36 research outputs found
Molecular dynamics simulations of complex systems including HIV-1 protease
Advances in supercomputer architectures have resulted in a situation where many scienti�fic codes are used on systems whose performance characteristics di�ffer considerably
from the platform they were developed and optimised for. This is particularly apparent
in the realm of Grid computing, where new technologies such as MPIg allow researchers
to connect geographically disparate resources together into virtual parallel machines.
Finding ways to exploit these new resources efficiently is necessary both to extract the
maximum bene�fit from them, and to provide the enticing possibility of enabling new science. In this thesis, an existing general purpose molecular dynamics code (LAMMPS)
is extended to allow it to perform more efficiently in a geographically distributed Grid
environment showing considerable performance gains as a result.
The technique of replica exchange molecular dynamics is discussed along with its applicability to the Grid model and its bene�fits with respect to increasing sampling of configurational space. The dynamics of two sub-structures of the HIV-1 protease (known
as the
flaps) are investigated using replica exchange molecular dynamics in LAMMPS
showing considerable movement that would have been difficult to investigate by traditional methods.
To complement this, a study was carried out investigating the use of computational tools
to calculate binding affinity between HIV-1 protease mutants and the drug lopinavir in
comparison with results derived experimentally by other research groups. The results
demonstrate some promise for computational methods in helping to determine the most
eff�ective course of treatment for patients in the future
MPWide: a light-weight library for efficient message passing over wide area networks
We present MPWide, a light weight communication library which allows
efficient message passing over a distributed network. MPWide has been designed
to connect application running on distributed (super)computing resources, and
to maximize the communication performance on wide area networks for those
without administrative privileges. It can be used to provide message-passing
between application, move files, and make very fast connections in
client-server environments. MPWide has already been applied to enable
distributed cosmological simulations across up to four supercomputers on two
continents, and to couple two different bloodflow simulations to form a
multiscale simulation.Comment: accepted by the Journal Of Open Research Software, 13 pages, 4
figures, 1 tabl
Lattice-Boltzmann simulations of cerebral blood flow
Computational haemodynamics play a central role in the understanding of blood behaviour
in the cerebral vasculature, increasing our knowledge in the onset of vascular
diseases and their progression, improving diagnosis and ultimately providing better
patient prognosis. Computer simulations hold the potential of accurately characterising
motion of blood and its interaction with the vessel wall, providing the capability to
assess surgical treatments with no danger to the patient. These aspects considerably
contribute to better understand of blood circulation processes as well as to augment
pre-treatment planning. Existing software environments for treatment planning consist
of several stages, each requiring significant user interaction and processing time,
significantly limiting their use in clinical scenarios.
The aim of this PhD is to provide clinicians and researchers with a tool to aid
in the understanding of human cerebral haemodynamics. This tool employs a high
performance
fluid solver based on the lattice-Boltzmann method (coined HemeLB),
high performance distributed computing and grid computing, and various advanced
software applications useful to efficiently set up and run patient-specific simulations.
A graphical tool is used to segment the vasculature from patient-specific CT or MR
data and configure boundary conditions with ease, creating models of the vasculature
in real time. Blood flow visualisation is done in real time using in situ rendering
techniques implemented within the parallel
fluid solver and aided by steering capabilities;
these programming strategies allows the clinician to interactively display the
simulation results on a local workstation. A separate software application is used
to numerically compare simulation results carried out at different spatial resolutions,
providing a strategy to approach numerical validation. This developed software and
supporting computational infrastructure was used to study various patient-specific
intracranial aneurysms with the collaborating interventionalists at the National Hospital
for Neurology and Neuroscience (London), using three-dimensional rotational
angiography data to define the patient-specific vasculature. Blood flow motion was
depicted in detail by the visualisation capabilities, clearly showing vortex fluid
ow features and stress distribution at the inner surface of the aneurysms and their surrounding
vasculature. These investigations permitted the clinicians to rapidly assess
the risk associated with the growth and rupture of each aneurysm. The ultimate goal
of this work is to aid clinical practice with an efficient easy-to-use toolkit for real-time
decision support
A platform independent communication library for distributed computing
We present MPWide, a platform independent communication library for performing message passing between supercomputers. Our library couples several local MPI applications through a long distance network using, for example, optical links. The implementation is deliberately kept light-weight, platform independent and the library can be installed and used without administrative privileges. The only requirements are a C++ compiler and at least one open port to a wide area network on each site. In this paper we present the library, describe the user interface, present performance tests and apply MPWide in a large scale cosmological N-body simulation on a network of two computers, one in Amsterdam and the other in Tokyo
Studies on distributed approaches for large scale multi-criteria protein structure comparison and analysis
Protein Structure Comparison (PSC) is at the core of many important structural biology problems. PSC is used to infer the evolutionary history of distantly related proteins; it can also help in the identification of the biological function of a new protein by comparing it with other proteins whose function has already been annotated; PSC is also a key step in protein structure prediction, because one needs to reliably and efficiently compare tens or hundreds of thousands of decoys (predicted structures) in evaluation of 'native-like' candidates (e.g. Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment). Each of these applications, as well as many others where molecular comparison plays an important role, requires a different notion of similarity, which naturally lead to the Multi-Criteria Protein Structure Comparison (MC-PSC) problem. ProCKSI (www.procksi.org), was the first publicly available server to provide algorithmic solutions for the MC-PSC problem by means of an enhanced structural comparison that relies on the principled application of information fusion to similarity assessments derived from multiple comparison methods (e.g. USM, FAST, MaxCMO, DaliLite, CE and TMAlign). Current MC-PSC works well for moderately sized data sets and it is time consuming as it provides public service to multiple users. Many of the structural bioinformatics applications mentioned above would benefit from the ability to perform, for a dedicated user, thousands or tens of thousands of comparisons through multiple methods in real-time, a capacity beyond our current technology.
