Given the nature of the project, RISC2 could not fail to be represented through its partners and with a strong presence in the event’s program. Carlos J. Barrios, researcher from the Universidad Industrial de Santander and RISC2 partner was responsible for opening CARLA, with his address setting the tone for the conference, emphasizing the importance of collaborative efforts and knowledge sharing in furthering the frontiers of HPC.

Fabrizio Gagliardi, the coordinator of RISC2, also took center stage with a special talk that introduced the audience to the mission and objectives of the RISC2 project. The presentation shed light on the pivotal role that RISC2 plays in advancing HPC research and development of the cooperation between the two continents in this field. Gagliardi participated in the EuroHPCLatam panel: Policy and Global Actions, which included representatives from Red Clara, CAF and the Ministry of CyT Colombia. This panel explored the policies and global actions required to propel HPC forward in Latin America, emphasizing collaboration between key stakeholders.

Another highlight of CARLA 2023 was the tribute to Mateo Valero, one of the promoters of RISC2. Valero’s dedication and contributions to the field were celebrated through an award with his name and one he was the first recepient, underscoring the lasting impact of his work on the entire HPC community.

This event was particularly important as it coincided with the end of the RISC2 project and the presentation of its results. Over the course of three years, the initiative has strengthened contacts and promoted the exchange of knowledge between researchers from Latin America and Europe through the organization of nine webinars, the support of several schools, workshops, and other training events in the field for young students and researchers. During this period, RISC2 partners also participated in several conferences and ceremonies with policymakers to raise awareness of the importance of continuing to support and prioritize this area of research in the future.

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All the videos are available here:

Sergio Nesmachnow

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Pablo Ezzati

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Esteban Meneses

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More information

The post HPC, Data & Architecture Week first appeared on RISC2 Project.

The goal of the investigation is to provide users with simplified access to computing structures through scientific solutions that represent significant developments in their fields. In the case of this project, it is intended to develop intelligent green scientific solutions for BioinfoPortal (a multiuser Brazilian infrastructure)supported by High-Performance Computing environments.

Technologically, it includes areas such as scientific workflows, data mining, machine learning, and deep learning. The outlook, in case of success, is the analysis and interpretation of Big Data allowing new paths in molecular biology, genetics, biomedicine, and health— so it becomes necessary tools capable of digesting the amount of information, efficiently, which can come.

The team performed several large-scale bioinformatics experiments that are considered to be computationally intensive. Currently, artificial intelligence is being used to generate models to analyze computational and bioinformatics metadata to understand how automatic learning can predict computational resources efficiently. The workshop was held from April 10th to 11th, and took place in the University of Sao Paulo.

RISC2 Project, which aims to explore the HPC impact in the economies of Latin America and Europe, relies on the interaction between researchers and policymakers in both regions. It also includes 16 academic partners such as the University of Buenos Aires, National Laboratory for High Performance Computing of Chile, Julich Supercomputing Centre, Barcelona Supercomputing Center (the leader of the consortium), among others.

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Humans are particularly efficient at recognising objects – think about what surrounds us: one recognises the object where one is reading the text from as a screen, the place where one sits as a chair, the utensil in which one drinks coffee as a cup, and one does all of this extremely quickly and virtually automatically. One is able to do all this despite the fact that 1) one holds large amounts of information about each object (if one is asked to write down everything you know about a pen, you would certainly have a lot to say); and that 2) there are several exemplars of each object type (a glass can be tall, made out of glass, metal, paper or plastic, it can be different colours, etc. – but despite that, any of them would still be a glass). How does one do this? How one is able to store and process so much information in the process of recognising a glass, and generalise all the different instances of a glass to get the concept “glass”? The goal of the ContentMAP is to understand the processes that lead to successful object recognition.

The answer to these question lies in better understanding of the organisational principles of information in the brain. It is, in fact, the efficient organisation of conceptual information and object representations in the brain that allows one to quickly and efficiently recognise the keyboard that is in front of each of us. To study the neuronal organisation of object knowledge, the project collects large sets of fMRI data from several participants, and then try to decode the organisational principles of information in the brain.

Given the amount of data and the computational requirements of this type of data at the level of pre-processing and post processing, the use of HPC is essential to enable these studies to be conducted in a timely manner. For example, at the post-processing level, the project uses whole brain Support Vector Machine classification algorithms (searchlight procedures) that require hundreds of thousands of classifiers to be trained. Moreover, for each of these classifiers one needs to compute a sample distribution of the average, as well as test the various classifications of interest, and this has to be done per participant.

Because of this, the use of HPC facilities of of the Advanced Computing Laboratory (LCA) at University of Coimbra is crucial. It allows us to actually perform these analyses in one to two weeks – something that on our 14-core computers would take a few months, which in pratice would mean, most probably, that the analysis would not be done. 

