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International audience; The Crystal program for quantum-mechanical simulations of materials has been bridging the realm of molecular quantum chemistry to the realm of solid state physics for many years, since its first public version released back in 1988. This peculiarity stems from the use of atom-centered basis functions within a linear combination of atomic orbitals (LCAO) approach and from the corresponding efficiency in the evaluation of the exact Fock exchange series. In particular, this has led to the implementation of a rich variety of hybrid density functional approximations since 1998. Nowadays, it is acknowledged by a broad community of solid state chemists and physicists that the inclusion of a fraction of Fock exchange in the exchange-correlation potential of the density functional theory is key to a better description of many properties of materials (electronic, magnetic, mechanical, spintronic, lattice-dynamical, etc.). Here, the main developments made to the program in the last five years (i.e., since the previous release, Crystal17) are presented and some of their most noteworthy applications reviewed.

Fully ab initio treatment of complex solid systems needs computational software which is able to efficiently take advantage of the growing power of high performance computing (HPC) architectures. Recent improvements in CRYSTAL, a periodic ab initio code that uses a Gaussian basis set, allows treatment of very large unit cells for crystalline systems on HPC architectures with high parallel efficiency in terms of running time and memory requirements. The latter is a crucial point, due to the trend toward architectures relying on a very high number of cores with associated relatively low memory availability. An exhaustive performance analysis shows that density functional calculations, based on a hybrid functional, of low-symmetry systems containing up to 100,000 atomic orbitals and 8000 atoms are feasible on the most advanced HPC architectures available to European researchers today, using thousands of processors. © 2012 Wiley Periodicals, Inc.

Since its inception in 1956 Fortran, and indeed FORTRAN, has been the computational language of science and engineering. Through Fortran aeroplanes fly, drugs are designed and nuclear reactors react. But though codes from the original manual still look familiar [1] Fortran itself has changed much over the last half century and more. So how is it currently being used on modern architectures, particularly at the high end? And how has the recent (in Fortran terms!) move from serial architectures to parallel ones affected practice? And indeed how has the evolution of those parallel platforms affected practice?

We consider the role that large-scale electronic structure computations can now play in the modelling of the condensed phase. To structure our analysis, we consider four distinct ways in which today’s scientific targets can be re-scoped to take advantage of advances in computing resources: 1. Time to solution—performing the same calculation, with delivery of the simulation in shorter elapsed time; 2. Size—applying today’s methods to a more extensive problem; 3. Accuracy—replacing current physical models with more accurate ones. 4. Sampling—simultaneously studying more chemical or conformational states. Each of these offer some scientific rewards, but all present technological challenges and it is likely that a mixture of approaches will be needed to make the best use of capability computing. We discuss some aspects of our work in each of these areas, including replicated and distributed data parallel implementations of GAMESS-UK, and approaches incorporating multi-level parallelism. Examples of the latter include pathway optimization using replica methods and task farming approaches to global optimization problems. We consider a typical application of GAMESS-UK to heterogeneous catalysis, and the role that large-scale DFT vibrational frequency calculations have played in the study of partial oxidation catalysts incorporating supported VOx species. q 2006 Elsevier B.V. All rights reserved.

We present a parallel implementation of the multi-bank k·p code () for calculation of the electronic structure and optical properties of zinc blend structure semiconductor quantum dots. The electronic wave-functions are expanded in a plane wave basis set in a similar way to ab initio calculations. This approach allows one to express the strain tensor components, the piezoelectric field and the arbitrary shape of the embedded quantum dot in the form of coefficients in the Fourier transform, significantly simplifying the implementation. Most of the strain elements can be given in an analytical form, while very complicated quantum dot shapes can be modelled as a linear combination of the Fourier transform of several characteristic shapes: box, cylinder, cone etc. We show that the parallel implementation of the code scales very well up to 512 processors, giving us the memory and processor power to either include more bands, as in the dilute nitrogen quantum dot structures, or to perform calculations on bigger quantum dots/supercells structures keeping the same “cut-off” energy. The program performance is demonstrated on the pyramidal shape InAs/GaAs, dilute nitrogen InGaAsN, and recently emerged volcano-like InAs/GaAs quantum dot systems.

