The third co-design and co-development workshop of Exa-DI on "Artificial Intelligence for HPC@Exscale"
The Third co-design/co-development workshop of the Exa-DI project (Development and Integration) of the PEPR NumPEx was dedicated to “Artificial Intelligence for HPC@Exscale” targeting the two topics “Image analysis @ exascale” and “Data analysis and robust inference @ exascale”. It took place on October 2 and 3, 2024 at the Espace La Bruyère, Du Côté de la Trinité (DCT) in Paris.
This face-to-face workshop brought together, for two days, Exa-DI members, members of the other NumPEx projects (Exa-MA: Methods and Algorithms for Exascale, Exa-SofT: HPC Software and Tools, Exa-DoST: Data-oriented Software and Tools for the Exascale and Exa-AToW: Architectures and Tools for Large-Scale Workflows), Application demonstrators (ADs) from various research and industry sectors and Experts to discuss advancements and future directions for integration of Artificial Intelligence into HPC/HPDA workflows at exascale targeting the two topics, “Large image analysis” and “Data analysis and robust inference”.
This workshop is the third co-design/co-development workshops in the series whose main objective is to promote software stack co-development strategies to accelerate exascale development and performance portability of computational science and engineering applications. This workshop is a little different from the previous two in that it has a prospective character targeting the increasing importance of rapidly evolving AI-driven and AI-coupled HPC/HPDA workflows in “Large images analysis @ exascale” and “Data analysis (simulation, experiments, observation) & robust inference @ exascale”. Its main objectives are first to co-develop a shared understanding of the different modes of coupling AI into HPC/HPDA workflows, second to co-identify execution motifs most commonly found in scientific applications in order to drive the co-development of collaborative specific benchmarks or proxy apps allowing to evaluate/measure end-to-end performance of AI-coupled HPC/HPDA workflows and finally, to co-identify software components (libraries, frameworks, data communication, workflow tools, abstraction layers, programming and execution environments) to be co-developed and integrated to improve critical components and accelerate them.
Key sessions included
- Introduction and Context: Setting the stage for the workshop’s two main topics as well as presenting the GT IA, a transverse action in NumPEx.
- Attendees Self-Introduction: Allowing attendees to introduce themselves and their interests.
- Various Sessions: These sessions featured talks on the challenges to tackle and bottlenecks to overcome (execution speed, scalability, volume of data…), on the type, the format and the volume of data currently investigated, on the frameworks or programming languages currently used (e.g. python, pytorch, JAX, C++, etc..) and on the typical elementary operations performed on data.
- Discussions and Roundtables: These sessions provided opportunities for attendees to engage in discussions and share insights on the presented topics in order to determine a strategy to tackle the challenges in co-design and co-development process.
Invited speakers
- Jean-Pierre Vilotte from CNRS, member of Exa-DI, who provided the introductory context for the workshop.
- Thomas Moreau from Inria, member of Exa-DoST, presenting the GT IA, a transverse action in NumPEx.
- Tobias Liaudat from CEA, discussing fast and scalable uncertainty quantification for scientific imaging.
- Damien Gradatour from CNRS, addressing how building new brains for giant astronomical telescopes with Deep Neural Networks?
- Antoine Petiteau from CEA, discussing data analysis for observing the Universe with Graviational Waves at low frequency.
- Kevin Sanchis from Safran AI, addressing benchmarking self-supervised learning methods in remote sensing.
- Hugo Frezat from Université Paris Cité, presenting learning subgrid-scale models for turbulent rotating convection.
- Benoit Semelin from Sorbonne Université, discussing simulation-based inference with cosmological radiative hydrodynamics simulations for SKA.
- Bruno Raffin & Thomas Moreau from Inria, presenting Machine Learning based analysis of large simulation outputs in Exa-DoST.
- Julián Tachella from CNRS, presenting DeepInverse: a PyTorch library for solving inverse problems with deep learning.
- Erwan Allys from ENS-PSL, exploring generative model and component separation in limited data regime with Scattering Transform.
