processing, ABCI has demonstrated unique advantages in enterprise applications. The following are several typical enterprise application cases:

In the field of autonomous driving, a Japanese car manufacturer uses ABCI to train its autonomous driving AI system. The project used a large amount of real road data and simulated data, totaling more than 100PB. ABCI’s high-performance GPU clusters enable the research team to complete a training process that would have taken months or longer in a matter of weeks. This not only accelerates the development of autonomous driving technology, but also improves the safety and reliability of the system. Through ABCI, the company is able to simulate a variety of extreme and rare driving situations, greatly enhancing the adaptability of the AI ​​system.

In the field of natural language processing, a Japanese IT company developed a large-scale multi-language translation system using ABCI. The project uses a corpus of billions of sentences, covering more than 100 languages. ABCI’s large-scale distributed training capabilities enable the company to train models for multiple language pairs at the same time, greatly improving development efficiency. This project not only improves the quality of machine translation, but also lays the foundation for applications such as cross-language information retrieval and text analysis.

In finance, ABCI is used to develop highly complex risk models. A large financial institution used ABCI to build a global market risk simulation system. The system is capable of analyzing the risk of millions of financial instruments in real time and performs Monte Carlo simulations to predict potential losses in extreme market conditions. ABCI’s high-performance computing capabilities enable banks to complete risk calculations that would otherwise take hours in minutes, greatly improving the real-time and accuracy of risk management.

4.3 Application of Earth Simulator in Environmental Science

Earth Simulator plays a key role in environmental research as a supercomputer dedicated to Earth system science. The following are several important application cases:

In terms of climate change prediction, the Japan Meteorological Agency develops high-resolution global climate models using Earth Simulator. This model is capable of simulating the interactions of multiple Earth system components such as the atmosphere, oceans, land and glaciers. By running long-term climate simulations, scientists can more accurately predict climate change trends over the next few decades to a century. These predictions provide an important basis for formulating climate change adaptation and mitigation strategies.

In the field of tsunami research, Earth simulators are used to develop highly accurate tsunami simulation models. The researchers used the massive computing power of Earth Simulator to build complex models containing detailed data on seafloor topography and coastal areas. These models can simulate the generation, propagation and landfall of tsunamis triggered by earthquakes. Through these simulations, scientists can not only better understand the physical mechanisms of tsunamis, but also develop more effective disaster prevention and mitigation plans for coastal areas.

In terms of global ecosystem analysis, Earth Simulator is used to build comprehensive Earth system models. This model integrates multiple factors such as the atmosphere, oceans, terrestrial ecosystems and human activities. Researchers use this model to study complex issues such as the global carbon cycle, biodiversity changes, and the impact of land use changes on climate. These studies provide important insights into understanding the impact of human activities on global ecosystems and provide scientific basis for formulating sustainable development strategies.

These cases fully demonstrate the important role of Japan’s high-performance computing resources in promoting scientific research, technological innovation and social development. From responding to global challenges such as the COVID-19 pandemic and climate change to promoting cutting-edge technologies such as artificial intelligence and the development of new materials, supercomputers have become an indispensable tool for modern scientific research and innovation. As these systems continue to be upgraded and their application scope expanded, we can expect to see more breakthrough research results and innovative applications.

High-performance computing resource usage strategies for overseas enterprises

Chinese companies doing business in Japan, especially those involved in big data analysis, artificial intelligence development or complex scientific computing, may need to take advantage of Japan’s high-performance computing resources. This section will explore in detail how these companies can effectively utilize these resources and avoid potential risks.

5.1 How to choose suitable high-performance computing resources

Choosing the right high-performance computing resources is key to business success. First, companies need to identify their computing needs. Different task types may be more suitable for different computing systems. For example, companies that need to conduct large-scale AI training may be more suitable to choose ABCI, while companies that need to conduct complex scientific simulations may be more inclined to choose Fugaku or Earth Simulator.

Businesses need to consider resource availability and usage costs. Some systems may require applications far in advance, while others may offer more flexible immediate access options. In terms of cost, the billing models of different systems may vary greatly, and enterprises need to choose the most economical solution based on their own budget and usage patterns. Additionally, businesses need to consider the availability of technical support and training resources. Some systems may offer more comprehensive technical support and training courses, which may be an important consideration for teams that lack relevant experience. Enterprises should also consider the possibility of establishing long-term relationships with these computing resource providers. This may not only bring more favorable conditions of use, but may also open up new R&D cooperation opportunities for enterprises.

