Professor Mateo Valero, born in 1952 (Alfamén, Zaragoza), obtained his Telecommunication Engineering Degree from the Technical University of Madrid (UPM) in 1974 and his Ph.D. in Telecommunications from the Technical University of Catalonia (UPC) in 1980. He has been teaching at UPC since 1974; since 1983 he has been a full professor at the Computer Architecture Department. From 1990 to 1995 Professor Valero created and directed the European Center for Parallelism of Barcelona (CEPBA) performing basic and applied research in parallel computing. He was also the director of C4, the Catalan Center for Computation and Communications, during 1995-2000. Since October 2000 to 2004, he has been the director of CIRI, the CEPBA-IBM Research Institute, created to conduct research on parallel computers. Since May 2004, he has been the director of Barcelona Supercomputing Center, the Spanish national supercomputing centre.

Mateo Valero (Barcelona Supercomputing)

Professor Mateo Valero, born in 1952 (Alfamén, Zaragoza), obtained his Telecommunication Engineering Degree from the Technical University of Madrid (UPM) in 1974 and his Ph.D. in Telecommunications from the Technical University of Catalonia (UPC) in 1980. He has been teaching at UPC since 1974; since 1983 he has been a full professor at the Computer Architecture Department. From 1990 to 1995 Professor Valero created and directed the European Center for Parallelism of Barcelona (CEPBA) performing basic and applied research in parallel computing. He was also the director of C4, the Catalan Center for Computation and Communications, during 1995-2000. Since October 2000 to 2004, he has been the director of CIRI, the CEPBA-IBM Research Institute, created to conduct research on parallel computers. Since May 2004, he has been the director of Barcelona Supercomputing Center, the Spanish national supercomputing centre.

Keynote: The future is wide open

Barcelona Supercomputing Center believes the future of the entire computing ecosystem will be based on open technology due to the technology trends, costs, and ubiquitous open source software.


PedroSilva

Pedro Mario Cruz E Silva (NVIDIA)

Pedro Mário Cruz e Silva did his BSc (1995), and MSc (1998) at Federal University of Pernambuco (UFPE), he also did his DSc in 2004 at PUC-Rio. He created the Computational Geophysics Group at Tecgraf/PUC-Rio were worked for 15 years as Manager, during this period was responsible for several Software Development and R&D projects for Geophysics with strong focus on innovation. He also finished an MBA in 2015 at Getúlio Vargas Foundation (FGV/RJ). He is a member of the main board of The Brazilian Geophysical Society (SBGf). Currently is the Solution Architect Manager at NVIDIA responsible for all technologies in the Latin America Region.

Keynote: NVIDIA Applications Frameworks for AI & HPC

In this presentation I’ll give an overview of key NVIDIA software and hardware components inside Deep Learning frameworks (TensorFlow & Pytorch) and NVIDIA applications platforms: RAPIDS (Machine Learning), Metropolis (IVA), Jarvis (Conversational AI), Merlin (Recommender Systems), Morpheus (Cybersecurity), etc. I’ll show the example of GPU Accelerated Quantum Computing Simulation with our new cuQuantum library.


carlos_jaime

Carlos Jaime (UIS)

Professor Barrios is a systems engineer from the Universidad Industrial de Santander (Bucaramanga, Colombia), a master’s degree in applied mathematics and computer science from the University of Grenoble – Alpes (Grenoble, France) and a PhD in Computer Science from the University of Nice-Costa Azul ( Nice, France). He collaborates with some international companies such as NVIDIA, Intel, HPE, IBM, Atos-BULL, Ecopetrol among others. He has also created and led HPC courses and conferences (such as SC-CAMP, CLCAR and CARLA) as well as participates in different scientific and technological associations around the world (SIGHPC-ACM, TCC-IEEE), around scalable architectures and high-performance computing. He is currently a research professor at the Industrial University of Santander in Bucaramanga, Colombia, and a consultant through the ICT Thought Tank for Colombian government affairs, via the Ministry of Information and Communication Technologies (MinTIC) of the Colombian Government, as well as coordinator General of the Advanced Computing Service for Latin America and the Caribbean.

Mónica Lopez (Renata)

Monica is an expert in the development of digital transformation processes for Higher Education Institutions and other organizations, as well as in models of appropriation of technologies from the human point of view with a vision of behavior and culture for the development of Digital Talent. She was also president of the Sectoral Board for Technology Management and Digital Talent in Colombia and the Council of TIC (Information and Communication Technologies) board of the country.

Rafael Rodriguez (Renata)

Rafael is an electronic engineer from the Pontificia Universidad Javeriana, a specialist in business administration from the Universidad de los Andes and has studies in management and evaluation of investment projects from the Universidad Externado de Colombia.