- François Lanusse from CNRS, discussing multimodal pre-training for Scientific Data: Towards large data models for Astrophysics. > en ligne
- Christophe Kervazo from Telecom Paris, addressing interpretable and scalable deep learning methods for imaging inverse problems.
- Eric Anterrieu from CNRS, exploring deep learning based approach in imaging radiometry by aperture synthesis and its implementation.
- Philippe Ciuciu from CEA, addressing Computational MRI in the deep learning era.
- Pascal Tremblin from CEA, characterizing patterns in HPC simulations using AI driven image recognition and categorization.
- Bruno Raffin from Inria, member of Exa-DI, presenting the Software Packaging in Exa-DI
Outcomes and impacts
Many interesting and fruitful discussions took place during this prospective workshop. These discussions allowed us first to progress in understanding the challenges and bottlenecks underpinning AI-driven HPC/HPDA workflows most commonly found in the ADs. Then, a first series of associated issues to be addressed have been identified and these issues can be gathered in two mains axes: (i) image processing of large volumes, images resulting either from simulations or from experiments and (ii) exploration of high-dimensional and multimodal parameter spaces.
One of the very interesting issues that emerged from these discussions concerns the NumPEx software stack and in particular, how could the NumPEx software stack be increased beyond support for classic AI/ML libraries (e.g. TensorFlow, PyTorch) to support concurrent real time coupled execution of AI and HPC/HPDA workflows in ways that allow the AI systems to steer or inform the HPC/HPDA task and vice versa?
A first challenge is the coexistence and communication between HPC/HPDA and AI tasks in the same workflows. This communication is mainly impaired by the difference in programming models used in HPC (i.e., C++, C; and Fortran) and AI (i.e., Python) which requires a more unified data plane management in which high-level data abstractions could be exposed and to hide from both HPC simulations and AI models the complexities of the format conversion and data storage and data storage and transport. A second challenge concerns using the insight provided by the AI models and simulations for identifying execution motifs commonly found in the ADs to guide, steer, or modify the shape of the workflow by triggering or stopping new HPC/HPDA tasks. This implies that the workflow management systems must be able to ingest and react dynamically to inputs coming from the AI models. This should drive the co-development of new libraries, frameworks or workflow tools supporting AI integration into HPC/HPDA workflows.
In addition, these discussions highlighted that an important upcoming action would be to build cross-functional collaboration between software and workflow components development and integration with the overall NumPEx technologies and streamline developer and user workflows.
It was therefore decided during this workshop the set-up of a working group addressing these different issues and allowing in fine the building of a suite of shared and well specified proxy-apps and benchmarks, with well-identified data and comparison metrics addressing these different issues. Several teams of ADs and experts have expressed their interest in participating in this working group that will be formed. A first meeting with all interested participants will be organized shortly.
Attendees
- Jean-Pierre Vilotte, CNRS and member of Exa-DI
- Valérie Brenner, CEA and member of Exa-DI
- Jérôme Bobin, CEA and member of Exa-DI
- Jérôme Charousset, CEA and member of Exa-DI
- Mark Asch, Université Picardie and member of Exa-DI
- Bruno Raffin, Inria and member of Exa-DI and Exa-DoST
- Rémi Baron, CEA and member of Exa-DI
- Karim Hasnaoui, CNRS and member of Exa-DI
- Felix Kpadonou, CEA and member of Exa-DI
- Thomas Moreau, Inria and member of Exa-DoST
- Erwan Allys, ENS-PSL and application demonstrator
- Damien Gradatour, CNRS and application demonstrator
- Antoine Petiteau, CEA and application demonstrator
- Hugo Frezat, Université Paris Cité and application demonstrator
- Alexandre Fournier, Institut de physique du globe and application demonstrator
- Tobias Liaudat, CEA
- Jonathan Kem, CEA
- Kevin Sanchis, Safran AI
- Benoit Semelin, Sorbonne Université
- Julian Tachella, CNRS
- François Lanusse, CNRS
- Christophe Kervazo, Telecom Paris
- Eric Anterrieu, CNRS
- Philippe Ciuiciu, CEA
- Pascal Tremblin, CEA
Call for proposals "Numérique pour l’Exascale"
The NumPEx program is launching its first call for projects to support advances in high-performance computing (HPC), high-performance data analysis (HPDA) and artificial intelligence (AI). Our France 2030 research program aims to develop software capable of operating future exascale machines, and to prepare the main scientific and industrial application codes.