5.2 Ways to cooperate with local research institutions in Japan

Cooperating with local research institutions in Japan can bring many benefits to enterprises, including easier access to high-performance computing resources, preferential policies, and valuable technical support. Companies can consider establishing industry-university partnerships with Japanese universities or research institutes. Many Japanese universities have dedicated industry-academic cooperation offices responsible for coordinating cooperation between industry and academia. Through such collaborations, companies may gain access to university supercomputers while drawing on the expertise of academia to solve technical challenges. You can also participate in industry alliances or research projects organized by the Japanese government or research institutions. For example, the RIKEN Institute of Science and Technology often organizes collaborative projects for industry, which provides companies with access to advanced computing resources. In addition, companies can also consider setting up R&D centers or branches in Japan, which can better integrate into the local scientific research ecosystem and make it easier to establish long-term cooperative relationships.

5.3 Legal and compliance considerations for the use of high-performance computing resources

When using high-performance computing resources in Japan, companies need to pay attention to complying with relevant laws, regulations and compliance requirements. Businesses need to understand Japan’s regulations regarding cross-border transfers of data. Japan’s Personal Information Protection Act has strict regulations on the processing and transfer of personal data, and companies need to pay special attention when using these computing resources to process data involving personal information. Enterprises need to pay attention to intellectual property protection issues. When using these computing resources to conduct research and development activities, new intellectual property may be generated. Enterprises need to clarify the ownership and use rights of intellectual property rights with resource providers in advance. Some high-performance computing resources may involve export-controlled sensitive technologies. Companies need to ensure that their use does not violate Japanese or international technology export control regulations. Enterprises also need to pay attention to the usage policies and ethical guidelines of each computing resource provider. For example, some systems may be prohibited for military use or other specific areas of research.

5.4 Data security and privacy protection measures

Protecting data security and privacy is a top priority for enterprises using high-performance computing resources.

First, companies need to understand and comply with Japan’s data protection regulations, especially the requirements of the Personal Information Protection Act. This includes obtaining the consent of the data subject, ensuring the secure storage and transmission of data, etc. Secondly, enterprises should sign detailed data processing agreements with computing resource providers to clarify the scope of data use, storage location, access rights and other issues. Some sensitive data may require special encryption or handling in a designated isolation environment. Enterprises should also establish their own data security management system, including employee training, access control, data desensitization and other measures. Regular security audits and risk assessments are also necessary. Additionally, businesses need to have emergency response plans in place to deal with possible data breaches or security incidents. This includes promptly notifying relevant parties, taking remedial measures, conducting post-mortem analysis, etc.

5.5 Talent training and technical support acquisition methods

To effectively utilize high-performance computing resources, enterprises need to cultivate relevant talents and obtain necessary technical support.

Companies can encourage employees to participate in training courses held by various universities or research institutions in Japan. Many institutions that provide high-performance computing resources organize regular user trainings, which are a good opportunity to learn about the latest technologies and best practices.

Companies can consider establishing talent exchange programs with Japanese universities or research institutes. For example, employees can be sent to these institutions for short-term study or cooperative research, or Japanese experts can be invited to the company to provide technical guidance.

In addition, companies should actively participate in Japan’s high-performance computing user community. Many systems have their own user forums or communication platforms, which are important channels for obtaining technical support and exchanging experience. For some special technical problems, companies can consider hiring Japanese technical consultants or working with professional consulting companies. These experts can provide targeted solutions and training. Enterprises should establish their own knowledge management systems to save and share experiences and best practices in using high-performance computing resources. This can help companies gradually build their own professional teams and reduce reliance on external support.

By adopting these strategies, overseas companies can more effectively utilize Japan’s high-performance computing resources, while ensuring data security and compliance while maximizing the technical and commercial value brought by computing resources. This will not only help the company’s development in the Japanese market, but also provide strong support for the company’s global technological innovation.

Future development trends of high-performance computing resources in Japan

Japan has always been a leader in the field of high-performance computing, and future development trends will continue to promote technological innovation and the expansion of application scope. This section will explore several main development directions of Japan’s high-performance computing resources, including quantum computing, green computing, the integration of edge computing and high-performance computing, and international cooperation projects.

