List of participants

Jan Brandejs

Jan Brandejs is a postdoc in the group of Trond Saue specializing on tensor software and code generation for quantum chemistry applications. His main task in the ERC advanced project HAMP-vQED is the creation of programming environment for elegant development of relativistic coupled-cluster methods using distributed memory tensor software for HPC platforms of today.

Paolo Bientinesi

Paolo Bientinesi is professor in High-Performance Computing, and the director of the High-Performance Computing Center North. One of Paolo's research goals is the automatic generation of algorithms and code for linear algebra operations. Together with his research group (HPAC), he has contributed many algorithms and libraries for a range of common tensor operations. hpac.cs.umu.se

Trond Saue

Trond Saue is a CNRS researcher at the Laboratoire de Chimie et Physique Quantiques (Toulouse, France). His current research focuses on the accurate calculation of molecular properties using relativistic coupled cluster theory with the inclusion of QED effects. He is one of the main authors of the Dirac program.

Lucas Visscher

Lucas Visscher is professor in Quantum Chemistry and Multiscale Modeling at the Vrije Universiteit Amsterdam. He works on developing electronic structure methods with a focus on the description of electronically excited states. His interest in tensor operations arises from his work on coupled cluster theory and quantum computing algorithms.

André Severo Pereira Gomes

Andre Gomes is a CNRS researcher at the “Laboratoire de Physique des Lasers, Atomes et Molecules” (Lille, France). His activities focus on the development of electronic structure methods which take into account relativistic effects, electron correlation (primarily with coupled cluster theory) and environment effects (via embedding methods), and their application to simulating molecules containing heavy elements. He is one of the authors of the DIRAC code.

Devin Matthews

Devin Matthews is an Assistant Professor of Chemistry at Southern Methodist University. His research interests are in electronic structure theory (primarily using coupled cluster methods), computational soft x-ray spectroscopy, tensor factorizations for reduced scaling, and high-performance computing/dense linear algebra. He is one of the authors of the CFOUR program suite.

Edward Valeev

Ed Valeev is Professor of Chemistry at Virginia Tech (Blacksburg, VA, USA). His primary research interests is the development of predictive electronic structure methods with robust control of numerical errors and reduced complexity. Motivated by the needs of such development the Valeev group has been developing a number of software components (Libint(X), TiledArray, MADNESS, SeQuant, BTAS) and as well as leading or contributing to several quantum chemistry packages. Of particular relevance to this workshop are two of such tools: TiledArray, a block-sparse tensor algebra framework for modern distributed accelerated HPC platforms, and SeQuant, a computer algebra system for tensor algebra. In concert they allow rapid composition of conventional and reduced scaling many-body methods.

Jeff Hammond

Jeff Hammond is a Principal Engineer at NVIDIA. He has worked on a wide range of HPC software and hardware projects related to distributed computing, parallel programming models, and numerical algorithms. Jeff received a PhD from the University of Chicago for the implementation and application of coupled-cluster response theory in NWChem.

Jiajia Li

Jiajia Li is an Assistant Professor in the Department of Computer Science at North Carolina State University (NCSU), USA. Her research focuses on high-performance tensor computation, particularly the interaction among applications, numerical methods, data structures, algorithms, and computer architectures.

Grzegorz Kwasniewski

Grzegorz Kwasniewski is a Mathematical Libraries Engineer at NVIDIA. He received a PhD at ETH Zurich. His work spans both theoretical and practical aspects of HPC, mostly related to (distributed) linear algebra and data movement optimal algorithms. The applications of interest range from dense linear algebra to "classical" scientific applications and (sparse) distributed LLM training and inference.

Justin Turney

Justin Turney is a Senior Research Scientist the University of Georgia in the Center for Computational Quantum Chemistry. His research focuses on theory and code development applicable to combustion related reactions.

Alexander Heinecke

Alexander Heinecke studied Computer Science and Finance and Information Management at Technische Universität München, Germany. In 2010 and 2012, he completed internships in the High Performance and Throughput Computing team at Intel, Munich, Germany and at Intel Labs Santa Clara, CA, USA, working on the Intel MIC architecture. In 2013 he finished his Ph.D. studies at Technische Universität München, Germany. He joined Intel's Parallel Computing Lab in Santa Clara, CA, USA in 2014 as Research Scientist. His core research field is in building a deep knowledge of hardware-aware multi/many-core computing in scientific computing and deep learning. Applications under investigation are complexly structured, normally adaptive, numerical methods which are quite difficult to parallelize. Special focus is hereby given to deep learning primitives such as CNN, RNN/LSTM, Transformers & MLPs and as well to their use in applications ranging from various ResNets to GPTs in GenAI.

Christopher Millette

Chris Millette is a technical lead and development manager at AMD that focuses on implementing GPU libraries for matrix multiplication and tensor primitives. He is a principal contributor to rocWMMA and hipTensor projects for the ROCm software stack, and is highly interested in accelerating applications via instruction and data-level parallelism.