This call is structured around three axes:
- Emerging AI methods, algorithms and software for scientific computing and HPC for AI.
- Programming models adapted to accelerated architectures.
- Workflows for scientific data analysis, with the SKA project as a use case.
This call for projects has a budget of 4 million euros. It will fund 1 to 2 projects per axis, for a maximum duration of 48 months.
The amount of funding requested must be a minimum of 500 k€ and a maximum of 1 M€, depending on the theme of the project.
The same project manager can only be responsible for one PEPR project, including targeted projects.
Deadline for applications: April 1, 2025.
The 2024 annual meeting of Exa-DoST
The second annual meeting of the NumPEx Exa-DoST project took place at Inria, in Rennes, on 18-19 September 2024. This two days were an opportunity to share the first outcomes of the projet and discuss the upcoming research.
The Exa-DoST project is one of the five targeted projects of the NumPEx program, focusing on the challenges posed by data storage, processing, and analytics in the context of the emergence of Exascale Computing in Europe. The goal is to leverage innovative storage technologies and support complex hybrid workflows involving simulation, analytics, and learning, running at extreme scales across supercomputers interconnected to Clouds and Edge-based systems.
The second annual meeting of the Exa-DoST project took place at Inria, in Rennes, on 18-19 September 2024. It gathered participants in the project (scientists, engineers, students) with the goal of providing a common, shared vision on the project’s objectives, activities, and strategy. It also included specific workshops focused on identifying challenging application requirements in terms of data storage and analytics. For the first time, members of the ExaDoST Scientific Advisory Committee and of the Industrial and Technology Advisory Committee attended a global Exa-DoST meeting.
Wednesday, 18 September 2024
The first day was dedicated to presentations providing an overview of the project’s goals and activities in the various specific areas covered by the technical work packages. These were followed by a discussion on how the activities performed in these work packages (WP) could interact together.
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- Introduction to NumPEx and Exa-DoST
by Gabriel Antoniu, Inria research scientist and Exa-DoST co-leader
and Julien Bigot, CEA research scientist and Exa-DoST co-leader - Goals and progress status of the work packages:
- WP1 – Storage and I/O
by Francieli Boito, Inria research scientist and Exa-DoST WP leader
and François Tessier, Inria research scientist and Exa-DoST WP leader - WP2 – In situ processing
By Yushan Wang, CEA research scientist and Exa-DoST WP leader
and Laurent Colombet, CEA research scientist and Exa-DoST WP leader - WP3 – ML-based analytics
by Thomas Moreau, Inria research scientist and Exa-DoST WP leader
and Bruno Raffin, Inria research scientist and Exa-DoST WP leader - WP4 – Application illustrator :
by Virginie Grandgirard, CEA research scientist and Exa-DoST WP leader
and Damien Gratadour, Université Paris Cité professor and Exa-DoST WP leader
- WP1 – Storage and I/O
- Introduction to NumPEx and Exa-DoST
- Session on inter-WP interaction
animated by Gabriel Antoniu and Julien Bigot
Thursday, 19 September 2024
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- Introduction to the parallel brainstorming sessions
by Julien Bigot - Session on Codex
by Laurent Colombet - Session on Gysela
by Virginie Grandgirard - Session on SKA
by Laurent Colombet
- Introduction to the parallel brainstorming sessions
The participants found the exchanges particularly fruitful and decided to continue this work through a series of online and physical meetings.
