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Dr Giuseppe Barca

Lecturer
Hanna Neumann Blg (145), 4.16

» read more about Dr Giuseppe Barca

I am a Lecturer of High-Performance Computing (HPC) in the School of Computing at the Australian National University (ANU). 

 

I hold a leadership role in large multi-institutional partnerships encompassing world-leading Australian and US universities, supercomputing facilities, and IT corporations. I am the leader of one of the Pawsey Centre for Extreme-scale Computing (PaCER) projects, the lead of GPU development for the GAMESS Exascale Computing Project, and the lead of a collaboration in HPC between the ANU, the National Computational Infrastructure and the RIKEN supercomputing centre in Japan.

 

In 2020, 2021 and 2022, using my algorithms on the fastest supercomputer on the planet, I broke the world record for the largest computational-driven quatum molecular modelling of material structure, setting new standards in HPC, and enabling the accurate molecular modelling of matter at unprecedented scales.

 

In 2023, the translational nature of my research led to spinning out QDX Technologies, a deep-tech drug discovery company of which I am co-founder and Head of Research. 

 

 

Research

My research focuses on advancing translational digital technologies that harness the power of high-performance computing (HPC) and artificial intelligence (AI) to enhance, simplify, or even replace physical experimentation in research and development (R&D). 

The focus is the development of high-performance algorithms, machine learning (ML) models and software artefacts that can efficiently use state-of-the-art supercomputing technology, including the world’s top supercomputers, to simulate and predict the physicochemical behaviour of matter at unprecedented molecular scales, and with an accuracy that rivals or surpasses physical experiments.

This digitalization of physical experiments is poised to unlock a radical new R&D era in chemistry, biology, materials, and many other related fields of science. The matter simulations enabled by my research agenda are as accurate as physical experimentation, but faster, cheaper, more versatile, and fully automatable. By integrating high-performance matter simulations in automated pipelines, and by augmenting them with machine learning models that are trained to guide and inform problem-specific resolution strategies, we can accelerate the progress of all physical sciences.

Current group members

Dr Jorge Galvez-Vallejo, Research Fellow

Dr Andrew Gilbert, Research Adjunct

Elise Palethorpe, Research Assistant

Fiona Yu, PhD student

Fazeleh Kazemian, PhD student

Calum Snowdon, PhD student

Ryan Stocks, Teaching assistant

Jack Miller, Project student

Jack Carey, Honours student

Joshua Singla, Project student

Xin Lu, Project student

 

PhD and other projects under my supervision

I am always seeking talented students for Honours and PhD positions within my group. 

Concerning PhD positions, at the moment fully funded scholarships are available as well as top-up scholarships based on merit.

 

If you are interested in joining my group, please read the following guidelines to express your interest.

  1. First, familiarise either with the ANU requirements for Honours entry or with the ANU requirements for PhD/MPhil entry.
  2. If you are an ANU undergraduate or masters' student interested in Honours, I have various existing projects ideas in HPC and computational science: please refer to  student projects tab on this page to confirm your interest in my research. Projects are not limited to the ones listed on the student projects tab: As long as it aligns with my research directions, I am also happy for you to propose your own project. Therefore, email me to express your interest, including background information (e.g., courses taken, academic transcript, and programming skills) and a concise statement about the research that you would like to undertake.
  3. If you are a prospective PhD student: I expect you to have excellent programming and mathematical skills, preferably with some prior experience in scientific computation and/or HPC. You should have good English proficiency, strong programming skills in C/C++, some familiarity with MPI, OpenMP and/or CUDA, and with version control (GitHub or SVN). If you meet these requirements, email me to express your interest!
  4. How to apply for a PhD position: After reading paragraph 3, write your email with care, avoiding carelessness or obvious mistakes. Include in the email background information (e.g., courses taken, academic transcript, and programming skills) and a concise statement about your motivation to undertake a PhD under my supervision. Based on your email, I will decide whether we can proceed with an interview.

