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PubMed2002

Promise and challenge of high-performance computing, with examples from molecular modelling.

Computational modelling is one of the most significant developments in the practice of scientific inquiry in the 20th century. During the past decade, advances in computing technologies have increased the speed of computers by a factor of 100; an increase of a factor of 1000 can be expected in the next decade. These advances have, however, come at a price, namely, radical change(s) in computer architecture. Will computational scientists and engineers be able to harness the power offered by these high-performance computers to solve the most critical problems in science and engineering? In this paper, we discuss the challenges that must be addressed if we are to realize the benefits offered by high-performance computing. The task will not be easy; it will require revision or replacement of much of the software developed for vector supercomputers as well as advances in a number of key theoretical areas. Because of the pace of computing advances, these challenges must be met by close collaboration between computational scientists, computer scientists and applied mathematicians. The effectiveness of such a multidisciplinary approach is illustrated in a brief review of NWCHEM, a general-purpose computational chemistry code designed for parallel supercomputers.

Algorithms↗
PubMed2002

Application of high-throughput computing in bioinformatics.

We describe the challenges faced when developing a Linux/PC-based cluster to apply bioinformatics algorithms to the rapidly increasing raw genomics data available. The calculations, which take around two months to complete, result in a powerful resource that can be used for data mining--most obviously for the human genome. Our current infrastructure consists of a 1314 node cluster with 1734 processors supporting both production and research. This paper highlights the problems in achieving high data throughput with such systems and shows that raw computer power is only one component of a complex problem.

Computational Biology↗
PubMed2002

Data Grids: a new computational infrastructure for data-intensive science.

Twenty-first-century scientific and engineering enterprises are increasingly characterized by their geographic dispersion and their reliance on large data archives. These characteristics bring with them unique challenges. First, the increasing size and complexity of modern data collections require significant investments in information technologies to store, retrieve and analyse them. Second, the increased distribution of people and resources in these projects has made resource sharing and collaboration across significant geographic and organizational boundaries critical to their success. In this paper I explore how computing infrastructures based on Data Grids offer data-intensive enterprises a comprehensive, scalable framework for collaboration and resource sharing. A detailed example of a Data Grid framework is presented for a Large Hadron Collider experiment, where a hierarchical set of laboratory and university resources comprising petaflops of processing power and a multi-petabyte data archive must be efficiently used by a global collaboration. The experience gained with these new information systems, providing transparent managed access to massive distributed data collections, will be applicable to large-scale, data-intensive problems in a wide spectrum of scientific and engineering disciplines, and eventually in industry and commerce. Such systems will be needed in the coming decades as a central element of our information-based society.

Computer Communication Networks↗
PubMed2002

Simulation of the strong interaction.

In the Standard Model (SM) of particle physics, quarks are permanently confined by the strong interaction into bound states called hadrons. The values of some parameters, such as the quark masses and the strengths of the decays of one quark flavour into another, cannot be measured directly and must be deduced from experiments on hadrons. This requires calculations of the strong-interaction effects within the bound states, which are only possible using numerical simulations of quantum chromodynamics (QCD), the quantum field theory of the strong interaction. In conjunction with experimental data from B factories over the next few years, QCD simulations may provide clues to physics beyond the SM. The simulations are computationally intensive and, for the past 20 years, have exploited leading-edge computing technology. This continues today, with a project to develop a 10 Tflops computer for QCD costing less than 1 US dollar per Mflops.

Algorithms↗
PubMed2002

High-performance computing in computational fluid dynamics: progress and challenges.

Computational fluid dynamics (CFD) is by far the largest user of high-performance computing (HPC) in engineering. The main scientific challenge is the need to gain a greater understanding of turbulence and its consequences for the transfer of momentum, heat and mass in engineering applications, including aerodynamics, industrial flows and combustion systems. Availability of HPC has led to significant advances in direct numerical simulation (DNS) of turbulence and turbulent combustion, and has encouraged the development of large-eddy simulation (LES) for engineering flows. The statistical data generated by DNS have provided valuable insight into the physics of many turbulent flows and have led to rapid improvements in turbulence and combustion modelling for industry. Nevertheless, major challenges remain and the computational requirements for turbulence research, driven by well-established physical scaling laws, are likely to remain at the limit of the available HPC provision for some time to come.

Air Movements↗
PubMed2002

Computationally intensive econometrics using a distributed matrix-programming language.

This paper reviews the need for powerful computing facilities in econometrics, focusing on concrete problems which arise in financial economics and in macroeconomics. We argue that the profession is being held back by the lack of easy-to-use generic software which is able to exploit the availability of cheap clusters of distributed computers. Our response is to extend, in a number of directions, the well-known matrix-programming interpreted language Ox developed by the first author. We note three possible levels of extensions: (i) Ox with parallelization explicit in the Ox code; (ii) Ox with a parallelized run-time library; and (iii) Ox with a parallelized interpreter. This paper studies and implements the first case, emphasizing the need for deterministic computing in science. We give examples in the context of financial economics and time-series modelling.