The development and application prospects of quantum computing are one of the most exciting trends in high-performance computing in Japan. The Japanese government and business community are investing heavily in quantum computing technology, with the goal of developing practical quantum computers within the next decade. RIKEN is leading a large-scale quantum computing research project dedicated to developing superconducting qubits and optical quantum computing technology. At the same time, large companies such as Hitachi and Toshiba are also actively developing quantum computing hardware and software. These efforts are expected to bring breakthroughs in cryptography, materials science, drug discovery and other fields. For example, in the development of new drugs, quantum computing is expected to greatly accelerate the molecular simulation process, allowing researchers to screen and design new drug molecules faster. However, the practical application of quantum computing still faces many challenges, including how to maintain the stability of the quantum state and how to expand the number of qubits. In the coming years, we are likely to see the emergence of more quantum-classical hybrid computing systems, which will be an important stage in the transition to full quantum computing.

Green computing and sustainability are another important trend. As the scale and energy consumption of high-performance computing systems continue to increase, how to improve energy efficiency and reduce environmental impact has become a key issue. Japan is actively exploring various energy-saving technologies, including advanced liquid cooling systems, efficient power management technology, and the use of renewable energy to power data centers. For example, the Fugaku supercomputer was designed with special attention to energy efficiency, using advanced ARM processors and innovative cooling systems. In the future, we may see more supercomputing facilities that utilize seawater cooling or geothermal energy. In addition, software-level optimization will also play an important role in improving energy efficiency, including the development of more efficient algorithms and smarter resource scheduling systems. These efforts not only help reduce operating costs, but are also in line with the carbon neutrality goals proposed by the Japanese government.

The integration of edge computing and high-performance computing is the third trend worthy of attention. With the development of IoT and 5G technology, large amounts of data need to be processed in real time at the edge of the network. Japan is exploring how to extend high-performance computing capabilities to the edge of the network to support applications such as autonomous driving and smart manufacturing. This convergence may lead to a new paradigm of distributed high-performance computing systems, in which large supercomputers in central data centers work in conjunction with smaller high-performance computing nodes distributed throughout the country. For example, in smart city applications, edge nodes can process real-time data from various sensors, while complex model training and large-scale simulations are performed on central supercomputers. This architecture can not only improve the efficiency of data processing, but also reduce the delay and bandwidth requirements of data transmission.

International cooperation projects and opportunities are another important direction for the future development of high-performance computing in Japan. Japan is actively participating in several international cooperation projects, such as a high-performance computing cooperation agreement with the European Union and a supercomputing cooperation project with the U.S. Department of Energy. These cooperation not only involve technical exchanges, but also jointly address global challenges. For example, in climate change research, Japan’s Earth Simulator has conducted many joint simulations with climate models from other countries. In the future, we may see more cross-border joint research projects, especially in response to global challenges such as epidemic prevention, climate change, energy crisis, etc. These international collaborations can not only promote technological progress, but also promote new models of global scientific research cooperation. For Chinese companies, these international cooperation projects may provide opportunities to participate in the global high-performance computing ecosystem.

Generally speaking, the future development trend of Japan’s high-performance computing resources shows the characteristics of combining technological innovation with social needs. Quantum computing is expected to bring a qualitative leap in computing power. Green computing reflects the pursuit of sustainable development. The integration of edge computing and high-performance computing adapts to the needs of the Internet of Things era. International cooperation reflects the globalization of technological innovation. trend. These developments will not only promote Japan to maintain its leading position in the field of high-performance computing, but will also make certain contributions to global scientific and technological innovation. For companies doing business in Japan, paying close attention to these trends and actively participating in related projects will help seize new opportunities brought about by technological innovation.

Frequently Asked Questions (FAQ)

Below are some frequently asked questions and their detailed answers when using Japan’s high-performance computing resources. These questions cover various situations that may be encountered from project evaluation to actual use, and we hope to provide you with valuable guidance and reference.

Q1: How to evaluate whether a project requires the use of supercomputers?