By Faculty of Psychology and Educational Sciences, University of Coimbra

Reference 

ProAction Lab http://proactionlab.fpce.uc.pt/ 

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The Call for High Performance Computing (HPC) Centers aims to support the acquisition of high performance computing equipment that can provide computational infrastructure to conduct research in all areas of knowledge that are intensive in computing resources. The resources necessary for the development of the infrastructure of the facilities to receive the high performance computing equipment are considered to be the responsibility of the proponent institutions and constitute the required counterpart for the presentation of the proposal. In addition, proposers must demonstrate a proven track record as an HPC center.

This program has the nature of creating infrastructure and is not intended to provide conventional funding for research projects that will eventually take advantage of the infrastructure supported here, and the support for the realization of such research projects should be sought in the lines of funding for research.

A portion of the maintenance costs of the equipment to be purchased may be requested in this Call. However, it is expected that proposals submitted to this Call will also propose other ways to cover equipment maintenance costs. No funds may be requested to cover costs for the maintenance of the building infrastructure and support for computer equipment, such as air conditioning and the like, which should be covered by funds contributed by the proponent institutions or from other sources. Furthermore, the costs of salaries and other charges related to the support staff that this Call for Proposals foresees should be available for the operation of the center cannot be requested in the proposals submitted to this Call for Proposals and are the sole responsibility of the proposing institutions. The proponents may foresee, in their business plan, charging for the provision of the services, provided that some level of gratuity is offered to users from academic institutions.

WHO?

This Call is open to Education or Research Institutions from all over Brazil, consortium or not, to support 1 center in the state of São Paulo and 1 or 2 centers in other Brazilian states, in a total amount of up to R$ 100 million. The center based in São Paulo may receive, in this Call, resources of up to R$ 50 million, and must meet the demand for high performance computing services within the entire state of São Paulo. The centers located in other states may receive resources of up to R$ 25 million, in the case of non-consortium projects, or up to R$ 50 million in the case of a consortium of several institutions that meet the demand for high performance computing services nationwide.

This Call is launched in the scope of FAPESP’s Multiuser Equipment Program – EMU and has an infra-structural nature.

Know more about this call here. 

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The RISC2 partners which participed as keynote speakers on the event were Santiago Iturriaga, with a talk about “ClusterUY Advanced Usage Tutorial”, Esteban Mocskos, with a presentation about “Systems based on blockchain. Studying its behavior as a distributed system: from emulation to simulation”, and Sergio Nesmachnow, with a talk about “Message Passing Interface Tutorial”.

According to Esteban Mocskos, this seminar was very relevant for the RISC2 project as “it is one step to consolidate the HPC network in Latin America (damaged by COVID) and collaborate to the success of future activities”.

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On November 7, 2022, LNCC researchers, Carla Osthoff and Kary Ocaña, participated in a seminar in collaboration with our partner Inria, with a presentation entitle “Developing Efficient Scientific Gateways for Bioinformatics in Supercomputer Environments Supported by Artificial Intelligence”. The seminar aimed at promoting the interaction between LNCC’s and Inria’s high-performance computing researchers.

On November 18, Carla Osthoff participated in a seminar organized by the University of Campinas, where she presented the Santos Dumont Supercomputer. The event aimed to promote the exchange of the best HPC practices, promoting the interaction between computer science researchers towards the definition of a coordinated policy and a concrete roadmap for the future.

On November 23, Carla Osthoff also presented the Santos Dumont Supercomputer, on an online lecture, organized by the Research Centre in Digitalization and Intelligent Robotics of the Polytechnic Institute of Bragança, promoting the knowledge exchange between both regions.

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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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As the utility and usage of HPC infrastructures increases, more computational and storage power is required to efficiently handle the amount of targeted applications. In fact, many HPC centers are now aiming at exascale supercomputers supporting at least one exaFLOPs (1018 operations per second), which represents a thousandfold increase in processing power over the first petascale computer deployed in 2008 [RD+15]. Although this is a necessary requirement for handling the increasing number of HPC applications, there are several outstanding challenges that still need to be tackled so that this extra computational power can be fully leveraged. 

Management of large infrastructures and heterogeneous workloads: By adding more compute and storage nodes, one is also increasing the complexity of the overall HPC distributed infrastructure and making it harder to monitor and manage. This complexity is increased due to the need of supporting highly heterogeneous applications that translate into different workloads with specific data storage and processing needs [ECS+17]. For example, on the one hand, traditional scientific modeling and simulation tasks require large slices of computational time, are CPU-bound, and rely on iterative approaches (parametric/stochastic modeling). On the other hand, data-driven Big Data applications contemplate shorter computational tasks, that are I/O bound and, in some cases, have real-time response requirements (i.e., latency-oriented). Also, many of the applications leverage AI and machine learning tools that require specific hardware (e.g., GPUs) in order to be efficient.

