“The RISC2 project has proven to be a team effort in which European and Latin American partners worked together to drive HPC collaboration forward. We have been able to create a lively and active community across the Atlantic to stimulate dialogue and boost cooperation that won’t die with RISC2’s formal end”, says Fabrizio Gagliardi, manager director of RISC2.

Since 2021, this knowledge-sharing network has organised webinars, summer schools, meetings with policymakers and participated in conferences and dissemination events on both sides of the Atlantic. The project also resulted in the HPC Observatory Repository — a collection of documents and training materials produced as part of the project – and the White Paper on HPC R&I Collaboration Opportunities, a document that reviews the key socio-economic and environmental factors and trends that influence HPC needs.

These were two of the issues highlighted by European Commission officials and experts during the final evaluation of the project, which could provide continuity to the work carried out by the consortium over the last three years, in line with the wishes of the partners and the advice of the evaluators. “Beyond RISC2, we should keep the momentum and leverage the importance of Latin America in the frame of the Green Deal actions: HPC stakeholders should encourage policymakers to build bilateral agreements and offer open calls focused on HPC collaboration“, reflects Fabrizio Gagliardi.

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The session began with a welcome and introduction by Mateo Valero (BSC), one of the main drivers of this cooperation and a leading name in the field of HPC. This intervention was later complemented by Fabrizio Gagliardi (BSC). Afterward, Elsa Carvalho (INESC TEC) presented the work done in terms of communication by the RISC2 team, an important segment for all the news and achievements to reach all the partners and countries involved.

Carlos J. Barrios Hernandez then presented the work done within the HPC Observatory, a relevant source of information that European and Latin American research organizations can address with HPC and/or AI issues.

The session closed with an important and pertinent debate on how to strengthen cooperation in HPC between the European Union and Latin America, in which all participants contributed and gave their opinion, committing to efforts so that the work developed within the framework of RISC2 is continued.

What our partners had to say about the meeting?

Rafael Mayo Garcia, CIEMAT:

“The policy event organized by RISC2 in Brussels was of utmost importance for the development of HPC and digital capabilities for a shared infrastructure between EU and LAC. Even more, it has had crucial contributions to international entities such as CYTED, the Ibero-American Programme for the Development of Science and Technology. On the CIEMAT side, it has been a new step beyond for building and participating in a HPC shared ecosystem.”

Esteban Meneses, CeNAT:

“In Costa Rica, CeNAT plays a critical role in fostering technological change. To achieve that goal, it is fundamental to synchronize our efforts with other key players, particularly government institutions. The event policy in Brussels was a great opportunity to get closer to our science and technology ministry and start a dialogue on the importance of HPC, data science, and artificial intelligence for bringing about the societal changes we aim for.”

Esteban Mocskos, UBA:

“The Policy Event recently held in Brussels and organized by the RISC2 project had several remarkable points. The gathering of experts in HPC research and management in Latin America and Europe served to plan the next steps in the joint endeavor to deepen the collaboration in this field. The advance in management policies, application optimization, and user engagement are fundamental topics treated during the main sessions and also during the point-to-point talks in every corner of the meeting room.
I can say that this meeting will also spawn different paths in these collaboration efforts that we’ll surely see their results during the following years with a positive impact on both sides of this fruitful relationship: Latin America and Europe.”

Sergio Nesmachnow, Universidad de la República:

“The National Supercomputing Center (Uruguay) and Universidad de la República have led the development of HPC strategies and technologies and their application to relevant problems in Uruguay. Specific meetings such as the policy event organized by RISC2 in Brussels are key to present and disseminate the current developments and achievements to relevant political and technological leaders in our country, so that they gain knowledge about the usefulness of HPC technologies and infrastructure to foster the development of national scientific research in capital areas such as sustainability, energy, and social development. It was very important to present the network of collaborators in Latin America and Europe and to show the involvement of institutional and government agencies.

Within the contacts and talks during the organization of the meeting, we introduced the projecto to national authorities, including the National Director of Science and Technology, Ministry of Education and Culture, and the President of the National Agency for Research and Innovation, as well as the Uruguayan Agency for International Cooperation and academic authorities from all institutions involved in the National Supercomputing Center initiative. We hope the established contacts can result in productive joint efforts to foster the development of HPC and related scientific areas in our country and the region.”