Postdoctoral openings

I have no current postdoctoral openings.

 

 

I am the convener and lecturer of the COMP4300/83200 course on Parallel Sytems https://comp.anu.edu.au/courses/comp4300/

I am the co-convener and lecturer of the COMP3320/6464 course on High Performance Scientific Computation https://programsandcourses.anu.edu.au/2021/course/comp3320

My research focuses on advancing translational digital technologies that harness the power of high-performance computing (HPC) and artificial intelligence (AI) to enhance, simplify, or even replace physical experimentation in research and development (R&D). 

The focus is the development of high-performance algorithms, machine learning (ML) models and software artefacts that can efficiently use state-of-the-art supercomputing technology, including the world’s top supercomputers, to simulate and predict the physicochemical behaviour of matter at unprecedented molecular scales, and with an accuracy that rivals or surpasses physical experiments.

This digitalization of physical experiments is poised to unlock a radical new R&D era in chemistry, biology, materials, and many other related fields of science. The matter simulations enabled by my research agenda are as accurate as physical experimentation, but faster, cheaper, more versatile, and fully automatable. By integrating high-performance matter simulations in automated pipelines, and by augmenting them with machine learning models that are trained to guide and inform problem-specific resolution strategies, we can accelerate the progress of all physical sciences.

Please refer to the Student projects section or to the group website (www.gbarca.com) for more information on research projects and current openings.

  • G. M. J. Barca, M. Alkan, J. L. Galvez Vallejo, D. Poole, A. P. Rendell, and M. S. Gordon, Faster Self-Consistent Field Calculations on GPU Clusters, Journal of Chemical Theory and Computation, 2021, 17, 12, 7486-7503.

  • G. M. J. Barca, J. L. Galvez Vallejo, M. Alkan, D. Poole, R. Stocks, A. P. Rendell, and M. S. Gordon, Enabling large-scale correlated electronic structure calculations: scaling the RI-MP2 method on Summit, SC21: International Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2021, Article no 40, pp 1-15.

  • T. Tran-Phu, Z. Fusco, I. Di Bernardo, J. Lipton-Duffin, C. Ying Toe, R Daiyan, T. Gengenbach, C.-H. Lin, R. Bo, H. T. Nguyen, G. M. J. Barca, T. Wu, H. Chen, R. Amal, A. Tricoli, Understanding the Role of Vanadium Vacancies in BiVO4 for Efficient Photoelectrochemical Water Oxidation,  Chemistry of Materials, 2021, 33, 10, 3553.

  • G. M. J. Barca, J. L. Galvez Vallejo, D. Poole, A. P. Rendell, and M. S. Gordon, A High-Performance GPU-Accelerated Fock Build Algorithm, Journal of Chemical Theory and Computation, 2020, 16, 12, 7232-7238. 

  • G. M. J. Barca,  D. Poole, J. L. Galvez Vallejo, M. Alkan, C. Bertoni, A. P. Rendell, and M. S. Gordon, Scaling the Hartree-Fock Matrix Build on Summit ,in 2020 SC20: International Conference for High Performance Computing, Networking, Storage and Analysis (SC), Atlanta, GA, US, 2020 pp. 1141-1154.

  • M. S. Gordon, G. M. J. Barca, S. S. Leang,  D. Poole, A. P. Rendell, J. L. Galvez Vallejo and B. Westheimer, Novel Computer Architectures and Quantum Chemistry, Journal of Physical Chemistry A, 2020, 124, 23, 4557-4582. Obtained the journal cover

  • Giuseppe M. J. Barca, C. Bertoni, L. Carrington, D. Datta, [...], and Mark S. Gordon, Recent developments in the general atomic and molecular electronic structure system, Journal of Chemical Physics, 2020, 152, 154102.

  • Giuseppe M. J. Barca, Simon C. McKenzie, Nathaniel Bloomfield, Andrew T. B. Gilbert, and Peter M. W. Gill, Q-MP2-OS: Møller–Plesset Correlation Energy by Quadrature, Journal of Chemical Theory and Computation, 2020, 16, 3, 1568.

