Organisers

• Nick R. Papior
  Technical University of Denmark, Denmark
• Micael Oliveira
  Max Planck Institute for the Structure and Dynamics of Matter, Hamburg, Germany
• Yann Pouillon
  Universidad de Cantabria, Spain
• Volker Blum
  Duke University, Durham, NC, USA, USA
• Fabiano Corsetti
  Synopsys QuantumWise, Denmark
• Emilio Artacho
  University of Basque Country, United Kingdom

Description

The evolutionary pressure on electronic structure software development is greatly increasing, due to the emergence of new paradigms, new kinds of users, new processes, and new tools. Electronic structure software complexity is consequently also increasing, requiring a larger effort on code maintenance. Developers of large electronic structure codes are trying to relieve some complexity by transitioning standardized algorithms into separate libraries [BigDFT-PSolver, ELPA, ELSI, LibXC, LibGridXC, etc.]. This paradigm shift requires library developers to have a hybrid developer profile where the scientific and computational skill set becomes equally important. These topics have been extensively and publicly discussed between developers of various projects including ABINIT, ASE, ATK, BigDFT, CASTEP, FHI-aims, GPAW, Octopus, Quantum Espresso, SIESTA, and SPR-KKR.

High-quality standardized libraries are not only a highly challenging effort lying at the hands of the library developers, they also open possibilities for codes to take advantage of a standard way to access commonly used algorithms. Integration of these libraries, however, requires a significant initial effort that is often sacrificed for new developments that often not even reach the mainstream branch of the code. Additionally, there are multiple challenges in adopting new libraries which have their roots in a variety of issues: installation, data structures, physical units and parallelism – all of which are code-dependent. On the other hand, adoption of common libraries ensures the immediate propagation of improvements within the respective library’s field of research and ensures codes are up-to-date with much less effort [LibXC]. Indeed, well-established libraries can have a huge impact on multiple scientific communities at once [PETSc].

In the Electronic Structure community, two issues are emerging. Libraries are being developed [esl, esl-gitlab] but require an ongoing commitment from the community with respect to sharing the maintenance and development effort. Secondly, existing codes will benefit from libraries by adopting their use. Both issues are mainly governed by the exposure of the libraries and the availability of library core developers, which are typically researchers pressured by publication deliverables and fund-raising burdens. They are thus not able to commit a large fraction of their time to software development.

An effort to allow code developers to make use of, and develop, shared components is needed. This requires an efficient coordination between various elements:

– A common and consistent code development infrastructure/education in terms of compilation, installation, testing and documentation.
– How to use and integrate already published libraries into existing projects.
– Creating long-lasting synergies between developers to reach a “critical mass” of component contributors.
– Relevant quality metrics (“TRLs” and “SRLs”), to provide businesses with useful information .

This is what the Electronic Structure Library (ESL)[esl, esl-gitlab] has been doing since 2014, with a wiki, a data-exchange standard, refactoring code of global interest into integrated modules, and regularly organizing workshops, within a wider movement lead by the European eXtreme Data and Computing Initiative [exdci].

References

[BigDFT-PSolver] http://bigdft.org/Wiki/index.php?title=The_Solver_Package
[ELPA] https://gitlab.mpcdf.mgp.de/elpa/elpa
[ELSI] http://elsi-interchange.org
[LibXC] http://www.tddft.org/programs/libxc/
[LibGridXC] https://launchpad.net/libgridxc
[PETSc] https://www.mcs.anl.gov/petsc/
[esl] http://esl.cecam.org/
[esl-gitlab] http://gitlab.e-cam2020.eu/esl
[exdci] https://exdci.eu/newsroom/press-releases/exdci-towards-common-hpc-strategy-europe

Organisers 

• Jony Castagna
  STFC Daresbury Laboratory, United Kingdom
• Simon Wong
  Irish Centre for High-End Computing, Ireland
• Donal MacKernan
  University College Dublin, Ireland

Overview 

The 4-day school will focus on providing the participants with a concise introduction to key machine and deep learning (ML & DL) concepts, and their practical applications with relevant examples in the domain of molecular dynamics (MD), rare-event sampling and electronic structure calculations (ESC). ML is increasingly being used to make sense of the enormous amount of data generated every day by MD and ESC simulations running on supercomputers. This can be used to obtain mechanistic understanding in terms of low-dimensional models that capture the crucial features of the processes under study, or assist in the identification of relevant order parameters that can be used in the context of rare-event sampling. ML is also being used to train neural network based potentials from ESC which can then be used on MD engines such as LAMMPS allowing orders of magnitude increase in the dimensionality and time scales that can be explored with ESC accuracy. So while the first half of this school will cover the fundamentals of ML and DL, the second half will be dedicated to relevant examples of how these techniques are applied in the domains of MD and ESC.