A1: Evaluating whether a project requires the use of a supercomputer requires consideration of multiple factors, including computational complexity, time constraints, data size, accuracy requirements, and cost-effectiveness. Computational complexity is a key metric. If your project involves large-scale data processing, complex scientific simulations, or deep learning tasks, you may need the support of a supercomputer. For example, tasks such as climate simulations, genome analysis, or large-scale neural network training often require the powerful computing power of supercomputers.

Taking into account time constraints, supercomputers may be a necessary option if conventional computing equipment cannot complete the computing task within a reasonable time. For example, in drug discovery, rapid screening of large numbers of compounds may require the parallel processing power of supercomputers. Data size is also an important factor, and for projects dealing with terabytes or even petabytes of data, the parallel processing capabilities of supercomputers may be indispensable. Tasks such as big data analysis and high-resolution image processing often require the support of supercomputers.

Certain projects may require extremely high calculation accuracy, such as precise scientific calculations or complex financial models. In these cases, the high-precision floating-point capabilities of a supercomputer may be necessary. Finally, there is also cost-effectiveness to consider. While using a supercomputer may seem costly, it may be more cost-effective in the long run if it significantly shortens the project cycle or improves the quality of the results. For example, in automotive design, using supercomputers for crash simulations can significantly reduce the need for physical testing, saving time and costs.

It is recommended that you first conduct a small-scale test to evaluate the performance of conventional computing equipment. If you find that the performance is insufficient, then consider applying to use a supercomputer. At the same time, consulting experts in relevant fields or technical personnel at supercomputing centers can also help you make more accurate judgments. Remember, choosing to use a supercomputer should be based on the actual needs of the project, not just because it looks cool.

Q2: After the application is rejected, how to improve the success rate of the next application?

A2: It is common for applications to be rejected, so don’t be discouraged. To improve the application success rate, you can start from many aspects: carefully understand the reasons for rejection , carefully read the rejection notice, and understand the specific reasons. If possible, reach out to relevant people for more detailed feedback. This information is critical to improving your next application.

Improve the project description , ensure that the project description is clear and specific, and highlight the scientific value or commercial potential of the project. Use specific data and examples to support your argument. Clearly explain why your project requires supercomputer support and how the expected results will contribute to scientific advancement or social development.

It is also important to optimize resource requirements and re-evaluate computing resource requirements to ensure that the amount of resources requested is consistent with project needs. Requesting resources that are too high or too low may result in application rejection. If possible, provide preliminary results obtained using smaller-scale computing resources to demonstrate the feasibility and scalability of the project.

Consider seeking collaborations . Working with local Japanese research institutions or universities may add credibility to your application. Not only will this enhance the academic value of the project, it may also bring in additional resources and expertise.

Improve technical solutions based on feedback and demonstrate your plan for efficient use of supercomputer resources, including parallelization strategies, data management solutions, etc. This shows you’re ready to take full advantage of your high-performance computing resources.

Pay attention to the application time. Some computing resources may be easier to apply for during a specific period of time. Reasonably arranging the application time may improve the success rate. It is also a good idea to attend relevant training. Many supercomputing centers offer training courses. Participating in these courses can not only improve your technical skills, but also help you better understand the application process and evaluation criteria.

Stay patient and positive , and even if you get rejected again, stay positive and continue to optimize your application. Each application is an opportunity to learn and help improve the quality of your future applications.

Q3: How to deal with the intellectual property protection issues when using Japanese high-performance computing resources?

A3: Intellectual property protection is an important consideration when using high-performance computing resources. Here are some suggestions and considerations: Read the usage agreement carefully and understand its intellectual property terms before you start using computing resources. These terms usually stipulate attribution of research results, publication requirements, etc. If there is anything unclear, don’t hesitate to ask the resource provider directly.

It is very important to clarify ownership . Before starting the project, clearly agree with the resource provider on the ownership of intellectual property rights. Typically, research results generated using public resources are owned by the users, but the use of the resources may need to be acknowledged at the time of publication. For projects involving commercial secrets, ensure that a confidentiality agreement is signed with the resource provider.

Data security is also part of intellectual property protection , encrypting sensitive data, limiting access rights, and preventing unauthorized access. If your project involves personal information or sensitive business data, additional security measures may be required.