Support for general-purpose analytics: The increased heterogeneity also demands that HPC infrastructures are now able to support general-purpose AI and BigData applications that were not designed explicitly to run on specialised HPC hardware [KWG+13]. Therefore, developers are not required to significantly change their applications so that they can execute efficiently at HPC clusters.

Avoiding the storage bottleneck: By only increasing the computational power and improving the management of HPC infrastructures it may still not be possible to fully harmed the capabilities of these infrastructures. In fact, Big Data and AI applications are data-driven and require efficient data storage and retrieval from HPC clusters. With an increasing number of applications and heterogeneous workloads, the storage systems supporting HPC may easily become a bottleneck [YDI+16, ECS+17]. Indeed, as pointed out by several studies, the storage access time is one of the major bottlenecks limiting the efficiency of current and next-generation HPC infrastructures. 

In order to address these challenges, RISC2 partners are exploring: New monitoring and debugging tools that can aid in the analysis of complex AI and Big Data workloads in order to pinpoint potential performance and efficiency bottlenecks, while helping system administrators and developers on troubleshooting these [ENO+21].

Emerging virtualization technologies, such as containers, that enable users to efficiently deploy and execute traditional AI and BigData applications in an HPC environment, without requiring any changes to their source-code [FMP21].  

The Software-Defined Storage paradigm in order to improve the Quality-of-Service (QoS) for HPC’s storage services when supporting hundreds to thousands of data-intensive AI and Big Data applications [DLC+22, MTH+22].  

To sum up, these three research goals, and respective contributions, will enable the next generation of HPC infrastructures and services that can efficiently meet the demands of Big Data and AI workloads. 

References

[DLC+22] Dantas, M., Leitão, D., Cui, P., Macedo, R., Liu, X., Xu, W., Paulo, J., 2022. Accelerating Deep Learning Training Through Transparent Storage Tiering. IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGrid)  

[ECS+17] Joseph, E., Conway, S., Sorensen, B., Thorp, M., 2017. Trends in the Worldwide HPC Market (Hyperion Presentation). HPC User Forum at HLRS.  

[FMP21] Faria, A., Macedo, R., Paulo, J., 2021. Pods-as-Volumes: Effortlessly Integrating Storage Systems and Middleware into Kubernetes. Workshop on Container Technologies and Container Clouds (WoC’21). 

[KWG+13] Katal, A., Wazid, M. and Goudar, R.H., 2013. Big data: issues, challenges, tools and good practices. International conference on contemporary computing (IC3). 

[NCR+18] Netto, M.A., Calheiros, R.N., Rodrigues, E.R., Cunha, R.L. and Buyya, R., 2018. HPC cloud for scientific and business applications: Taxonomy, vision, and research challenges. ACM Computing Surveys (CSUR). 

[MTH+22] Macedo, R., Tanimura, Y., Haga, J., Chidambaram, V., Pereira, J., Paulo, J., 2022. PAIO: General, Portable I/O Optimizations With Minor Application Modifications. USENIX Conference on File and Storage Technologies (FAST). 

[OG+15] Osseyran, A. and Giles, M. eds., 2015. Industrial applications of high-performance computing: best global practices. 

[RD+15] Reed, D.A. and Dongarra, J., 2015. Exascale computing and big data. Communications of the ACM. 

[ENO+21] Esteves, T., Neves, F., Oliveira, R., Paulo, J., 2021. CaT: Content-aware Tracing and Analysis for Distributed Systems. ACM/IFIP Middleware conference (Middleware). 

[YDI+16] Yildiz, O., Dorier, M., Ibrahim, S., Ross, R. and Antoniu, G., 2016, May. On the root causes of cross-application I/O interference in HPC storage systems. IEEE International Parallel and Distributed Processing Symposium (IPDPS). 

By INESC TEC

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The workshop aimed to exchange experiences, results, and best practices of collaboration initiatives between Europe and Latin America, in which HPC was essential, and to discuss how to work towards sustainability by reinforcing the bridges between the HPC communities in both regions. The workshop was organized by our partners Esteban Meneses from CeNAT, Fabrizio Gagliardi from BSC, Bernd Mohr from JSC, Carlos J. Barrios H. from UIS, and Rafael Mayo-Gacía from CIEMAT.

The workshop was opened with a keynote by Daniele Lezzi from BSC who reviewed the EU-LATAM collaboration on HPC. Six more presentations highlighted research work from Latin America and collaborative work between organizations on both continents. More information about the workshop including a detailed program can be found here.

The RISC2 project supported the IEEE Cluster Conference, a major international forum for presenting and sharing recent accomplishments and technological developments in the field of cluster computing, as well as the use of cluster systems for scientific and commercial applications by organizing a networking event at the end of the workshop day.

Our partner Esteban Meneses, from National High Technology Center in Costa Rica and one of the RISC2 partners, was one of the Publicity Co-Chairs of the IEEE Cluster 2022 Conference.

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