Learning outcomes 

By the end of the school, participants are expected to:

• Gain an understanding of the fundamental concepts of ML and DL, including how neural networks function, different types of topologies, common pitfalls, etc.
• Be able to implement basic deep learning workflows using Python.
• Leverage existing framework to discover molecular mechanisms from MD simulations.
• Utilise the PANNA[1,2] toolkit to create neural network models for atomistic systems and generate results that can be integrated with MD packages.

Prerequisites 

Participants are expected to have a working knowledge of Python (i.e. familiar with the basic syntax and constructs, have used Python before for at least a few months) and have a basic understanding of the fundamental physics behind molecular dynamics simulations and electronic structure calculations. All participants are expected to bring his/her own laptop to the school to conduct hands-on exercises.

Registration 

There is no registration charge for accepted participants. However, all participants must register via the webpage  https://events.prace-ri.eu/event/995 and due to limited space, in the event of high demand, participants will be selected according to expressions of interest  provided.

Non-academic participants are welcome to register to the school but should notify the organisers in order to pre-empt issues with third party copyright material that will be used for parts of the school.

Organisers

• Donal Mackernan
  University College Dublin, Ireland
• Brian Glennon
  University College Dublin & SSPC, Ireland
• Erik Santiso
  North Carolina State University, USA
• Fernando Luís Barroso da Silva
  University of São Paulo, Brazil

Description 

Event Postponed – new dates not yet available. Alternative options, such as virtual meetings, are also being considered. Information will be promptly updated on this page and on the CECAM website for the event at https://www.cecam.org/workshop-details/10.

The thermodynamic constraints which best reflect the conditions of many experiments and industrial processing correspond to fixed chemical potentials, pressure and temperature where particle number can fluctuate (from a statistical perspective this is known as the “Grand Canonical Ensemble”), rather than fixed particle number, pressure and temperature, yet most simulation methods in the condensed phase enforce the latter. For instance, many activated processes of relevance to the chemical and pharmaceutical industries occur at constant concentration, e.g. crystallization usually happens at constant supersaturation (Liu et al. 2018, Perego et al. 2015); catalysis usually involves porous materials, where, if diffusion is fast compared to reaction, the appropriate ensemble is the grand canonical. Chemical reactions in solution usually happen at a given concentration of reactants, and many biological processes, to be understood properly, need to be modeled at constant-pH (CpH) (Barroso da Silva and Dias, 2017; Barroso Da Silva and Jönsson, 2009; de Vos et al., 2010; Jönsson et al., 2007; Kirkwood and Shumaker, 1952). The binding free energy of proteins onto nano surfaces such as titanium dioxide, can depend on the local charge on the surface due to the binding, for example, of hydroxyl ions, which in turn depends on the relative concentrations of hydroxyl ions in water and cannot be fully described in systems where particle number cannot fluctuate. Similarly, the binding of antibodies to antigens or nanocarriers (in the context of drug delivery systems) strongly depends on electrostatic effects (Gunner and Baker, 2016; Han et al., 2010; Ivanov et al., 2017; Li et al., 2015; Poveda-Cuevas et al., 2018). These sorts of effects are important for nano-toxicology, food processing, immuno-diagnostics, and drug delivery. Their study through simulation is further complicated when large free energy barriers exist between key metatable states corresponding, for example, to bound and unbound configurations configurations of a ligand to a binding site; or a crystal phase and an amorphous phase; or folded and unfolded protein;or different charge configuration of titratable sites of pH-sensitive proteins in solution (Barroso da Silva and MacKernan, 2017; Barroso da Silva et al., 2019, p. 6; Barroso Da Silva and Jönsson, 2009; Jönsson et al., 2007).
In recent years there have been many developments on methods to study rare events, but these methods usually rely on biasing molecular dynamics with fixed particle number, and are difficult to adapt to ensembles where numbers of particles fluctuate.

Recently, some emerging approaches have tackled the question of modeling rare events at constant chemical potential, for example using the String Method in Collective Variables in the osmotic ensemble to model crystal nucleation at constant supersaturation, but these approaches are still in their infancy. There is a clear need to further develop these approaches and come up with new ideas to study rare events in open systems. In a similar way, the modeling of pH-related processes has been attracting scientific interests, and nowadays a diversity of CpH methods and protocols are available from DFT molecular dynamics to coarse-grained Monte Carlo simulations (Baptista et al., 2002; Bennett et al., 2013; Srivastava et al., 2017). Indeed a key difficulty for many CpH methods of macromolecules with explicit solvents is the presence of very high free energy barriers existing between different charge configurations…

Given the importance of open systems including CpH to industrial processing, and at the same time, the fundamental questions these pose to rare-event methods, the current proposal envisages a combined E-CAM industry scoping and research workshop.

