What Is

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?

The Trillion Parameter Consortium (TPC) is a global, community-driven, open initiative that brings together researchers, technical practitioners, educators, trainees, and other stakeholders working across the fields of AI and HPC. There are currently 82 active member organizations within TPC, and all organizations are encouraged to apply for membership.

What Is

tpc-logotype-w-1200

?

Established in 2023, the TPC community has grown to more than 1,400 participants from over 100 organizations around the world.

Participants include computer scientists, mathematicians, and computational scientists; domain experts from astronomy, physics, chemistry, biology, environment, materials, and climate science; and experts in large-scale computing systems, computational frameworks, data management, ethical considerations, and responsible AI practices. 

TPC aims to advance and accelerate the responsible, open, and safe development of large-scale AI capabilities for scientific and engineering applications. Its community represents the intersection of AI and HPC, encompassing not only the science of AI and the use of AI for scientific discovery, but also the challenges of harnessing the necessary extreme scale systems spanning data and computation.

As the community continues to grow, participants from around the world are empowered to contribute knowledge, propose projects, and work together in pursuit of scientific breakthroughs, inspiring future leaders and advancing discovery in ways that would be difficult or impossible through isolated efforts.

Photo: TPC European Kickoff Workshop in Barcelona, Spain

TPC Has Three Overarching Objectives for AI in Science and Engineering:

1.
Building an Open Community
2.
Identifying, Incubating, and Facilitating
3.
Creating a Global Network of Expertise and Resources

The TPC community pursues these objectives in alignment with scientific and government guidelines, with a commitment to open collaborations that accelerate the development of scientific AI capabilities and are characterized by:

Leadership

TPC is guided by an executive committee, a technical steering group, and a planning team — all comprising leaders from around the world. The executive committee was formed by TPC founders from North America (Rick Stevens, Argonne National Laboratory and The University of Chicago, USA), Asia-Pacific (Satoshi Matsuoka, RIKEN,  Japan), and Europe (Mateo Valero, Barcelona Supercomputing Center, Spain).

An additional 22 leaders serve on the planning team and technical steering group, which are led by regional co-chairs. The planning team co-chairs are Charlie Catlett (USA), Fabrizio Gagliardi (Spain), and Kyoung-Sook Kim (Japan), while the technical steering group co-chairs are Ian Foster (USA), Laura Morselli (Italy), and Rio Yokota (Japan).

TPC Planning Team

Thierry Bidot (Inria, France)

Jerome Bobin (CEA , France)

Charlie Catlett (Argonne National Laboratory and The University of Chicago, USA)

Karthik Duraisamy (University of Michigan, USA)

Nick Jones (NESI, New Zealand)

Fabrizio Gagliardi (Barcelona Supercomputing Center, Spain)

Nicolay Hammer (Leibniz Supercomputing Centre, Germany)

Kyoungsook Kim (AIST, Japan)

Taiji Makoto (RIKEN, Japan)

Per Oster (CSC, Finland)

Noah Smith (University of Washington and Allen Institute for AI, USA)

Samantika Sury (HPE, USA)

Valerie Taylor (Argonne National Laboratory and The University of Chicago, USA)

TPC Technical Steering Group

Javier Aula-Blasco (BSC, Spain)

Franck Cappello (Argonne, USA)

Jens Domke (RIKEN, Japan)

Ian Foster (Argonne, USA)

Neeraj Kumar (PNNL, USA)

Laura Morselli (CINECA, Italy)

Arvind Ramanathan (Argonne, USA)

Miguel Vazquez (BSC, Spain)

Mohamed Wahib (RIKEN, Japan)

Rio Yokota (IS Tokyo, Japan)

TUTORIAL CHAIRS FOR TPC25

Neeraj Kumar (PNNL), Samantika Sury (HPE), Laura Morselli (CINECA), and Prasanna Balaprakash (ORNL)

HACKATHON CHAIRS FOR TPC25

Miguel Vazquez (BSC), Arvind Ramanathan (ANL), and Mohamed Wahib (RIKEN)

For more information, please see the TPC Introduction and Structure white paper.

What Does TPC Hope to Achieve?

As the community’s interest in large-scale AI for science and engineering accelerates, TPC will:

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