Computer Communication Networks↗
PubMed2002

Computational challenges in atomic, molecular and optical physics.

Six challenges are discussed. These are the laser-driven helium atom; the laser-driven hydrogen molecule and hydrogen molecular ion; electron scattering (with ionization) from one-electron atoms; the vibrational and rotational structure of molecules such as H(3)(+) and water at their dissociation limits; laser-heated clusters; and quantum degeneracy and Bose-Einstein condensation. The first four concern fundamental few-body systems where use of high-performance computing (HPC) is currently making possible accurate modelling from first principles. This leads to reliable predictions and support for laboratory experiment as well as true understanding of the dynamics. Important aspects of these challenges addressable only via a terascale facility are set out. Such a facility makes the last two challenges in the above list meaningfully accessible for the first time, and the scientific interest together with the prospective role for HPC in these is emphasized.

Computer Simulation↗
PubMed2003

Self-organization and complexity: a new age for theory, computation and experiment.

I first describe the notion of self-organization as a property of far-from-equilibrium nonlinear dissipative dynamical systems. Rather than describing such complex systems at a purely phenomenological level, however, I focus attention on the emergent nature of this complexity, by analysing a few examples of physical and physicochemical systems with simple underlying microscopic dynamics yet complex, self-organizing macroscopic properties. These include several mesoscopic models of fluid dynamics as well as a modern approach to nucleation and growth phenomena. Finally, I discuss how the advent of computational grids is set to provide a major boost to the study of such complex, self-organizing systems.

Adaptation, Physiological↗
PubMed2003

Quantum technology: the second quantum revolution.

We are currently in the midst of a second quantum revolution. The first quantum revolution gave us new rules that govern physical reality. The second quantum revolution will take these rules and use them to develop new technologies. In this review we discuss the principles upon which quantum technology is based and the tools required to develop it. We discuss a number of examples of research programs that could deliver quantum technologies in coming decades including: quantum information technology, quantum electromechanical systems, coherent quantum electronics, quantum optics and coherent matter technology.

Computing Methodologies↗
PubMed2003

Artificial intelligence and the future.

We consider some of the ideas influencing current artificial-intelligence research and outline an alternative conceptual framework that gives priority to social relationships as a key component and constructor of intelligent behaviour. The framework starts from Weizenbaum's observation that intelligence manifests itself only relative to specific social and cultural contexts. This is in contrast to a prevailing view, which sees intelligence as an abstract capability of the individual mind based on a mechanism for rational thought. The new approach is not based on the conventional idea that the mind is a rational processor of symbolic information, nor does it require the idea that thought is a kind of abstract problem solving with a semantics that is independent of its embodiment. Instead, priority is given to affective and social responses that serve to engage the whole agent in the life of the communities in which it participates. Intelligence is seen not as the deployment of capabilities for problem solving, but as constructed by the continual, ever-changing and unfinished engagement with the social group within the environment. The construction of the identity of the intelligent agent involves the appropriation or 'taking up' of positions within the conversations and narratives in which it participates. Thus, the new approach argues that the intelligent agent is shaped by the meaning ascribed to experience, by its situation in the social matrix, and by practices of self and of relationship into which intelligent life is recruited. This has implications for the technology of the future, as, for example, classic artificial intelligence models such as goal-directed problem solving are seen as special cases of narrative practices instead of as ontological foundations.

Artificial Intelligence↗
PubMed2004

Large-scale molecular dynamics simulation of DNA: implementation and validation of the AMBER98 force field in LAMMPS.

Molecular modelling played a central role in the discovery of the structure of DNA by Watson and Crick. Today, such modelling is done on computers: the more powerful these computers are, the more detailed and extensive can be the study of the dynamics of such biological macromolecules. To fully harness the power of modern massively parallel computers, however, we need to develop and deploy algorithms which can exploit the structure of such hardware. The Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) is a scalable molecular dynamics code including long-range Coulomb interactions, which has been specifically designed to function efficiently on parallel platforms. Here we describe the implementation of the AMBER98 force field in LAMMPS and its validation for molecular dynamics investigations of DNA structure and flexibility against the benchmark of results obtained with the long-established code AMBER6 (Assisted Model Building with Energy Refinement, version 6). Extended molecular dynamics simulations on the hydrated DNA dodecamer d(CTTTTGCAAAAG)(2), which has previously been the subject of extensive dynamical analysis using AMBER6, show that it is possible to obtain excellent agreement in terms of static, dynamic and thermodynamic parameters between AMBER6 and LAMMPS. In comparison with AMBER6, LAMMPS shows greatly improved scalability in massively parallel environments, opening up the possibility of efficient simulations of order-of-magnitude larger systems and/or for order-of-magnitude greater simulation times.