Attendees
- Gabriel Antoniu, Inria and Exa-DoST leader
- Rosa Badia, BSC and board member of Exa-DoST
- Thomas Badts, Inria
- Andres Bermeo Marinelli, Inria and member of Exa-DoST
- Julien Bigot, CEA and Exa-DoST leader
- Francieli Boito, Inria and Exa-DoST WP leader
- Silvina Caino-Lores, Inria and member of Exa-DoST
- Damien Chapon, CEA and member of Exa-DoST
- Laurent Colombet, CEA and Exa-DoST WP leader
- Almuhisen Feda, CEA and member of Exa-DoST
- Chiara Ferrari, Observatoire de la Côte d’Azur and Board member of Exa-DoST
- Virginie Grandgirard, CEA and Exa-DoST WP leader
- Damien Gratadour, Université Paris Cité and Exa-DoST WP leader
- Gabriel Hautreux, CINES and board member of Exa-DoST
- Nicolas Lardjane, CEA and board member of Exa-DoST
- Pierre-François Lavallée, CNRS and board member of Exa-DoST
- Jakob Luettgau, Inria and member of Exa-DoST
- Benoit Martin, CEA and member of Exa-DoST
- François Mazen, Kitware and board member of Exa-DoST
- Yann Meurdesoif, CEA and board member of Exa-DoST
- Dorian Midou, CEA and member of Exa-DoST
- Shan Mignot, CNRS and member of Exa-DoST
- Julien Monniot, Inria and member of Exa-DoST
- Thomas Moreau, Inria and Exa-DoST WP leader
- Sai Narasimhamurthy, ParTec and board member of Exa-DoST
- Etienne Ndamlabin, Inria and member of Exa-DoST
- Jean-Francois Nezan, INSA
- Thomas Noël, ANR and Exa-DoST point of contact
- Kevin Obrejan, CEA and member of Exa-DoST
- Guillaume Pallez, Inria and member of Exa-DoST
- Lucas Pernollet, CEA and project manager of NumPEx
- Cédric Prigent, Inria and member of Exa-DoST
- Abhishek Purandare, Inria and member of Exa-DoST
- Bruno Raffin, Inria and Exa-DoST WP leader
- Stéphane Requena, Genci and board member of Exa-DoST
- Kento Sato, Riken and board member of Exa-DoST
- Frederic Suter, CNRS and board member of Exa-DoST
- François Tessier, Inria and Exa-DoST WP leader
- Sunrise Wang, Observatoire de la Côte d’Azur
- Yushan Wang, CEA and Exa-DoST WP leader
© Lucas Pernollet
2023 Inria annual report: NumPEx, a programme aimed at boosting the capacities of exascale computing
The annual report of the French National Institute for Research in Digital Science and Technology (Inria), published last June, provides an overview of the research activities and results of its teams and laboratories. Appointed coordinator of the “Numérique logiciel” program agency in 2024, Inria is a key player in French computer science research. Inria works to ensure that France is part of the European dynamic through the research and innovation of its project teams and collaborations with other research organizations.
Inria’s highlights for 2023 include a panel of France 2030 research programs co-piloted by Inria, including NumPEx!
Find out more on page 10 of the 2023 annual report.
2023 – Annual Report Inria (english version)
2023 – Rapport d’activité Inria (french version)
© Guillaume Martel / CEA
NumPEx Highlighted in GENCI's 2023 Annual Report
In the field of research and innovation, GENCI is a key player in the landscape of high-performance computing (HPC) in France. Established in 2007, its mission is to provide the French scientific community with some of the most powerful HPC resources in the world, including the supercomputers Jean Zay, Joliot Curie, and Adastra. These resources enable scientists to perform complex numerical simulations and analyze massive volumes of data, which are crucial for advancements in various fields such as climatology, particle physics, biology, and much more.
Recently, GENCI published its 2023 activity report, and one of the highlights of the year was the launch of NumPEx!
Find NumPEx on page 20 of the 2023 activity report of GENCI.
2023 – Annual Report GENCI (english version)
2023 – Rapport d’activité GENCI (french version)
© Cyril FRESILLON / IDRIS / CNRS Images
2024 InPEx Workshop
The Barcelona Supercomputing Center and NumPEx were thrilled to gather the InPEx community in Sitges, Spain. From June 17th to June 19th, the workshop brought together around 100 HPC experts from Europe, Japan, and the United States.
This event was the perfect opportunity to discuss about the state of the art, projects and program for Exascale and post-Exascale, to present the lastest achievements of the InPEx working groups since the 2023 Workshop, and to work together about the next steps of InPEx.