He is an expert in research, structuring and integral management of infrastructure and technology projects, as well as in the articulation of projects of national, regional and local scope.

Before assuming the Executive Direction of RENATA, he worked advising, structuring and managing strategic infrastructure projects and solutions for sustainable cities at the national and district levels.

Keynote: SCALAC & LaRedCCA (Spanish)


Nina Bogl (Amazon WebService HPC)

Nina Vogl is a HPC Specialist Solution Architect at AWS. She’s worked with HPC workloads for close to thirty-five years, covering multiple HPC disciplines, such as Bioscience/LifeSciences, Physics, Electronic Design Automation, Oil and Gas industry modeling, Weather/Climate modeling, Media/Entertainment and more, serving both commercial as well as public sector customers. Over the years Nina had the opportunity to deploy many different technologies to implement HPC solutions, such as mainframes, proprietary Unix workstations, Linux clusters, GPGPU accelerated solutions, and in the recent years, cloud computing solutions. Nina has a postgraduate mathematics degree with a minor in physical chemistry.

Keynote: Research Computing on AWS Made Easy!

AWS offers a vast number of resources and services, including an amazing amount of compute capacity, and a variety of architecture options, such that every researcher could have a supercomputer “at their fingertips”.

However, the task of having to setup their own environment and needing “IT Skills” may seem daunting to many scientists and researchers.

This presentation will demonstrate an easy way to use AWS tools and services to create an HPC cluster the way you need, when you need it. You will also learn how to setup your preferred application once, and use it every time you start a new cluster. In the AWS Cloud you can. experiment without fear!


George Thiruvathukal (Loyola University Chicago)

George K. Thiruvathukal is a full professor of computer science at Loyola University Chicago. His primary research interests span high-performance computing, distributed systems, and software engineering. His current research foci are on machine learning and computer vision, empirical software engineering (in support of research software development), and the intersection of cloud computing and supercomputing. Dr. Thiruvathukal received the PhD and MS degrees in computer science from Illinois Institute of Technology in 1995 and 1990, respectively and BA degrees in physics and computer science (mathematics minor) from Lewis University (Romeoville, IL) in 1988.

Keynote: Software Engineering in Scientific Computing

Scientific software is a special class of software that includes software developed to support various scientific endeavors that would be difficult, or impossible, to perform experimentally or without computational support. The development of scientific software differs significantly from the development of more traditional business information systems, from which many software engineering best practices and tools have been drawn.

Keynote: Bias in AI


Robert Davey (Earlham Institute)

Rob is the Head of Research e-Infrastructure at the Earlham Institute (EI), where he leads both the Data Infrastructure research faculty group, the Scientific Computing group, and the National Capability in e-Infrastructure. The team applies their research expertise to develop infrastructure platforms for data and software dissemination and publication, large-scale data visualisation, and best practice and training in bioinformatics. He completed his BSc in Microbiology (2001) and his PhD in Bioinformatics (2005), both at the University of East Anglia, the latter developing statistical algorithms and end user software for assessing the gene content of bacterial organisms using Comparative Genomic Hybridisation microarrays.

Keynote: Implementation of Cyverse UK

CyVerse UK provides free, large scale, computing facilities and data storage designed for life scientists. CyVerse provides an intuitive web interface, Discovery Environment (DE), where scientists can upload data and run analyses.


Nina McCurdy (NASA)

Dr. Nina McCurdy is the newest member of the Data Analysis and Visualization group within the NASA Advanced Supercomputing (NAS) Division at NASA Ames Research Center. Her research focuses on developing custom data visualizations to support domain expert analysis. Nina received a bachelor’s degree in applied physics from the University of California Santa Cruz, and a Ph.D. in data visualization and computer graphics from the University of Utah.

 Patrick Moran (NASA)

Dr. Patrick Moran is a Computer Scientist with the Data Analysis and Visualization group at the NASA Advanced Supercomputing (NAS) Division at NASA Ames Research Center.  His research interests include visualization techniques, graphics, computational geometry, schlieren imaging and the synergy between visualization and photography.  Dr. Moran has a bachelor’s degree in electrical engineering from Santa Clara University and a Ph.D. in Computer Science from the University of Illinois Urbana-Champaign.

Keynote: Data Visualization at the NASA Advanced Supercomputing Division

The goal of data visualization is to provide further insight by rendering data in a manner that best leverages our visual perception capabilities.  In the Data Analysis and Visualization group within the NASA Advanced Supercomputing (NAS) Division at NASA Ames Research Center, we collaborate with the users of the NAS systems in the development of visualizations and tools that enable one to see and interrogate computing results in new and fruitful ways.  In this talk we will describe some of our work, the interesting challenges that we faced, and why we think visualization is cool.