If the research results have potential commercial value, consider applying for patent protection in a timely manner. Patent laws in Japan may differ from those in other countries, and it is recommended to consult with legal counsel familiar with Japanese intellectual property laws to ensure that your rights and interests are fully protected. When publishing research results, comply with the citation guidelines of the resource provider and give appropriate acknowledgments. This is not only a requirement of academic ethics but may also be a clause in a usage agreement. It is also important to regularly review your IP protection strategy , as you may need to adjust protections as projects progress and regulations change. Maintain communication with legal counsel and resource providers to ensure your IP protection strategy remains effective.

Remember that intellectual property protection is an ongoing process that requires vigilance at all stages of the project. By taking these steps, you can effectively protect your intellectual property while making full use of Japan’s high-performance computing resources.

Q4: How to deal with the challenges of data transmission and storage?

A4: Handling large-scale data transfer and storage is indeed a major challenge when using high-performance computing resources. Here are some strategies and suggestions: Assess your data needs and carefully evaluate which data must be transmitted and which data can be pre-processed locally before being transmitted to reduce the amount of transmission. This not only saves transfer time but also reduces storage costs.

Using a high-speed network is key , and if possible, use a dedicated high-speed scientific research network for data transmission, such as SINET (Japanese Scientific Research Network). These networks typically offer higher bandwidth and more stable connections and are particularly suitable for large-scale data transfers.

Data compression can significantly reduce transmission time by compressing data before transmission, but there is a trade-off between compression time and transmission time. For certain types of data, such as scientific datasets, there may be specialized compression algorithms worth exploring.

Consider the incremental transmission strategy . If the data will be updated regularly, using the incremental transmission strategy to only transmit the changed parts can greatly reduce the amount of transmission. This is especially useful for long-running projects.

Choose a protocol suitable for large-scale data transfer, such as GridFTP. These protocols generally provide better performance and reliability, especially over long distances or unstable network connections.

In terms of storage, considering the data offloading strategy and distributing data to multiple storage nodes can improve read and write efficiency. At the same time, select an appropriate storage system based on data access patterns, such as using high-speed storage for frequently accessed hot data.

Develop data lifecycle management strategies, including data retention and deletion strategies, to avoid unnecessary storage overhead. Regularly cleaning out data that is no longer needed can significantly reduce storage costs. Security cannot be ignored, and encrypted transmission protocols (such as SFTP) are used to ensure the security of data transmission. Implement appropriate access controls and encryption measures for stored data.

Use data transfer and storage monitoring tools to identify and resolve issues promptly. These tools can help you optimize your transfer strategy and improve storage efficiency.

Dealing with these challenges requires a combination of technology and management , and it is recommended to work closely with technical staff at supercomputing centers, who often have extensive experience dealing with these types of problems. At the same time, as technology develops, new solutions may emerge, and it is also important to keep an eye on new technologies.

Q5: How can small and medium-sized enterprises afford the use of high-performance computing resources?

A5: For small and medium-sized enterprises, the cost of using high-performance computing resources can indeed be a challenge. However, there are several strategies that can help reduce costs and make the use of HPC resources more affordable: Be aware of and take advantage of government subsidy and support programs . The Japanese government and some local governments offer programs targeting the use of HPC resources by small and medium-sized enterprises. Subsidy projects. For example, the Ministry of Economy, Trade and Industry’s “Future Investment Promotion Subsidy” includes support for companies to use AI and high-performance computing. Paying close attention to these projects could significantly reduce cost pressures.

Consider using cloud high-performance computing services . Many cloud service providers such as Amazon AWS, Microsoft Azure and Google Cloud provide high-performance computing services. These services usually adopt a pay-as-you-go model, which can effectively reduce initial investment costs. This is a great option for businesses that don’t require constant use of high-performance computing resources.

It is also a good idea to seek academic cooperation . Cooperating with universities or research institutions can share their computing resources and obtain professional technical support. Such collaborations not only reduce costs but may also lead to new innovation opportunities.

It is important to optimize your resource usage strategy , carefully evaluate project needs, and only use high-performance computing resources when they are truly needed. By optimizing algorithms and codes, computational efficiency can be significantly improved, thereby reducing the required computing time and resources.

Consider using open source software and tools. Many high-performance computing tasks can be completed using free open source software, which can significantly reduce software licensing costs. Joining industry alliances or resource sharing platforms is also an option. Small and medium-sized enterprises in some industries may form alliances to share high-performance computing resources and thereby share costs.