This research is aimed at the investigation of Grid-styled distributed computing strategies for the solution of the enormous computational challenge inherent in MC-PSC. To this aim a novel distributed algorithm has been designed, implemented and evaluated with different load balancing strategies and selection and configuration of a variety of software tools, services and technologies on different levels of infrastructures ranging from local testbeds to production level eScience infrastructures such as the National Grid Service (NGS). Empirical results of different experiments reporting on the scalability, speedup and efficiency of the overall system are presented and discussed along with the software engineering aspects behind the implementation of a distributed solution to the MC-PSC problem based on a local computer cluster as well as with a GRID implementation. The results lead us to conclude that the combination of better and faster parallel and distributed algorithms with more similarity comparison methods provides an unprecedented advance on protein structure comparison and analysis technology. These advances might facilitate both directed and fortuitous discovery of protein similarities, families, super-families, domains, etc, and also help pave the way to faster and better protein function inference, annotation and protein structure prediction and assessment thus empowering the structural biologist to do a science that he/she would not have done otherwise
Studies on distributed approaches for large scale multi-criteria protein structure comparison and analysis
Protein Structure Comparison (PSC) is at the core of many important structural biology problems. PSC is used to infer the evolutionary history of distantly related proteins; it can also help in the identification of the biological function of a new protein by comparing it with other proteins whose function has already been annotated; PSC is also a key step in protein structure prediction, because one needs to reliably and efficiently compare tens or hundreds of thousands of decoys (predicted structures) in evaluation of 'native-like' candidates (e.g. Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment). Each of these applications, as well as many others where molecular comparison plays an important role, requires a different notion of similarity, which naturally lead to the Multi-Criteria Protein Structure Comparison (MC-PSC) problem. ProCKSI (www.procksi.org), was the first publicly available server to provide algorithmic solutions for the MC-PSC problem by means of an enhanced structural comparison that relies on the principled application of information fusion to similarity assessments derived from multiple comparison methods (e.g. USM, FAST, MaxCMO, DaliLite, CE and TMAlign). Current MC-PSC works well for moderately sized data sets and it is time consuming as it provides public service to multiple users. Many of the structural bioinformatics applications mentioned above would benefit from the ability to perform, for a dedicated user, thousands or tens of thousands of comparisons through multiple methods in real-time, a capacity beyond our current technology.
This research is aimed at the investigation of Grid-styled distributed computing strategies for the solution of the enormous computational challenge inherent in MC-PSC. To this aim a novel distributed algorithm has been designed, implemented and evaluated with different load balancing strategies and selection and configuration of a variety of software tools, services and technologies on different levels of infrastructures ranging from local testbeds to production level eScience infrastructures such as the National Grid Service (NGS). Empirical results of different experiments reporting on the scalability, speedup and efficiency of the overall system are presented and discussed along with the software engineering aspects behind the implementation of a distributed solution to the MC-PSC problem based on a local computer cluster as well as with a GRID implementation. The results lead us to conclude that the combination of better and faster parallel and distributed algorithms with more similarity comparison methods provides an unprecedented advance on protein structure comparison and analysis technology. These advances might facilitate both directed and fortuitous discovery of protein similarities, families, super-families, domains, etc, and also help pave the way to faster and better protein function inference, annotation and protein structure prediction and assessment thus empowering the structural biologist to do a science that he/she would not have done otherwise
Unstable periodic orbits in turbulent hydrodynamics
In this work we describe a novel parallel space-time algorithm for the computation of periodic
solutions of the driven, incompressible Navier-Stokes equations in the turbulent regime. Efforts to
apply the machinery of dynamical systems theory to fluid turbulence depend on the ability to accurately
and reliably compute such unstable periodic orbits (UPOs). These UPOs can be used to construct the
dynamical zeta function of the system, from which very accurate turbulent averages of observables
can be extracted from first principles, thus circumventing the inherently statistical description of fluid
turbulence.
In order to identify these orbits we use a space-time variational principle, first introduced in 2004.
This approach has not, to the best of our knowledge, been used before on dynamical systems of high
dimension because of the formidable storage and computation required. In this thesis we describe
the utilization of petascale high performance computation to the problem of applying this space-time
algorithm to hydrodynamic turbulence.
The lattice-Boltzmann method is used to simulate the Navier-Stokes equations, due to its locality,
and is implemented in a fully-parallel software package using the Message Passing Interface. This
implementation, called HYPO4D, was successfully deployed on a large variety of platforms both in the
UK and the US with an extremely good scalability to tens of thousands of computing cores. Based
on this fluid solver other routines were developed, for the systematic location of suitable candidate
spacetime minima and their numerical relaxation, using the gradient descent and conjugate gradient
algorithms.
Following this methodology, several UPOs are identified in homogeneous turbulence driven by an
Arnold-Beltrami-Childress force field in three spatial dimensions, at Reynolds numbers corresponding
to weakly-turbulent flow. We characterize the transition to turbulence in the ABC flow and the periodic
orbits computed, for a flow with Re = 371, after the transients have died down. The work concludes
with a discussion of the potential for this approach to become a new paradigm in the study of driven
dissipative dynamical systems