Carolina González (Microsoft Azure)

Carolina Gonzalez Zapata is a Program Manager II on the Azure Compute team focused on Microsoft Azure HPC. Carolina is a graduate from Universidad Central de Chile as a Civil Informatics Engineering.

She has more than ten years of experience developing and executing project plans for high-profile clients in multiple industries. At Microsoft, she spent the last two years on HPC customer experience improvements

from the Support Team through the Azure Portal using the best industry practices related to supportability.

Andrew Howard (Microsoft Azure)

Andy Howard is a Senior Program Manager on the Azure Compute team focused on HPC and Azure CycleCloud. Andy is a graduate from Purdue University where he received a BS in Electrical and Computer Engineering Technology. After spending almost a decade helping architect, build, and manage on-premises HPC systems for companies such as Purdue University, Cray, and the U.S. Department of Defense, Andy has spent the last seven years helping transition HPC workloads to the cloud. At Microsoft, he draws on this industry experience to help customers plan cloud HPC implementations and guide Microsoft’s HPC product offerings.

Keynote: Meteorological models with Microsoft Azure


Yuri Alexeev (Argonne)

He is a Principal Project Specialist at the Argonne National Laboratory. His research involves development of quantum computing algorithms, error correction/mitigation techniques, and numerical simulator of quantum systems using high-performance computing on next-generation high-performance supercomputers. The recent projects include development of quantum chemistry and combinatorial optimization quantum algorithms for NISQ quantum computers.

Keynote: Quantum Computing trends


Paulo Aragão (AWS)

Paulo Aragão is a Solutions Architect. For more than 20 years he has been helping HPC and Enterprise customers to use technology to achieve their business outcomes. Nowadays he is helping customers innovate using AI/ML services on the AWS Cloud. Passionate about music and scuba diving, he is a bass player in a rock band and has an extensive dive log. In his spare time, Paulo likes to play World of Warcraft, read books, and cook for his family and friends.

Keynote: HPC in Geology


Nelson Vera (UDistrital)

Electronic Engineer and Doctor of Engineering. Coordinator of the Master’s Degree in Information and Communication Sciences and professor at the Francisco José de Caldas District University. Researcher in HPC, Data Science and Bioinformatics. Author of books, such as: “OpenCL Práctico”, Redes neuronales convolucionales usando Keras y acelerando con GPU”, “Entorno bioinformático para RNA-Seq”, “Biopython básico, manual práctico”

Keynote: From Bits to Qbits


Jacob Tomlinson (Nvidia)

Jacob Tomlinson is a senior Python software engineer at NVIDIA with a focus on deployment tooling for distributed systems. His work involves maintaining open source projects including RAPIDS and Dask. RAPIDS is a suite of GPU accelerated open source Python tools which mimic APIs from the PyData stack including those of Numpy, Pandas and SciKit-Learn. Dask provides advanced parallelism for analytics with out-of-core computation, lazy evaluation and distributed execution of the PyData stack. He also tinkers with the open source chatbot automation framework Opsdroid in his spare time. Jacob volunteers with the local tech community group Tech Exeter and lives in Exeter, UK.

Keynote: RAPIDS

RAPIDS is a “suite of open source software libraries and APIs” grouped together for the purpose of providing users the ability to “execute end-to-end data science and analytics pipelines entirely on GPUs.”

RAPIDS also includes support for multi-node, multi-GPU deployments, enabling vastly accelerated processing and training on much larger dataset sizes.


Jacob Tomlinson (Nvidia)

Jacob Tomlinson is a senior Python software engineer at NVIDIA with a focus on deployment tooling for distributed systems. His work involves maintaining open source projects including RAPIDS and Dask. RAPIDS is a suite of GPU accelerated open source Python tools which mimic APIs from the PyData stack including those of Numpy, Pandas and SciKit-Learn. Dask provides advanced parallelism for analytics with out-of-core computation, lazy evaluation and distributed execution of the PyData stack. He also tinkers with the open source chatbot automation framework Opsdroid in his spare time. Jacob volunteers with the local tech community group Tech Exeter and lives in Exeter, UK.

Natalia Clementi (Coiled)

Natalia (Naty) Clementi is an open source software engineer at Coiled. Her work involves contributing to the open source project Dask. She is an ex-academic who got her PhD in Mechanical Engineering at The George Washington University, and her masters degree in Physics at Universidad Nacional de Córdoba, Argentina. In her spare time, she likes playing ultimate frisbee, going fly fishing, and playing video games. She currently lives in Arlington, Virginia, USA; but she is originally from Córdoba, Argentina.

