Building on the success of previous editions, the seventh installment of the Costa Rica High Performance Computing School (CRHPCS) aims at preparing students and researchers to introduce HPC tools in their workflows. A selected team of international experts taught sessions on shared-memory programming, distributed-memory programming, accelerator programming, and high performance computing.  This edition had instructors Alessandro Marani and Nitin Shukla from CINECA, which greatly helped in bringing a vibrant environment to the sessions.

Bernd Mohr, from Jülich Supercomputing Centre, was the Keynote Speaker of this year’s edition of the event.  A well-known figure in the HPC community at large, Bernd presented the talk Parallel Performance Analysis at Scale: From Single Node to one Million HPC Cores. In an amazing voyage through different architecture setups, Bernd highlighted the importance and challenges of performance analysis.

For Esteban Meneses, Costa Rica HPC School General Chair, the School is a key element in building a stronger and more connected HPC community in the region. This year, thanks to the RISC2 project, we were able to gather participants from Guatemala, El Salvador, and Colombia. Creating these ties is fundamental for later developing more complex initiatives. We aim at preparing future scientists that will develop groundbreaking computer applications that tackle the most pressing problems of our region.

More information here. 

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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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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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This event, which aimed at preparing students and researchers to introduce HPC tools in their workflows, discussed topics such as Shared-Memory Programming, Distributed-Memory Programming, and High Performance Computing. Rui Oliveira, from INESC TEC, was the Keynote Speaker of this year’s edition of the event.  During his talk, Rui gave a historical perspective of HPC in Europe and Portugal, emphasizing the design and main considerations of the upcoming  Deucalion supercomputer at Minho Advanced Computing Center.

For Esteban Meneses, Costa Rica HPC School General Chair, the event is of strategic importance for the Central American region. As developing countries aim at catching up with European peers in the use of HPC for science and technology, having training resources is fundamental. An in-person event is also a fantastic opportunity for networking and building up truly interdisciplinary research teams.

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