Carla Osthoff, LNCC:

“In Brazil, LNCC is critical in providing High Performance Computing Resources for the Research Community and training Human Resources and fostering new technologies. The policy event organized by RISC2 in Brussels was fundamental to synchronizing LNCC efforts with other government institutions and international  entities. On the LNCC side, it has been a new step beyond building and participating in an HPC-shared ecosystem.

Specific meetings such as the policy event organized by RISC2 in Brussels  were very important to present the network of collaborators in Latin America and Europe and to show the involvement of institutional and government agencies.

As a result of joint activities in research and development in the areas of information and communication technologies (ICT), artificial intelligence, applied mathematics, and computational modelling, with emphasis on the areas of scientific computing and data science, a Memorandum of Understanding (MoU) have been signed between LNCC and Inria/France. As a  result of new joint activities, LNCC and INESC TEC/Portugal are starting  collaboration through INESC TEC International Visiting Researcher Programme 2023.”

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As the coordinator of the High Performance Computing Center (Nacad) at COPPE/UFRJ, Alvaro Coutinho, presented advances in AI in Engineering and the importance of multidisciplinary research networks to address current issues in Scientific Machine Learning. Alvaro took the opportunity to highlight the need for Brazil to invest in high performance computing capacity.

The country’s sovereignty needs autonomy in producing ML advances, which depends on HPC support at the Universities and Research Centers. Brazil has nine machines in the Top 500 list of the most powerful computer systems in the world, but almost all at Petrobras company, and Universities need much more. ML is well-known to require HPC, when combined to scientific computer simulations it becomes essential.

The conventional notion of ML involves training an algorithm to automatically discover patterns, signals, or structures that may be hidden in huge databases and whose exact nature is unknown and therefore cannot be explicitly programmed. This field may face two major drawbacks: the need for a significant volume of (labelled) expensive to acquire data and limitations for extrapolating (making predictions beyond scenarios contained in the trained data difficult).

Considering that an algorithm’s predictive ability is a learning skill, current challenges must be addressed to improve the analytical and predictive capacity of Scientific ML algorithms, for example, to maximize its impact in applications of renewable energy. References [1-5] illustrate recent advances in Scientific Machine Learning in different areas of engineering and computer science.

References:

[*] https://www.coppe.ufrj.br/pt-br/planeta-coppe-noticias/noticias/coppe-e-sociedade-especialistas-debatem-os-reflexos-da-inteligencia

[1] Baker, Nathan, Steven L. Brunton, J. Nathan Kutz, Krithika Manohar, Aleksandr Y. Aravkin, Kristi Morgansen, Jennifer Klemisch, Nicholas Goebel, James Buttrick, Jeffrey Poskin, Agnes Blom-Schieber, Thomas Hogan, Darren McDonaldAlexander, Frank, Bremer, Timo, Hagberg, Aric, Kevrekidis, Yannis, Najm, Habib, Parashar, Manish, Patra, Abani, Sethian, James, Wild, Stefan, Willcox, Karen, and Lee, Steven. Workshop Report on Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial Intelligence. United States: N. p., 2019. Web. doi:10.2172/1478744.

[2] Brunton, Steven L., Bernd R. Noack, and Petros Koumoutsakos. “Machine learning for fluid mechanics.” Annual Review of Fluid Mechanics 52 (2020): 477-508.

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Several factors contributed to the catastrophic outcomes of the Black Death. The crises was boosted by the lack of two important components: knowledge and technology. There was no clue about the spread dynamics of the disease, and containment policies were desperately based on assumptions or beliefs. Some opted for self-isolation to get away from the “bad air” that was believed to be the cause of the illness [2]. Others thought the plague was a divine punishment and persecuted the heretics in order to “appease the heavens” [3]. Though the first of these two strategies was actually very effective, the second one only increased the tragedy of that scenario. 

The bubonic plague of the 14th century is a great example of how unfortunate ignorance can be in the context of epidemics. If the transmission mechanisms are not well-understood, we are not able to design productive measures against them. We may end up −such as our medieval predecessors− making things much more worse. Fortunately, the advances in science and technology have provided humanity with powerful tools to comprehend infectious diseases and rapidly develop response plans. In this particular matter, epidemic models and simulations have become crucial. 

In the recent COVID-19 events, many public health authorities relied on the outcomes of models, so as to determine the most probable paths of the epidemic and make informed decisions regarding sanitary measures [4]. Epidemic models have been around for a long time, and have become more and more sophisticated. One reason is the fact that they feed on data that has to be collected and processed, and which has increased in quantity and variety.  