Finally, don’t neglect training and upskilling. By upskilling employees, high-performance computing resources can be used more efficiently, thereby reducing overall costs. Many supercomputing centers offer free or low-cost training courses that are worth attending.

Remember, the use of high-performance computing resources should be based on clear business needs and return on investment analysis. With careful planning and innovative approaches, it is entirely possible for SMEs to affordably tap into these powerful resources and improve their competitiveness.

Q6: How to choose a high-performance computing system suitable for your project?

A6: There are several factors to consider when choosing an appropriate high-performance computing system:

Project requirements are clear, and different types of computing tasks (such as large-scale data analysis, complex simulations, machine learning, etc.) may be more suitable for systems with different architectures. Evaluate system performance indicators, paying attention to the system’s peak performance, memory bandwidth, storage capacity and other indicators to ensure that they can meet your needs.

Consider software compatibility and make sure the software and libraries you need are available on the target system or can be easily installed. In addition, system availability and usage strategies must also be considered. Some systems may have strict usage limits or long waiting queues. Don’t overlook the importance of technical support, either. Choosing a system with good technical support can help you resolve issues faster. It is recommended that you communicate with the technical staff of multiple high-performance computing centers to compare the advantages of different systems before making a choice.

Q7: How to optimize code to make full use of performance computing resources?

A7: Code optimization is the key to making full use of performance computing resources. Here are some suggestions: Understand the system architecture . Different performance computing systems may have different architectures, such as CPU, GPU or hybrid systems. Optimizing code for a specific architecture can significantly improve performance. Focus on tasks. Most high-performance computing requires sophistication. Multi-core and multi-node computing capabilities can be fully utilized using task programming models such as OpenMP and MPI.

Optimizing data access patterns, rationally using servers, and reducing data movement can maximize computing efficiency. Use appropriate compiler optimization options. Modern compilers provide many optimization options that, when used correctly, can produce more efficient code. Take advantage of performance analysis tools that can help you identify bottlenecks in your code and guide further optimization.

Q8: How to ensure data security when using high-performance computing resources?

A8: Data security is an important consideration when using high-performance computing resources. Here are some strategies to keep your data safe: Implement enhanced access controls and protect your accounts with strong passwords, two-factor authentication, and more. Encrypt sensitive data and use strong encryption algorithms to protect data during transmission and storage. Understand and comply with the data management policies, each computing center may have different data management and privacy policies, make sure you comply with and comply with these policies. Back up important data from time to time. Although high-performance computing centers usually have their own backup strategies, additional backups can provide more backup. Keep your software updated and make sure all software you use is up to date to protect against known security vulnerabilities. If your project involves particularly sensitive data, you may want to consider using a dedicated secure performance computing facility.

Q9: How to handle the scheduling and management of high-performance computing jobs?

A9: Efficient job scheduling and management are crucial for efficient use of high-performance computing resources: Be familiar with the system’s job scheduler. Common schedulers include SLURM, PBS, etc., and understand their characteristics and usage. Reasonable estimation of resource requirements and accurate estimation of job running time and resource requirements can improve scheduling efficiency. Automate and manage jobs using scripts, which can greatly improve efficiency, especially for projects that require running a large number of jobs. Monitor job status, use the tools provided by the system to regularly check job status, and handle problems that arise in a timely manner. Optimizing the job splitting strategy, for example, splitting a large job into multiple small jobs, may improve resource utilization and job turnover.

Q10: How to deal with software dependency issues in the performance calculation process?

A10: Software dependency issues are a common challenge in high-performance computing environments: use environment module systems. High -performance computing systems use module systems to manage software environments. Being familiar with this system can help you easily switch between different software versions.

Consider using container technology such as Singularity, which allows you to use preconfigured software environments in high-performance computing environments. Communicate promptly with the system administrator and request installation if the software or specific version you need is not available on the system. In addition, use a virtual environment. For languages ​​such as Python, using a virtual environment can avoid dependency conflicts in the global environment.

Finally, maintain good documentation of your documented software dependencies and environment configuration, which is important for the reproducibility of your experiments and long-term detailed maintenance. If possible, consider using a scientific workflow management tool such as Next flow or Snake make, which can help manage complex software dependencies.