  • Simon C. McKenzie, Evgeny Epifanovsky, Giuseppe M. J. Barca, Andrew T. B. Gilbert, and Peter M. W. Gill, Efficient Method for Calculating Effective Core Potential Integrals, The Journal of Physical Chemistry A, 2018, 122, 3066-3075.

  • Giuseppe M. J. Barca, Andrew T. B. Gilbert, and Peter M. W. Gill, Simple Models for Difficult Electronic Excitations, Journal of Chemical Theory and Computation, 2018, 14, 1501-1509.

  • Giuseppe M. J. Barca, Andrew T. B. Gilbert, and Peter M. W. Gill, Excitation Number: Characterizing Multiply Excited States, Journal of Chemical Theory and Computation, 2018, 14, 9-13.

  • Giuseppe M. J. Barca, and Pierre-Francois Loos, Three- and four-electron integrals involving Gaussian geminals: fundamental integrals, upper bounds, and recurrence relations, The Journal of Chemical Physics, 2017, 147, 024103.

  • Giuseppe M. J. Barca, and Pierre-Francois Loos, Recurrence Relations for Four-Electron Integrals Over Gaussian Basis Functions, Advances in Quantum Chemistry, 2018, 76, 147-165.

  • Giuseppe M. J. Barca, Pierre-Francois Loos, and Peter M. W. Gill, Many-Electron Integrals over Gaussian Basis Functions. I. Recurrence Relations for Three-Electron Integrals, Journal of Chemical Theory and Computation, 2016, 12, 1735-1740.

  • Giuseppe M. J. Barca, and Peter M. W. Gill, Two-Electron Integrals over Gaussian Geminals, Journal of Chemical Theory and Computation, 2016, 12, 4915-4924.

  • Gianpiero Pataro, Giuseppe M. J. Barca, Giorgio Donsi, and Giovanna Ferrari, On the modelling of electrochemical phenomena at the electrode-solution interface in a PEF treatment chamber: methodological approach to describe the phenomenon of metal release, Journal of Food Engineering, 2015, 165, 34-44.

  • Gianpiero Pataro, Giuseppe M. J. Barca, Giorgio Donsi, and Giovanna Ferrari, On the modelling of the electrochemical phenomena at the electrode-solution interface of a PEF treatment chamber: effect of electrical parameters and chemical composition of model liquid food, Journal of Food Engineering, 2015, 165, 45-51.

  • Giuseppe M. J. Barca, Andrew T. B. Gilbert, and Peter M. W. Gill, Communication: Hartree-Fock description of excited states of H2, The Journal of Chemical Physics, 2014, 141, 111104.

  • Gianpiero Pataro, Giuseppe M. J. Barca, Ricardo N. Pereira, Antonio A. Vicente, Jose A. Teixeira, and Giovanna Ferrari, Quantification of metal release from stainless steel electrodes during conventional and pulsed ohmic heating, Innovative Food Science & Emerging Technologies, 2014, 21, 66-73.

I regularly review for the Journal of Chemical Theory and Computation and for the Journal of Chemical Physics.

  • 2022 Chair of the ANU Merit Allocation Scheme (ANUMAS) committee for the allocation of computational resources at the National Computational Infrastructure (NCI).

  • 2021 member of the ANU Merit Allocation Scheme (ANUMAS) committee for the allocation of computational resources at the National Computational Infrastructure (NCI).

  • 2020 member of the ANU Merit Allocation Scheme (ANUMAS) committee for the allocation of computational resources at the National Computational Infrastructure (NCI).

  • 2021 member of the program commitee for IEEE International Workshop on Parallel and Distributed Scientific and Engineering Computing (PDSEC 2021)

Updated:  10 August 2021/Responsible Officer:  Dean, CECS/Page Contact:  CECS Marketing