Tutorial: High Performance Computing with Dask

Dask is a free and open-source library for parallel computing in Python. Dask helps you scale your data science and machine learning workflows.


Carlos Alvarez (URosario)

Biologist with a Master in Physics from Universidad de los Andes. Obtained his Ph.D. in Physics from Université Paris XI developing models on ferrofluids and charged colloids via molecular simulations. He realized his post-doctoral stay in the Technische Universität of Berlín, where he worked on numerical simulations of magnetic nano-rods. Currently, he is Professor of the School of Engineering, Science and Technology at Universidad del Rosario – Bogotá.

Tutorial: Introduction to Julia

Julia is a free open source, high-level, high-performance, dynamic programming language for numerical computing. Primarily Julia is built for speed and applications using it rather than Python or R have been found to have very fast running times. Much of Julia’s speed is attributed to its LLVM-based just-in-time (JIT) compiler which often matches the performance of C. It also provides support to perform advanced tasks such as cloud computing and parallelism which are more fundamental to performing big data analytics.


Luiz Angelo Steffenel (Université de Reims Champagne Ardenne)

Jean Francois Couturier (Université de Reims Champagne Ardenne)

Gilberto Javier Dìaz Toro (SC3UIS)

carlos_jaime

Carlos J. Barrios (UIS)

Tutorial: Quantum Computing


Juan Pablo Mallarino

Juan P. Mallarino (Cybercolombia)

Physicist from Universidad Nacional de Colombia, obtained my Ph.D. in Physics from Universidad de los Andes developing analytic models for stiff rod-like polyelectrolytes through molecular simulations. He was also the HPC Coordinator and Researcher for the School of Sciences in Universidad de los Andes until early 2021. He has a solid background on theoretical statistical mechanics, programming languages (C/C++, Python, R and SQL), and Linux administration for cluster environments with application development and deployment.

Tutorial: OpenMP

OpenMP is a set of compiler directives as well as an API for programs written in C, C++, or FORTRAN that provides support for parallel programming in shared-memory environments. OpenMP identifies parallel regions as blocks of code that may run in parallel. Application developers insert compiler directives into their code at parallel regions, and these directives instruct the OpenMP run-time library to execute the region in parallel.


Jose Monsalve

Jose Monsalve (Argonne)

Jose Manuel Monsalve Diaz is a postdoctoral appointee in Argonne National Laboratory working on exploring innovative ideas on future computer architectures. He obtained his PhD in Electrical and Computer Engineering from the University of Delaware in 2021. His work defined the Sequential Codelet Model, a program execution model for future parallel, heterogeneous and distributed computers based on principles of Dataflow models of computation. Jose M. Monsalve Diaz obtained his Masters in Electrical and Computer Engineering from the University of Delaware in 2020, and his bachelor’s degree in Electronics Engineering from the Pontificia Universidad Javeriana in 2013. Throughout the years he has worked as a research assistant of the CAPSL research group for Prof Guang. R. Gao, and the CRPL research group for Prof. Sunita Chandrasekaran. His areas of interest are parallel computer architecture design, parallel computer systems and parallel programming models. He has worked on validation and verification of OpenMP target offloading, as well as with OpenACC programming targetting CPU and heterogeneous systems based on GPGPUs. Other projects also involved unconventional Data-flow based programming models and computer architectures

Tutorial: OpenACC

OpenACC (for open accelerators) is a programming standard for parallel computing. The standard is designed to simplify parallel programming of heterogeneous CPU/GPU systems. The programmer can annotate C, C++ and Fortran source code to identify the areas that should be accelerated using compiler directives and additional functions.


Catalina Albornoz (IBM)

Catalina is passionate about quantum computing and fighting climate change. She is currently an IBM Quantum Computing Ambassador and a Power Server Sales Specialist at IBM Colombia. She is a Mechanical and Electronic Engineer with an MSc. In Electronic Engineering and MEng. in Control Systems. She has experience in managing energy efficiency projects, especially in the retail sector. She also has experience developing algorithms for autonomous vehicles and smart agriculture.

Sieglinde Pfaendler (IBM)

Have been coordinating industrial based research projects, focused on the translational border between academia and industry since 2008. Trained as an experimental physicist with ten years of experience developing semiconductor materials and fabricating devices for direct commercial applications including quantum transistors, thin film transistors, piezoelectric touch sensors, liquid
crystal and photovoltaic cells for the flexible, printed and plastic electronics industry. Specialities: Next generation materials and devices for the security, retail and packaging industries.
Flexible and transparent metal oxides, cleanroom processing, materials research, experimental research project management, instruction, teaching, data acquisition

Tutorial: An Introduction to Quantum Computing