Mike Pitman

Blue Matter, an application framework for molecular simulation on blue gene

In this paper we describe the context, architecture, and challenges of Blue Matter, the application framework being developed in conjunction with the science effort within IBMs Blue Gene project. The study of the mechanisms behind protein folding and related topics can require long time simulations on systems with a wide range of sizes and the application supporting these studies must map efficiently onto a large range of parallel partition sizes to optimize scientific throughput for a particular study. The design goals for the Blue Matter architecture include separating the complexities of the parallel implementation on a particular machine from those of the scientific simulation as well as minimizing system environmental dependencies so that running an application within a low overhead kernel with minimal services is possible. We describe some of the parallel decompositions currently being explored that target the first member of the Blue Gene family, BG/L, and present simple performance models for these decompositions that we are using to prioritize our development work. Preliminary results indicate that the high-performance networks on BG/L will allow us to use FFT-based techniques for periodic electrostatics with reasonable speedups on 512-1024 node count partitions even for systems with as few as 5000 atoms.

Blue matter: scaling of N-body simulations to one atom per node

N-body simulations present some of the most interesting challenges in the area of massively parallel computing, especially when the object is to improve the time to solution for a fixed-size problem. The Blue Matter molecular simulation framework was developed specifically to address these challenges, to explore programming models for massively parallel machine architectures in a concrete context, and to support the scientific goals of the IBM Blue Gene® Project. This paper reviews the key issues involved in achieving ultrastrong scaling of methodologically correct biomolecular simulations, particularly the treatment of the long-range electrostatic forces present in simulations of proteins in water and membranes. Blue Matter computes these forces using the particle-particle particle-mesh Ewald (P3ME) method, which breaks the problem up into two pieces, one that requires the use of three-dimensional fast Fourier transforms with global data dependencies and another that involves computing interactions between pairs of particles within a cutoff distance. We summarize our exploration of the parallel decompositions used to compute these finite-ranged interactions, describe some of the implementation details involved in these decompositions, and present the evolution of strong-scaling performance achieved over the course of this exploration, along with evidence for the quality of simulation achieved.

Early experience with scientific applications on the blue gene/l supercomputer

Blue Gene/L uses a large number of low power processors, together with multiple integrated interconnection networks, to build a supercomputer with low cost, space and power consumption. It uses a novel system software architecture designed with application scalability in mind. However, whether real applications will scale to tens of thousands of processors has been an open question. In this paper, we describe early experience with several applications on a 16,384 node Blue Gene/L system. This study establishes that applications from a broad variety of scientific disciplines can effectively scale to thousands of processors. The results reported in this study represent the highest performance ever demonstrated for most of these applications, and in fact, show effective scaling for the first time ever on thousands of processors.

Custom math functions for molecular dynamics

While developing the protein folding application for the IBM Blue Gene®/L supercomputer, some frequently executed computational kernels were encountered. These were significantly more complex than the linear algebra kernels that are normally provided as tuned libraries with modern machines. Using regular library functions for these would have resulted in an application that exploited only 5-10% of the potential floating-point throughput of the machine. This paper is a tour of the functions encountered; they have been expressed in C++ (and could be expressed in other languages such as Fortran or C). With the help of a good optimizing compiler, floating-point efficiency is much closer to 100%. The protein folding application was initially run by the life science researchers on IBM POWER3™ machines while the computer science researchers were designing and bringing up the Blue Gene/L hardware. Some of the work discussed resulted in enhanced compiler optimizations, which now improve the performance of floating-point-intensive applications compiled by the IBM VisualAge® series of compilers for POWER3, POWER4™, POWER4+™, and POWER5™. The implementations are offered in the hope that they may help in other implementations of molecular dynamics or in other fields of endeavor, and in the hope that others may adapt the ideas presented here to deliver additional mathematical functions at high throughput.

Comparative molecular moment analysis (CoMMA)

The binding of a drug molecule to its targeted receptor site is dependent upon a number of physical and chemical factors. In many instances, this binding is a consequence of non-bonding as opposed to covalent interactions and is, therefore, determined to a large extent by the complementarity of ligand molecular shape and charge to its targeted receptor site. Molecular shape and charge can be characterized in a number of different ways as attested to by chapters in this volume. Perhaps the most elemental characterization of molecular shape and charge is provided by the moments of the mass (shape) and charge distributions. For those with no prior exposure to the concept of moments of a distribution, such a mass or charge, suitable references might be useful [1,2]. Certain of the lower-order molecular moments — e.g. molecular weight, moments of inertia, net molecular charge and dipole moment — have been used to characterize molecules, and it is perhaps not fully appreciated that these quantities are lower-order terms in a series that extends to infinity. Table 1 lists these commonly used moments and terminology, up to and inclusive of the second order of the molecular mass (shape) and charge. Molecular weight, moments of inertia and dipole moment have been previously used in a number of three-dimensional quantitative structure activity (3D QSAR) studies. Since such lower-order moments had been used to characterize neutral molecules, what captured our interest initially was that quadrupolar moments, the second-order electrostatic analog of the inertial moments, were never mentioned in connection with either discussions of molecular similarity or 3D QSAR procedures. A reason for this became apparent immediately. The comparison of quadrupolar moments between different molecules required the identification of a center — i.e. a center identified in an analogous fashion to the molecular center-of-mass which enables comparison of the moments of inertia of different molecules. Such center had not been identified. The zero’th-order moment of molecular mass is just the molecular weight, which is obviously independent of a location of the origin of multipolar expansion. The inertial or second-order moments do depend upon the choice of origin about which they are cal

MOLECULAR MOMENT SIMILARITY BETWEEN SEVERAL NUCLEOSIDE ANALOGS OF THYMIDINE AND THYMIDINE

Molecular moment descriptors of the shape and charge distributions of twenty five nucleoside structures have been examined. The structures include thymidine as well as the difluorotoluene nucleoside analog which has been found to pair efficiently with adenine by polymerase catalysis. The remaining twenty three structures have been chosen to be as structurally similar to thymidine and to the difluorotoluene nucleoside analog as possible. The moment descriptors which include a description of the relationship of molecular charge to shape show the difluorotoluene nucleoside to be one of the most proximate molecules to thymidine in the space of the molecular moments. The calculations, therefore, suggest that polymerase specificity might be not only a consequence of molecular steric features alone but also of the molecular electrostatic environment and its registration with molecular shape.

Molecular moment similarity between clozapine and substituted [(4-phenylpiperazinyl)-methyl] benzamides: Selective dopamine D4 agonists

Moment descriptors of the molecular charge and mass distributions are investigated within the context of molecular similarity. Euclidean distances in the moment descriptor space are shown to yield molecular proximities in accord with chemical intuition for a substituted [(4-phenylpiperazinyl)-methyl] benzamide series of dopamine D4 agonists. The proximity of the dopamine D4 antagonist clozapine to the molecules of this series is also examined in the moment space.