The RISC2 project was also represented, having made it possible, through monetary support, for some students from Latin America to take part – thus continuing its work in the social field. In total, 60 students from 25 different nationalities took part in the initiative.

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The ENERXICO Project focused on developing advanced simulation software solutions for oil & gas, wind energy and transportation powertrain industries.  The institutions that collaborated in the project are for México: ININ (Institution responsible for México), Centro de Investigación y de Estudios Avanzados del IPN (Cinvestav), Universidad Nacional Autónoma de México (UNAM IINGEN, FCUNAM), Universidad Autónoma Metropolitana-Azcapotzalco, Instituto Mexicano del Petróleo, Instituto Politécnico Nacional (IPN) and Pemex, and for the European Union: Centro de Supercómputo de Barcelona (Institution responsible for the EU), Technische Universitäts München, Alemania (TUM), Universidad de Grenoble Alpes, Francia (UGA), CIEMAT, España, Repsol, Iberdrola, Bull, Francia e Universidad Politécnica de Valencia, España.  

The Project contemplated four working packages (WP): 

WP1 Exascale Enabling: This was a cross-cutting work package that focused on assessing performance bottlenecks and improving the efficiency of the HPC codes proposed in vertical WP (UE Coordinator: BULL, MEX Coordinator: CINVESTAV-COMPUTACIÓN); 

WP2 Renewable energies:  This WP deployed new applications required to design, optimize and forecast the production of wind farms (UE Coordinator: IBR, MEX Coordinator: ININ); 

WP3 Oil and gas energies: This WP addressed the impact of HPC on the entire oil industry chain (UE Coordinator: REPSOL, MEX Coordinator: ININ); 

WP4 Biofuels for transport: This WP displayed advanced numerical simulations of biofuels under conditions similar to those of an engine (UE Coordinator: UPV-CMT, MEX Coordinator: UNAM); 

For WP1 the following codes were optimized for exascale computers: Alya, Bsit, DualSPHysics, ExaHyPE, Seossol, SEM46 and WRF.   

As an example, we present some of the results for the DualPHYysics code. We evaluated two architectures: The first set of hardware used were identical nodes, each equipped with 2 ”Intel Xeon Gold 6248 Processors”, clocking at 2.5 GHz with about 192 GB of system memory. Each node contained 4 Nvidia V100 Tesla GPUs with 32 GB of main memory each. The second set of hardware used were identical nodes, each equipped with 2 ”AMD Milan 7763 Processors”, clocking at 2.45 GHz with about 512 GB of system memory. Each node contained 4 Nvidia V100 Ampere GPUs with 40 GB of main memory each. The code was compiled and linked with CUDA 10.2 and OpenMPI 4. The application was executed using one GPU per MPI rank. 

In Figures 1 and 2 we show the scalability of the code for the strong and weak scaling tests that indicate that the scaling is very good. Motivated by these excellent results, we are in the process of performing in the LUMI supercomputer new SPH simulations with up to 26,834 million particles that will be run with up to 500 GPUs, which is 53.7 million particles per GPU. These simulations will be done initially for a Wave Energy Converter (WEC) Farm (see Figure 3), and later for turbulent models. 

Figure 1. Strong scaling test with a fix number of particles but increasing number of GPUs.

Figure 2. Weak scaling test with increasing number of particles and GPUs.

Figure 3. Wave Energy Converter (WEC) Farm (taken from https://corpowerocean.com/)

As part of WP3, ENERXICO developed a first version of a computer code called Black Hole (or BH code) for the numerical simulation of oil reservoirs, based on the numerical technique known as Smoothed Particle Hydrodynamics or SPH. This new code is an extension of the DualSPHysics code (https://dual.sphysics.org/) and is the first SPH based code that has been developed for the numerical simulation of oil reservoirs and has important benefits versus commercial codes based on other numerical techniques.  

The BH code is a large-scale massively parallel reservoir simulator capable of performing simulations with billions of “particles” or fluid elements that represent the system under study. It contains improved multi-physics modules that automatically combine the effects of interrelated physical and chemical phenomena to accurately simulate in-situ recovery processes. This has led to the development of a graphical user interface, considered as a multiple-platform application for code execution and visualization, and for carrying out simulations with data provided by industrial partners and performing comparisons with available commercial packages.  

Furthermore, a considerable effort is presently being made to simplify the process of setting up the input for reservoir simulations from exploration data by means of a workflow fully integrated in our industrial partners’ software environment.  A crucial part of the numerical simulations is the equation of state.  We have developed an equation of state based on crude oil data (the so-called PVT) in two forms, the first as a subroutine that is integrated into the code, and the second as an interpolation subroutine of properties’ tables that are generated from the equation of state subroutine.  