A description of the ab initio quantum chemistry package GAMESS-UK is presented. The package offers a wide range of quantum mechanical wavefunctions, capable of treating systems ranging from closed-shell molecules through to the species involved in complex reaction mechanisms. The availability of a wide variety of correlation methods provides the necessary functionality to tackle a number of chemically important tasks, ranging from geometry optimization and transition-state location to the treatment of solvation effects and the prediction of excited state spectra. With the availability of relativistic ECPs and the development of ZORA, such calculations may be performed on the entire Periodic Table, including the lanthanides. Emphasis is given to the DFT module, which has been extensively developed in recent years, and a number of other, novel features of the program. The parallelization strategy used in the program is outlined, and detailed speedup results are given. Applications of the code in the areas ...

We introduce HPCx—the U.K.'s new National HPC Service—which aims to deliver a world-class service for capability computing to the U.K. scientific community. HPCx is targeting an environment that will both result in world-leading science and address the challenges involved in scaling existing codes to the capability levels required. Close working relationships with scientific consortia and user groups throughout the research process will be a central feature of the service. A significant number of key user applications have already been ported to the system. We present initial benchmark results from this process and discuss the optimization of the codes and the performance levels achieved on HPCx in comparison with other systems. We find a range of performance with some algorithms scaling far better than others. Copyright © 2005 John Wiley & Sons, Ltd.

The molecular dynamics (MD) method is the only tool to provide detailed information on the time evolution of a molecular system on an atomistic scale. Although novel numerical algorithms and data reorganization approches can speed up the numerical calculations, the actual science of a simulation is contained in the captured frames of the system’s state and simulation data during the evolution. Therefore, an important bottleneck in the scalability and efficiency of any MD software is the I/O speed and reliabilty as data has to be dumped and stored for postmortem analysis. This becomes increasingly more important when simulations scale to many thousands of processors and system sizes increase to many millions of particles. This study outlines the problems associated with I/O when performing large classic MD runs and shows that it is necessary to use parallel I/O methods when studying large systems.

We present a new and completely parallel method for protein ligand docking. The potential of the docking target structure is obtained directly from the electron density derived through an ab initio computation. A large subregion of the crystal structure of Isocitrate Lyase, was selected as docking target. To allow the full ab initio treatment of this region special care was taken to assign optimal basis functions. The electrostatic potential is tested by docking a small charged molecule (succinate) into the binding site. The ab initio grid yields a superior result by producing the best binding orientation and position, and by recognizing it as the best. In contrast the same docking procedure, but using a classical point‐charge based potential, produces a number of additional incorrect binding poses, and does not recognize the correct pose as the best solution.

We report a series of computations on the active site in Ti-substituted zeolites, specifically TS-1. Hybrid QM/MM methods based on density functional calculations using the BB1K functional and a valence force field are used to study the processes of hydrolysis of Ti–O–Si linkages and inversion of the TiO4 tetrahedra. The structural features of the resulting series of tetra- and tripodal Ti moieties are in good agreement with data from EXAFS studies. The suggestion is made that the tripodal species will dominate in hydrous conditions, and that this is likely to be the chemically active form. We have made extensive use of the massively parallel HPCx computer system for these investigations and outline some of the technical developments to the ChemShell software that were needed to support the study.

We describe the HPCx UoE Ltd national computing resource HPCx Phase 2 as used in 2004 and 2005. We describe the work of the HPCx ‘terascaling team’ and how this work in collaboration with scientists and code developers allows for efficient exploitation of large-scale computational resources to produce new science as described in the rest of this volume. We emphasize the need for scientists and code developers to have an understanding of the peculiarities of the national and international facilities they use to generate their data. We give some examples of successful application code optimization in materials chemistry on HPCx. We introduce HPCx Phase 2A which entered service in November 2005.