The objectives of this meeting are: (i) provide industry participants a summary of the state of the art simulation and rare-event methods at fixed chemical potential; (ii) provide academic research scientists a perspective of the key challenges in this context that industry faced. (iii) allow for a fundamental review of the statistical foundations of rare-event methods in the context of fixed chemical potentials; (iv) determine the means by which corresponding simulations in the condensed phase can be practically implemented using or adapting popular community simulation engines such as LAMMPS, Gromacs or NAMD, and free energy software such as PLUMED. The possibility of also implementing such methods for ab-initio molecular dynamics will also be assessed.

Organisers

• Jony Castagna[1]
• Michael Seaton[1]
• Silvia Chiacchiera[1]
• Leon Petit[1]

[1]STFC Daresbury Laboratory, United Kingdom

Description

Event Postponed – new dates not yet available. Information will be promptly updated on this page and on the CECAM website for the event at https://www.cecam.org/workshop-details/8

Mesoscale simulations have grown recently in importance due to their capacity of capturing molecular and atomistic effects without having to solve for a prohibitively large number of particles needed in Molecular Dynamic (MD) simulations. Different approaches, emerging from a coarse approximation to a group of atoms and molecules, allow reproducing both chemical and physical main properties as well as continuum behaviour such as the hydrodynamics of fluid flows.

One of the most common techniques is the Dissipative Particle Dynamics (DPD): an approximate, coarse-grain, mesoscale simulation method for investigating phenomena between the atomic and the continuum scale world, like flows through complex geometries, micro fluids, phase behaviours and polymer processing. It consists of an off-lattice, discrete particle method similar to MD but with replacement of a soft potential for the conservative force, a random force to simulate the Brownian motion of the particles and a drag force to balance the random force and conserve the total momentum of the system.

However, real applications usually consist of a large number of particles and despite the coarse grain approximation, compared to MD, High Performance Computing (HPC) is often required for simulating systems of industrial and scientific interest. On the other hand, today’s hardware is quickly moving towards hybrid CPU-GPU architectures. In fact, five of the top ten supercomputer are made of mixed CPU and NVidia GPU accelerators which allow to achieve hundreds of PetaFlops performance. This type of architecture is also one of the main paths toward Exascale.

Few software, like DL_MESO, userMESO and LAMMPS, can currently simulate large DPD simulations. In particular, DL_MESO has recently been ported to multi-GPU architectures and runs efficiently up to 4096 GPUs. This allows investigating very large system with billions of particles within affordable computational effort. However, additional effort is required to enable the current version to cover more complex physics, like long range forces as well as achieving higher parallel computing efficiency.

The purpose of this proposal is to organize an Extended Software Development Workshop (ESDW) to introduce students to the parallel programming of hybrid CPU-GPU systems. The intention is not only to port mesoscale solvers on GPUs, but also to expose the ECAM community to this new programming paradigm and to benefit from it also in the other Work Packages. The course will then be open to all ECAM postdocs. Many users of DL_MESO are based at Daresbury Laboratory and we expect a good participation from local researchers. Moreover, due to DL_MESO’s large use in industrial research, we expect potential students from industrial companies like Unilever, Syngenta and Infineum to attend.

References

• Seaton M.A. et al. “DL_MESO: highly scalable mesoscale simulations” Molecular Simulation (39) 2013
• Castagna J. et al “Towards Extreme Scale using Multiple GPGPUs in Dissipative Particle Dynamics Simulations”, The Royal Society poster session on Numerical algorithm for high performance computational science” (2019)
• Castagna J. et al. “Towards extreme scale dissipative particle dynamics simulations using multiple GPGPUs”, Computer Physics Communications (2020) 107159, https://doi.org/10.1016/j.cpc.2020.107159

Organisers

• Nick R. Papior
  Technical University of Denmark, Denmark
• Micael Oliveira
  Max Planck Institute for the Structure and Dynamics of Matter, Hamburg, Germany
• Yann Pouillon
  Universidad de Cantabria, Spain
• Volker Blum
  Duke University, Durham, NC, USA, USA
• Fabiano Corsetti
  Synopsys QuantumWise, Denmark
• Emilio Artacho
  University of Basque Country, United Kingdom