Algorithms↗
PubMed2006

Enabling computer models of the heart for high-performance computers and the grid.

Although it is now feasible to compute multi-cellular models of the heart on a personal desktop or laptop computer, it is not feasible to undertake the detailed sweeps of high-dimensional parameter spaces required if we are to undertake in silico experimentation of the complex processes that constitute heart disease. For this research, modelling requirements move rapidly beyond the limit of commodity computers' resource both in terms of their memory footprint and the speed of calculation, so that multi-processor architectures must be considered. In addition, as such models have become more mature and have been validated against experimental data, there is increasing pressure for experimentalists to be able to make use of these models themselves as a key tool for hypothesis formulation and in planning future experimental studies to test those hypotheses. This paper discusses our initial experiences in a large-scale project (the Integrative Biology (IB) e-Science project) aimed at meeting these dual aims. We begin by putting the research in context by describing in outline the overall aims of the IB project, in particular focusing on the challenge of enabling novice users to make full use of high-performance resources without the need to gain detailed technical expertise in computing. We then discuss our experience of adapting one particular heart modelling package, Cellular Open Resource, and show how the solving engine of this code was dissected from the rest of the package, ported to C++ and parallelized using the Message-Passing Interface. We show that good parallel efficiency and realistic memory reduction can be achieved on simple geometries. We conclude by discussing lessons learnt in this process.

Action Potentials↗
PubMed2002

An update on blood pressure short-term variability.

This article summarizes current achievements of computer-based methodologies in identifying the constituting components of short-term blood pressure variability and the underlying regulatory mechanisms. It emphasizes the contribution of spectral methodologies in early diagnosis of blood pressure deregulations. Moreover, the effects of antihypertensive drugs, as well as of new, nonpeptide vasopressin antagonists on short-term blood pressure variability, are briefly described.

Animals↗
PubMed1997

Multiplex sequencing of 1.5 Mb of the Mycobacterium leprae genome.

The nucleotide sequence of 1.5 Mb of genomic DNA from Mycobacterium leprae was determined using computer-assisted multiplex sequencing technology. This brings the 2.8-Mb M. leprae genome sequence to approximately 66% completion. The sequences, derived from 43 recombinant cosmids, contain 1046 putative protein-coding genes, 44 repetitive regions, 3 tRNAs, and 15 tRNAs. The gene density of one per 1.4 kb is slightly lower than that of Mycoplasma (1.2 kb). Of the protein coding genes, 44% have significant matches to genes with well-defined functions. Comparison of 1157 M. leprae and 1564 Mycobacterium tuberculosis proteins shows a complex mosaic of homologous genomic blocks with up to 22 adjacent proteins in conserved map order. Matches to known enzymatic, antigenic, membrane, cell wall, cell division, multidrug resistance, and virulence proteins suggest therapeutic and vaccine targets. Unusual features of the M. leprae genome include large polyketide synthase (pks) operons, inteins, and highly fragmented pseudogenes.

Amino Acid Sequence↗
PubMed2006

Hybrid particle-field simulations of polymer nanocomposites.

We present a theoretical framework and computer simulation methodology for investigating the equilibrium structure and properties of mesostructured polymeric fluids with embedded colloids or nanoparticles. The method is based on a field-theoretic description of the fluid in which particle coordinates and chemical potential field variables are simultaneously updated. The fluid model can contain polymers of arbitrary chemical and architectural complexity, along with particles of all shapes, sizes, and surface treatments. Simulation results are compared with experiments conducted on polystyrene (PS)-functionalized Au nanoparticles in a PS-P2VP diblock copolymer melt.

Journal Article↗
PubMed2005

Hypothetical binodal zeolitic frameworks.

Hypothetical binodal zeolitic structures (structures containing two kinds of tetrahedral sites) were systematically enumerated using tiling theory and characterized by computational chemistry methods. Each of the 109 refineable topologies based on "simple tilings" was converted into a silica polymorph and its energy minimized using the GULP program with the Sanders-Catlow silica potential. Optimized structural parameters, framework energies relative to alpha-quartz and volumes accessible to sorption have been calculated. Eleven of the 30 known binodal topologies listed in the Atlas of Zeolite Framework Types were found, leaving 98 topologies that were unknown previously. The chemical feasibility of each structure as a zeolite was evaluated by means of a feasibility factor derived from the correlation between lattice energy and framework density. Structures are divided into 15 families, based on common structural features. Many "feasible" structures contain only small pores. Several very open structures were also enumerated, although they contain three-membered rings which are thermodynamically disfavoured and not found in conventional zeolites. We believe that such topologies may be realizable as framework materials, but with different elemental compositions to those normally associated with zeolites.

Computing Methodologies↗