Data contains interesting patterns that give hints about the influence of apparently non-epidemiological factors such as mobility and interaction type [5]. This is how, in the 19th century, John Snow managed to discover the cause of a cholera epidemic in Soho. He plotted the registered cholera cases in a map and saw they clustered around a water pump that he presumed was contaminated [6]. Thanks to Dr. Snow’s findings, water quality started to be considered as an important component of public health. 

As models grow in intricacy, the demand for more powerful computing systems also increases. In advanced approaches such as agent-based [7] and network (graph) models [8], every person is represented inside a complex framework in which the infection spreads according to specific rules. These rules could be related to the nature of the relations between individuals, their number of contacts, the places they visit, disease characteristics, and even stochastic influences. Frameworks are commonly composed of millions of individuals too, because we often want to analyze countrywide effects. 

In brief, to unravel epidemic dynamics we need to process and produce a lot of accurate information, and we need to do it fast. High-performance computing (HPC) systems provide high-spec hardware and support advanced techniques such as parallel computing, which accelerate calculation by using several resources at a time to perform one or different tasks concurrently. This is an advantage for stochastic epidemic models that require hundreds of independent executions to deliver reliable outputs. Frameworks with millions of nodes or agents need several GB of memory to be processed, which is a requirement that can be met only by HPC systems. 

Based on the work of Cruz et al. [9], we developed a model that represents the spread dynamics of COVID-19 in Costa Rica [10]. This model consists of a contact network of five million nodes, in which every Costa Rican citizen has a family, school, work, or random connection with their neighbors. These relations impact the probability of getting infected, as well as the “infection status” of the neighbors. The infection status varies with time, as people evolve from not having symptoms to have mild, severe, or critical conditions. People may be asymptomatic as well. The model also addresses variations in location, school and workplace sizes, age, mobility, and vaccination rates. In addition, some of these inputs are stochastic. 

Such model takes only a few hours to be simulated in an HPC cluster, when normal systems would require much more time. We managed to evaluate scenarios in which different sanitary measures were changed or eliminated. This analysis brought interesting results, such as that going to a meeting with our family or friends could be as harmful as attending a concert with dozens of strangers, in terms of the additional infections that these activities would generate. Such findings are valuable inputs for health authorities, because they demonstrate that preventing certain behaviors in the population can delay the peak of infections and give them more time to save lives. 

Even though HPC has been fundamental in computational epidemiology to give key insights into epidemic dynamics, we still have to leverage this technology in some contexts. For example, we must first strengthen health and information systems in developing countries to get the maximum advantage of HPC and epidemic models. The above can be achieved through inter–institutional and international collaboration, but also through national policies that support research and development. If we encourage the study of infectious diseases, we benefit from this knowledge in a way that we can approach other pandemics better in the future. 

References

[1] Encyclopedia Britannica. n.d. Crisis, recovery, and resilience: Did the Middle Ages end?. [online] Available at: <https://www.britannica.com/topic/history-of-Europe/Crisis-recovery-and-resilience-Did-the-Middle-Ages-end> [Accessed 13 September 2022]. 

[2] Mellinger, J., 2006. Fourteenth-Century England, Medical Ethics, and the Plague. AMA Journal of Ethics, 8(4), pp.256-260. 

[3] Carr, H., 2020. Black Death Quarantine: How Did We Try To Contain The Deadly Disease?. [online] Historyextra.com. Available at: <https://www.historyextra.com/period/medieval/plague-black-death-quarantine-history-how-stop-spread/> [Accessed 13 September 2022]. 

[4] McBryde, E., Meehan, M., Adegboye, O., Adekunle, A., Caldwell, J., Pak, A., Rojas, D., Williams, B. and Trauer, J., 2020. Role of modelling in COVID-19 policy development. Paediatric Respiratory Reviews, 35, pp.57-60. 

[5] Pasha, D., Lundeen, A., Yeasmin, D. and Pasha, M., 2021. An analysis to identify the important variables for the spread of COVID-19 using numerical techniques and data science. Case Studies in Chemical and Environmental Engineering, 3, p.100067. 

[6] Bbc.co.uk. 2014. Historic Figures: John Snow (1813 – 1858). [online] Available at: <https://www.bbc.co.uk/history/historic_figures/snow_john.shtml> [Accessed 13 September 2022]. 