Description 

The landscape of Electronic Structure Calculations is evolving rapidly. On one hand, the adoption of common libraries greatly accelerates the availability of new theoretical developments and can have a significant impact on multiple scientific communities at once [LibXC, PETSc]. On the other hand, electronic-structure codes are increasingly used as “force drivers” within broader calculations [Flos,IPi], a use case for which they have initially not been designed. Recent modelling approaches designed to address limitations with system sizes, while preserving consistency with what is currently available, have also become relevant players in the field. For instance, Second-Principles Density Functional Theory [SPDFT], a systematic approximation built on top of the First-Principles DFT approach, provides a similar level of accuracy to the latter and makes it possible to run calculations on more than 100,000 atoms [ScaleUp, Multibinit]. At a broader level, the European Materials Modelling Council (EMMC) has been organizing various events to establish guidelines and roadmaps around the collaboration of Academy and Industry, to meet prominent challenges in the modelling of realistic systems and the economic sustainability of such endeavours, as well as proposing new career paths for people with hybrid scientific/software engineer profiles [EMMC1,EMMC2].
All these trends further push the development of electronic-structure software more and more towards the provision of standards, libraries, APIs, and flexible software components. At a social level, they are also bringing different communities together and reinforce existing collaborations within the communities themselves. Ongoing efforts include an increasing part of coordination of the developments, enhanced integration of libraries into main codes, and consistent distribution of the software modules. They have been made possible in part by the successful adaptation of Lean, Agile and DevOps approaches to the context of scientific software development and the construction of highly-automated infrastructures [EtsfCI, OctopusCI, SiestaPro]. A key enabler in all this process has been the will to get rid of the former silo mentality, both at a scientific level (one research group, one code) as well as a business model level (libre software vs. open-source vs. proprietary), allowing collaborations between communities and making new public-private partnerships possible.

In this context, an essential component of the Electronic Structure Library [esl, els-gitlab] is the ESL Bundle, a consistent set of libraries broadly used within the Electronic Structure Community that can be installed together. This bundle solves various installation issues for end users and enables a smoother integration of the shipped libraries into external codes. In order to maintain the compatibility of the bundle with the main electronic-structure codes on the long run, its development has been accompanied by the creation of the ESL Steering Committee, which includes representatives of both the individual ESL components and the codes using them. As a consequence, the visibility of the ESL expands and the developers are exposed to an increasing amount of feedback, as well as requests from third-party applications. Since many of these developers are contributing to more than one software package, this constitutes an additional source of pressure, on top of research publications and fundraising duties, that is not trivial to manage.

Establishing an infrastructure that allows code developers to efficiently act upon the feedback received and still guarantee the long-term usability of the ESL components, both individually and as a bundle, has become a necessary step. This requires an efficient coordination between various elements:

Set up a common and consistent code development infrastructure / training in terms of compilation, installation, testing and documentation, that can be used seamlessly beyond the electronic structure community, and learn from solutions adopted by other communities.
Agree on metadata and metrics that are relevant for users of ESL components as well as third-party software, not necessarily related to electronic structure in a direct way.
Creating long-lasting synergies between stakeholders of all communities involved and making it attractive for Industry to contribute.

Since 2014, the ESL has been paving the way towards broader and broader collaborations, with a wiki, a data-exchange standard, refactoring code of global interest into integrated modules, and regularly organising workshops, within a wider movement lead by the European eXtreme Data and Computing Initiative [exdci].

References 

[EMMC1] https://emmc.info/events/emmc-csa-expert-meeting-on-coupling-and-linking/
[EMMC2] https://emmc.info/events/emmc-csa-expert-meeting-sustainable-economic-framework-for-materials-modelling-software/
[EtsfCI] https://www.etsf.eu/resources/infrastructure
[Flos] https://github.com/siesta-project/flos
[IPi] https://github.com/i-pi/i-pi
[LibXC] https://tddft.org/programs/libxc/
[Multibinit] https://ui.adsabs.harvard.edu/abs/2019APS..MARX19008R/abstract
[OctopusCI] https://octopus-code.org/buildbot/#/
[PETSc] https://www.mcs.anl.gov/petsc/
[ScaleUp] https://doi.org/10.1103/PhysRevB.95.094115
[SiestaPro] https://www.simuneatomistics.com/siesta-pro/
[SPDFT] https://doi.org/10.1088/0953-8984/25/30/305401
[esl] http://esl.cecam.org/
[esl-gitlab] http://gitlab.e-cam2020.eu/esl
[exdci] https://exdci.eu/newsroom/press-releases/exdci-towards-common-hpc-strategy-europe