If you want to know more, all presentations are available on InPEx website.
Photo credit: Corentin Lefevre/Neovia Innovation/Inria
The first workshop of the NumPEx Accelerator working group
On June 12-13th 2024, the Accelerator working group held the workshop “Programmation GPU” to take a first review of the current situation.
This workshop was the perfect occasion to have a comprehensive overview of the various approaches currently available for an effective use of GPUs, including direct programming, libraries, frameworks, and task-based methods.
The workshop enabled participants to leave with a clear understanding of the advantages and disadvantages of each approach and to benefit from insights and experiences with different codes across these approaches.
You will find below all the presentation materials and video recordings of the day’s events, which were held in French.
Introduction and Context
Both presented by Samuel Thibault, professor at Université de Bordeaux
Overview of GPU approaches
- Approche framework: Arcane, API accélérateur
Gilles Grospellier, CEA researcher - Approche bibliothèque: GPU Programming through external scientific libraries
Florent Pruvost, Inria researcher - Approche langage: Kokkos / OpenMP
Julien Bigot, CEA researcher - Approche tâches, StarPU
Samuel Thibault, professor at Université de Bordeaux
Retex session: feedback and experiences
- Retex – Approche tâches pour l’algèbre linéaire GPU + distribué
Antoine Jego, professor at Sorbonne Université - Retex – Approche tâches pour l’algèbre linéaire GPU + I/O, out-of-core, composition (Chameleon)
Florent Pruvost, Inria researcher - Retex – Approche OpenACC: YALES2
Vincent Moureau, CNRS researcher - Retex – Approche OpenACC: Porting a legacy Fortran CFD HPC code to (AVBP)
Joeffrey Legaux, engineer at CERFACS - Retex – Approche Kokkos: Dyablo, A new hardware-agnostic AMR code for Exascale using Kokkos
Arnaud Durocher, CEA researcher and engineer - Retex – Rust et OpenCL pour le portage GPU (minicl)
Philippe Helluy, professor at Université de Strasbourg
Contributions to the NumPex program and call for proposals
- Contributions prévues au sein du PEPR NumPEx
Samuel Thibault, professor at Université de Bordeaux - Brainstorming on the GPU call for proposals
Title image: © George Kedenburg / Unsplash
NumPEx Launches into Action with an Ambitious Kick-Off Agenda in Perros-Guirrec
In a series of dynamic sessions hosted from June 26th to 28th in the charming town of Perros-Guirrec, NumPEx embarked on an intensive kick-off event, setting the stage for a transformative journey in Exascale computing. Leaders, experts, and collaborators convened to delve into an agenda rich with insights,workshops, and collaborative initiatives.
The kick-off began with a comprehensive introduction, outlining the objectives and significance of the NumPEx program, aiming to establish a common vision and foster collaboration to implement a coherent software stack and related processes by 2025, benefiting not only France but also Europe, in preparation for the Exascale machine. Key figures such as Jerome Bobin, Michel Dayde, and Jean-Yves Berthou elaborated on the program's goals and organizational structure. Board members shared their perspectives on the Exascale vision and roadmaps:
GENCI's Exascale Vision and Roadmap:
- Presentation of GENCI's role and missions, including hosting the Exascale project for EuroHPC.
- European HPC initiative partnership with EuroHPC and others, leveraging PRACE and GEANT.
- Introduction of the Jules Verne consortium, highlighting international and industrial partnerships.
- Vision of the European Exascale machine: addressing societal challenges, fostering innovation, and emphasizing HPC/IA data-centric convergence.
- Collaboration plans with NumPEx, including building a functional program, benchmark development, and product promotion.
Eviden Exascale Vision and Roadmap:
- Eviden's complex approach involving HPC, HPDA, IA, and quantum technologies with a focus on sovereign and European components.
- Involvement in the European integrated processor for Exascale machines (SiPearl) and collaborations with various technology projects.
- Collaboration with CEPP for application support and participation in technology projects related to Exascale, quantum, cloud, and more.