Willow Ahrens

Willow Ahrens is an Assistant Professor of Programming Languages at the Georgia Institute of Technology. Her focus is domain specific languages for high performance computing. She is the developer of Finch, a sparse and structured tensor programming language and compiler. Finch has been adopted as the compiler backend for the pydata/sparse python library. Willow received her Ph.D. from MIT, advised by Saman Amarasinghe. willowahrens.io

Ryan Richard

Ryan Richard is a staff scientist at Ames National Laboratory and an adjunct assistant professor of chemistry at Iowa State University. Ryan is the lead developer of NWChemEx, a software environment for developing reusable, modular, and high-performance quantum chemistry tools. A key component of this ecosystem is the TensorWrapper library, which strives to decouple writing a tensor equation from how to performantly solve it. This is done by treating existing high-performance tensor libraries as "physical" layouts and the equation the user writes as a "logical" layout. The guiding design goal of TensorWrapper is for the library to use runtime information about the system and the tensors to choose the ideal mapping from logical layout to physical layout, though admittedly this process is at present entirely manual.

Anthony Scemama

HPC research engineer. Developer of quantum chemistry programs (Quantum Package, QMC=Chem, ..) and libraries (QMCkl, TREXIO, ...). scemama.githib.io

Jutho Haegeman

Jutho Haegeman is a professor in quantum many-body physics in the quantum group at Ghent University. Our group develops open-source tensor network packages using the Julia programming language (quantumghent.github.io), with a strong emphasis on exploiting symmetries and studying exotic phases of quantum matter.

 

Sarai Dery Folkestad

Working as an associate professor at the Norwegian University of Science and Technology. I am interested in development and implementation of electronic structure models and I am a developer of the eT program.

Nicolas Renon

CTO of Toulouse University Computing Center.

Michał Lesiuk

Michał Lesiuk is a Assistant Professor at Faculty of Chemistry, University of Warsaw, working on development of electronic structure methods based on tensor decomposition techniques (group webpage: aesmgroup.chem.uw.edu.pl).

Alex Breuer

Alex Breuer leads the Scalable Data- and Compute-intensive Analyses lab. His research and teaching activities cover the full spectrum of algorithms and software for modern and emerging hardware. In 2014, Alex was honored with an ACM/IEEE-CS George Michael Memorial HPC Fellowship for his Ph.D. project “High Performance Earthquake Simulations”. In addition, he and his collaborators have been awarded with the PRACE ISC Award and nominated as ACM Gordon Bell finalists. Alex holds a doctoral degree from the Technical University of Munich.

Örs Legeza

Örs Legeza is a professor at Wigner Research Centre for Physics and a Hans Fischer Senior Fellow at the Institute for Advanced Studies at the Technical University of Munich. His research interests focus on the development of novel tensor network state (TNS) methods and their application to strongly correlated quantum many-body systems to simulate and study magnetic properties in solid states, exotic quantum phases, complex molecular clusters, ultracold atomic systems, and nuclear structures. For the method development he combines established methods for simple networks (MPS, MERA, tensor trees) with concepts from quantum information theory and computational mathematics to push the current frontier of moderate system size to much larger and more complex systems via simulations on high performance computing infrastructures.

Juraj Hasik

Juraj Hasik is a postdoc at the University of Zurich, within the Quantum Matter Group led by prof. Neupert. His research centers on the development and application of tensor network methods to study strongly correlated systems in two dimensions. He develops peps-torch and YASTN libraries, which are designed to optimize two-dimensional (symmetric) tensor networks.

 

Matthieu Mambrini

Matthieu Mambrinbi is a CNRS researcher at the Laboratoire de Physique Théorique (Toulouse, France). His research focuses on quantum magnetism and spin liquids using various numerical methods. He is involved in tensor network methods and more particularly in the PEPS scheme, in a context where continuous (e.g. SU(N)) and discrete (e.g. point group) symmetries play a central role.

Kalman Szenes

Kalman Szenes is a PhD student in the theoretical chemistry group of Prof. Markus Reiher at ETH, Zurich. He is one of the developers of the QCMaquis density matrix renormalization group program. His research focuses on method development for electronic structure calculations on strongly correlated molecules. Personal webpage: kszenes.github.io

 

Andreas Irmler

Andreas Irmler is a postdoctoral researcher at TU in Vienna. As a member of Andreas Gruneis' group, his work focuses on developing new theoretical methods and computational implementations for large-scale coupled-cluster calculations. He is a co-author of the coupled-cluster code CC4S, which enables massively parallel computations across hundreds of compute nodes.

Marco Trenti

Marco Trenti is the CTO of Tensor AI Solutions, a startup focused on Explainable AI (XAI) and tensor network methods. His main work involves developing high-performance computing (HPC) algorithms for tensor network machine learning (TNML) and researching their applications in data science, quantum computing, quantum simulations, and industrial problems. He is particularly interested in specific contraction patterns and tensor algebra kernels that appear in TNML.

Alejandro Estaña

HPC and AI Research Engineer in the Application Support Team at CALMIP Computing Center.