An oil reservoir is composed of a porous medium with a multiphase fluid made of oil, gas, rock and other solids. The aim of the code is to simulate fluid flow in a porous medium, as well as the behaviour of the system at different pressures and temperatures.  The tool should allow the reduction of uncertainties in the predictions that are carried out. For example, it may answer questions about the benefits of injecting a solvent, which could be CO2, nitrogen, combustion gases, methane, etc. into a reservoir, and the times of eruption of the gases in the production wells. With these estimates, it can take the necessary measures to mitigate their presence, calculate the expense, the pressure to be injected, the injection volumes and most importantly, where and for how long. The same happens with more complex processes such as those where fluids, air or steam are injected, which interact with the rock, oil, water and gas present in the reservoir. The simulator should be capable of monitoring and preparing measurement plans. 

In order to be able to perform a simulation of a reservoir oil field, an initial model needs to be created.  Using geophysical forward and inverse numerical techniques, the ENERXICO project evaluated novel, high-performance simulation packages for challenging seismic exploration cases that are characterized by extreme geometric complexity. Now, we are undergoing an exploration of high-order methods based upon fully unstructured tetrahedral meshes and also tree-structured Cartesian meshes with adaptive mesh refinement (AMR) for better spatial resolution. Using this methodology, our packages (and some commercial packages) together with seismic and geophysical data of naturally fractured reservoir oil fields, are able to create the geometry (see Figure 4), and exhibit basic properties of the oil reservoir field we want to study.  A number of numerical simulations are performed and from these oil fields exploitation scenarios are generated.

Figure 4. A detail of the initial model for a SPH simulation of a porous medium.

More information about the ENERXICO Project can be found in: https://enerxico-project.eu/

By: Jaime Klapp (ININ, México) and Isidoro Gitler (Cinvestav, México)

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The post ACM Europe Summer School on HPC Computer Architectures for AI and Dedicated Applications first appeared on RISC2 Project.

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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The posters “Developing Efficient Scientific Gateways for Bioinformatics in Supercomputing Environments Supported by Artificial Intelligence” and “Scalable Numerical Method for Biphasic Flows in Heterogeneous Porous Media in High-Performance Computational Environments” are part of the activities of the LNCC RISC2 projects.

According to Carla Osthoff (LNCC) , former poster presents a collaboration project that aims to develop green and intelligent scientific gateways for bioinformatics supported by high-performance computing environments (HPC) and specialized technologies such as scientific workflows, data mining, machine learning, and deep learning.  The efficient analysis and interpretation of Big Data open new challenges to explore molecular biology, genetics, biomedical, and healthcare to improve personalized diagnostics and therapeutics; then, it becomes necessary to availability of new avenues to deal with this massive amount of information. New paradigms in Bioinformatics and Computational Biology drive the storing, managing, and accessing of data. HPC and Big Data advances in this domain represent a vast new field of opportunities for bioinformatics researchers and a significant challenge. The Bioinfo-Portal science gateway is a multiuser Brazilian infrastructure for bioinformatics applications, benefiting from the HPC infrastructure. We present several challenges for efficiently executing applications and discussing the findings on how to improve the use of computational resources. We performed several large-scale bioinformatics experiments that are considered computationally intensive and time-consuming. We are currently coupling artificial intelligence to generate models to analyze computational and bioinformatics metadata to understand how automatic learning can predict computational resources’ efficient use. The computational executions are carried out at Santos Dumont Supercomputer. This is a multi-disciplinary project requiring expertise from several knowledge areas from four research institutes (LNCC, UFRGS, INRIA Bordeaux, and CENAT in Costa Rica). Finally, Brazilian funding agencies (CNPQ, CAPES) and the RISC-2 project from the European Economic and Social Committee (EESC) support the project.

Latter poster presents a project that aims to develop a scalable numerical approach for biphasic flows in heterogeneous porous media in high-performance computing environments based on the high-performance numerical methodology. In this system, an elliptical subsystem determines the velocity field, and a non-linear hyperbolic equation represents the transport of the flowing phases (saturation equation). The model applies a locally conservative finite element method for the mixing speed. Furthermore, the model employs a high-order non-oscillatory finite volume method, based on central schemes, for the non-linear hyperbolic equation that governs phase saturation. Specifically, the project aims to build scalable codes for a high-performance environment. Identified the bottlenecks in the code, the project is now working in four different research areas. Parallel I/O routines and high-performance visualization to decrease the I/O transfers bottleneck, Parallel programming to reduce code bottlenecks for multicore and manycore architectures. and Adaptive MPI  to decrease the message communication bottleneck. The poster presents the first performance evaluation results used to guide the project research areas. This endeavor is a multi-disciplinary project requiring expertise from several knowledge areas from four research institutes (LNCC, UFRGS, UFLA in Brazil, and CENAT in Costa Rica). Finally, Brazilian funding agencies (CNPQ, CAPES) and the RISC-2 project.

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