National and European Ecosystem:
- Introduction of EUPEX, a 4-year project with a budget similar to NumPEx, aiming to deploy a modular Exascale system using the OpenSequana architecture.
- Collaboration with NumPEx, potential for shared experiments and results, and exploration of common dissemination.
- Presentation of Data Direct Network (DDN) with a focus on AI and Lustre parallel file system, highlighting challenges and the importance of understanding NumPEx applications.
The afternoon continued with a tour of the five projects (PCs) within the NumPEx program:
- Exa-MA, which aims to design scalable algorithms and numerical methods for forthcoming exascale machines. Led by Christophe Prudhomme (Université de Strasbourg) and Helene Barucq (Inria).
- Exa-Soft, to develop a coherent, portable, efficient, and resilient software stack for exascale. Led by Raymond Namyst (Inria) and Alfredo Buttari (CNRS - Centre national de la recherche scientifique).
- Exa-DoST, to overcome challenges relating to data, notably storage, I/O, in situ processing, and smart analytics, in exascale supercomputers. Led by Gabriel Antoniu (Inria) and Julien Bigot (CEA).
- Exa-ATOW, to deal with large-scale workflows involving exascale machines. Led by François Bodin (Université de Rennes), Mark Asch (Université de Picardie Jules Verne (UPJV)), and Thierry Deutsch (CEA).
- Exa-DI, to ensure transverse co-design and software productivity for exascale supercomputers. Led by Jean-Pierre Vilotte (CNRS) and Valérie Brenner (CEA).
The day concluded with an emphasis on the collaborative efforts between NumPEx and other initiatives, with a focus on benchmark development, software-hardware links, and the overall goal of preparing for the challenges of the Exascale era.
The second day kicked off with an invigorating early morning jog along the seashore, setting a vibrant tone for a day filled with thematic workshops. Participants engaged in focused discussions on energy synergies, GPU integration, applications, co-design, gender/diversity/equity, software production integration, training, resilience, international collaborations, and artificial intelligence. Thematic workshops, led by domain experts, fostered collaboration within smaller groups, emphasizing the program's commitment to a transverse approach to Exascale challenges.
The final day commenced with a synthesis of workshop outcomes, highlighting the depth of discussions within each thematic area. Workshop leaders consolidated insights, offering a panoramic view of challenges and opportunities. Here is an overview of the key insights and strategic actions discussed during these workshops:
GPU Accelerators Workshop
In a dedicated workshop on GPU Accelerators, experts emphasized the pivotal role of Graphics Processing Units (GPUs) in achieving exascale computing. With 90-99% of large machine performance attributed to GPU acceleration, the workshop highlighted the need for applications to explore the potential of these powerful processors. Challenges discussed included new programming paradigms, code portability, data management, and the hardware landscape driven by gaming and artificial intelligence. The workshop outlined a comprehensive plan, including future workshops, analysis papers, tutorials, hackathons, and examples of successfully ported mini-apps.
Energy Workshop
The Energy Workshop focused on achieving Exascale computing within a power consumption limit of 20MW. Experts delved into environmental, scientific, technical, and societal dimensions, providing a roadmap for the HPC community. Key challenges identified included modeling system consumption, real-time measurement tools, resource prioritization based on societal impact, and the broader environmental impact of research activities. The action plan involves developing a performance and consumption model, optimization strategies, tools for users, and fostering links with external entities to incorporate energy considerations.
Gender Equity and Diversity Seminar
The action plan includes the establishment of a Code of Conduct, assessment of gender distribution, creation of a web platform for resources, education and training initiatives, awareness and outreach programs, and dedication to accessibility and recognition. NumPEx aims to create an inclusive and collaborative future, inviting all stakeholders to contribute to the initiatives.
AI Workshop
The AI Workshop explored the critical intersection of HPC and AI, addressing challenges and outlining a strategic plan for collaborative exploration. Key discussions included decision support tools for AI applications in HPC, optimizing runtimes for AI models, and converging HPC and AI usages. The action plan involves establishing an AI Working Group, conducting transversal workshops, and developing fundamental building blocks for a convergent future.