[7] Publichealth.columbia.edu. 2022. Agent-Based Modeling. [online] Available at: <https://www.publichealth.columbia.edu/research/population-health-methods/agent-based-modeling> [Accessed 13 September 2022]. 

[8] Keeling, M. and Eames, K., 2005. Networks and epidemic models. Journal of The Royal Society Interface, 2(4), pp.295-307. 

[9] Cruz, E., Maciel, J., Clozato, C., Serpa, M., Navaux, P., Meneses, E., Abdalah, M. and Diener, M., 2021. Simulation-based evaluation of school reopening strategies during COVID-19: A case study of São Paulo, Brazil. Epidemiology and Infection, 149. 

[10] Abdalah, M., Soto, C., Arce, M., Cruz, E., Maciel, J., Clozato, C. and Meneses, E., 2022. Understanding COVID-19 Epidemic in Costa Rica Through Network-Based Modeling. Communications in Computer and Information Science, pp.61-75. 

By CeNAT

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RISC2 was responsible for the organization of the “HPC and Data Sciences meet Scientific Computing” workshop, on September 26, which gathered 15 participants. This workshop discussed different topics, such as Scientific Machine Learning, High Performance Scientific Computing, and Data Science. Álvaro Coutinho, Marta Mattoso (from COPPE/Federal University of Rio de Janeiro), Frédéric Valentin (from the National Laboratory for Scientific Computing), Luc Giraud, Stéphane Lanteri, and Patrick Valduriez (from Inria) were the organizers of the workshop.

RISC2 also organized a tutorial about physics-informed neural networks. Our partners from Brazil, Álvaro Coutinho and Romulo Montalvão, from the Federal University of Rio de Janeiro, António Tadeu Gomes and Frédéric Valentin, from the National Laboratory for Scientific Computing, were the instructors of the session.

Our partners Carlos Barrios, from the Universidad Industrial de Santander, was one of the General Chairs of the Conference. “With 130 participants from all over the world, CARLA 2022 was a space of “rediscover” (to rediscover us) after two years in virtual mode. More than the scientific tracks and the panels, CARLA 2022 allowed us to discuss the challenges and the strengthening of collaboration between the partners (old and new)”, says Carlos Barrios.

Various RISC2 members also gave different presentations. Alba Cervera-Lierta, from the Barcelona Supercomputing Center, was one of the Keynote Speakers of the CARLA Conference, with a presentation about Quantum Computing. Esteban Meneses, from CeNAT, participated in a presentation about “Implementing a GPU-Portable Field-Line Tracing Application with OpenMP Offload”. Pablo Mininni, from the University of Buenos Aires, was responsible for one of the invited talks about “Multi-level parallelisation of computational fluid dynamics codes using CUDA, MPI and OpenMP.”

CARLA is an international conference that provides a forum to foste the growth and strength of the HPC community in Latin America through the exchange and dissemination of new ideas, techniques, and research in HPC and its application areas.

Also during the conference, the RISC2 members had a networking meeting with the SCALAC members, reinforcing the partnership with the SCALAC network.

About CARLA 2022:

“CARLA 2022 was a space of “rediscover” (to rediscover us) after two years in virtual mode. More than the scientific tracks and the panels, CARLA 2022 allowed us to discuss the challenges and the strengthening of collaboration between the partners (old and new)”.

Carlos Barrios Hernandez,  Universidad Industrial de Santander

“Having the RISC2 project supporting a networking dinner in CARLA was crucial in building up the next research collaboration we want to have in the region. I am thoroughly satisfied with the experience of connecting with European and Latin American peers”.

Esteban Meneses, CeNAT

“Among the most important elements, I can highlight the quality and variety of paper presented. This indicates to me that the Latin American HPC community is growing and getting stronger. In addition, I was able to notice efforts to generate relations between Europe and Latin America through the RISC2 project”.

Elvis Rojas Ramírez, CeNAT

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The RISC2 project supported the participation of five Latin American students, boosting the exchange of experience and knowledge between Europe and Latin America on the HPC fields. After the Summer School, the students whose participation supported by RISC2 wrote on a blog post: “We have brought home a new vision of the world of computing, new contacts, and many new perspectives that we can apply in our studies and share with our colleagues in the research groups and, perhaps, start a new foci of study”.

Distinguished scientists in the HPC field gave lectures and tutorials addressing architecture, software stack and applications for HPC and AI, invited talks, a panel on The Future of HPC and a final keynote by Prof Mateo Valero. On the last day of the week, the ACM School merged with MATEO2022 (“Multicore Architectures and Their Effective Operation 2022”), attended by world-class experts in computer architecture in the HPC field.

The ACM Europe Summer School joined 50 participants, from 28 different countries, from young computer science researchers and engineers, outstanding MSC students, and senior undergraduate students.

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The BCS-CNS hosted the ACM Summer School 2022. From 29 August to 2 September 2022, students, researchers, and professors from all over the world gathered to discuss High-Performance Computing (HPC), Artificial Intelligence (AI) and Machine Learning.

The RISC2 project supported the participation of Latin American students. We had the opportunity to travel from Argentina, Brazil, Chile, Colombia, and Costa Rica to connect with leading researchers in HPC at the ACM Summer School and boost our professional careers. For some of us, it was our first time in Europe. For others, it was the first time we had the chance to visit a research centre that hosts a TOP500 supercomputer such as Mare Nostrum. We shared our latent curiosity to learn, meet, and relate to people from all over the world.

We were welcomed to the ACM School by a legend in the world of HPC, Professor Mateo Valero, director of the BSC. World-class lecturers and researchers introduced us to topics that we had only read about in scientific articles, like specialized processors for machine learning, neuromorphic engineering, technical software development for new architectures, and vector accelerators. We could delve into the state-of-the-art of many lines of study, opening our minds in countless ways. We faced new challenges and found new perspectives that would allow us to advance our research projects and complete our graduate degrees.

Throughout the week, we met colleagues from all over the world with different lines of research, projects, and fields of study. This opportunity allowed us to create new relationships, nurtured us at a cultural level, and built new ties of friendship and possible professional contributions in the future, connecting Europe with Latin America. Likewise, we strengthened relations between Latin Americans, usually separated despite being neighbours. Conversations that initially arose with academic topics ended with more trivial issues, all accompanied by a cup of coffee or even a mate brought directly from Argentina. These conversations go hand in hand with great minds and unique people.

Professors like Valerie Taylor from the Argonne National Laboratory, Charlotte Frenkel from the Delft University of Technology, Luca Benini from the Università di Bologna and ETHZ, and Jordi Torres from Universitat Politècnica de Catalunya, among many others, allowed us to be part of a world that, in many cases, is hard to reach for many students in Latin America. Thanks to the RISC2 project, we had the opportunity to be part of this process, learn and bring back to our countries the knowledge about state of the art in HPC architectural trends and a new vision of the world of computing.

At the end of an intense week of study and conversations, of new knowledge and new friends, we returned to our countries of origin. Together, we have brought a new vision of the world of computing, new contacts, and many new perspectives that we can apply in our studies and share with our colleagues in the research groups and, perhaps, start new foci of study.

Finally, we hope to return and meet again, make new friends, share the knowledge acquired and our experiences, and further deepen the ties within Latin America and between Europe and Latin America. We hope that other fellow Latin Americans will also benefit from similar opportunities and that they can live these kinds of experiences. The RISC2 project gave us a unique opportunity, so we want to thank them and all of those who made it possible.

By:

• Claudio Aracena, University of Chile
• Christian Asch, CeNAT, Costa Rica
• Luis Alejandro Torres Niño, UIS, Colombia
• Matías Mazzanti, UBA, Argentina
• Matheus Borges Seidel, UFRJ, Brazil

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Date: September 22, 2022 | 4 p.m. (UTC+1)

Speaker’s presentation is available here.

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The RISC2 consortium presented the work done so far, demonstrating achievements, and outputs, such as the creation of a strong collaborative network between the European and the Latin American research and industrial communities on advanced HPC application development, the HPC Observatory, the promotion of science, technology, and innovation to overcome different challenges, the project website and the White Paper, among other.

The European Commission was represented by Josiane Xavier Parreira, Laura Tosoratto and Lidia Yamamoto. The reviewers recognized and acknowledged the work done so far and provided advice and suggestions for future improvement. Official result of the review will be available in about one month.

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Mexico has a solid tradition in scientific research and education and has excellent human resources in the computer science field. Participants focused on promoting cooperation between supercomputing centers across the country. With that aim, they focused on the need to improve connectivity and engage on networks that allow for efficient and effective coordination among centers.

Leveraging from other cooperation-focused initiatives, like the Red Española de Supercomputación (RES) in Spain and PRACE at the European level, the Mexican HPC community is seeking to kick-off a nationwide collaboration network.

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