Training Strategies Workshop
The Training Strategies Workshop addressed the complexities of training in the context of the impending exascale era. Discussions included the scope and subjects of training programs, the creation of sustainable training models, and economic considerations in training initiatives. The workshop emphasized collaborative and inclusive training initiatives to prepare the scientific community for the challenges and opportunities of exascale computing.
International Collaborations Workshop
The International Collaborations Workshop focused on identifying challenges and setting objectives for enhanced collaborative frameworks on a European and global scale. Discussions covered scientific and technological challenges, the design and development of the exascale software stack, and strategic action plans. The outlined roadmap includes hosting workshops, exchanging insights and experiences, and strengthening collaborations with international entities.
National Centers Integration Workshop
The National Centers Integration Workshop aimed to align NumPEx with HPC infrastructures, emphasizing operational elements between computing centers and NumPEx 's targeted projects. Discussions covered operational assessment, cybersecurity, job profiling, and traceability. The workshop set a plan for regular video conferences, ensuring ongoing communication and collaboration.
Software Production Workshop
The Software Production Workshop focused on streamlining software development practices in the HPC domain. Challenges discussed included bridging silos, enforcing good practices, and amplifying impact. Insights and conclusions highlighted diverse development practices, sustainability models, and the deployment of continuous integration and certification. NumPEx 's commitment to advancing software production practices aims to foster innovation, collaboration, and sustainable development in HPC.
Exascale Resilience Workshop
The Exascale Resilience Workshop navigated complexities associated with exascale application deployment. Discussions covered diverse approaches across NumPEx PCs, key challenges, and strategic choices. The action plan involves listing and analyzing application needs, analyzing barriers to library adoption, and scrutinizing international solutions. NumPEx aims to foster collaborative solutions for enhanced application resilience at a global scale.
Applications and Co-Design Workshop
The Applications and Co-Design Workshop promoted co-development strategies for advanced application development. Discussions included challenges in co-design, key questions for collective exploration, building connections, and initiatives for sustainability. The workshop set the stage for upcoming co-development project workshops, emphasizing collaboration and innovation.
As the leaders bid farewell to Perros-Guirrec, NumPEx looks ahead to transforming shared visions and insights into tangible actions in the realm of Exascale computing. The kick-off marked the initiation of a collaborative journey, and NumPEx is poised to lead the charge in scientific innovation.
For the latest updates and progress on the NumPEx program, stay tuned to our news section. The journey to Exascale has begun, and NumPEx is at the forefront of this pioneering expedition.
What is exascale ?
In today’s world, information has become an essential resource. Massive amounts of data are produced every day, from various sources such as social networks, sensors, scientific simulations, and many more. To efficiently process this data and meet the complex challenges of our time, it is crucial to have powerful computing capabilities.
This is where exascale comes in. Exascale is a measure of computing power that represents one trillion (10^18) floating point operations per second, or one million billion calculations per second. This performance is simply astounding and far exceeds that of all existing supercomputers.
Discover the exascale: The computing power of the future
The race to exascale :
Since the first electronic computers, the computing power of machines has grown exponentially thanks to the advancement of technologies. As computational demands grew more complex, researchers and engineers set themselves the goal of achieving exascale. This has given rise to a veritable race for innovation in the field of supercomputers.
Technological challenges :
Achieving exascale is not just about increasing the speed of processors. This requires a multidimensional approach that integrates several research areas. One of the main challenges is to design more energy-efficient processors capable of processing billions of calculations while minimizing power consumption.
In addition, the architecture of supercomputers must be redesigned to fully exploit the performance of processors. Parallel and distributed architectures, as well as the use of specialized processors like graphics accelerators (GPUs), play a key role in achieving exascale.
Exascale applications :
The exascale opens the way to many possibilities in various fields. In science and research, it will enable more accurate and faster simulations, enabling significant advances in fields such as medical research, meteorology, materials physics, astrophysics and many more.
Exascale is also essential for the development of artificial intelligence and machine learning. Deep learning models, which require massive amounts of data and computation, will be able to be trained much faster, enabling faster advancements in these areas.
