Russ Miller

The design and implementation of SnB version 2.0

SnB is a direct-methods program based on the Shake-and-Bake methodology. It has been used to solve difficult or large structures that could not be solved by traditional reciprocal-space routines based on the tangent formula. Recently, it has also been used to determine the Se sites in large selenomethionyl-substituted proteins. SnB version 1.5 has been available for several years and is being used regularly in many laboratories. In this paper, we introduce SnB version 2.0, which incorporates a graphical user interface written in Java, a dynamic histogram display, and an interactive Java/VRML-based visualization facility. In addition, it provides the user with several utility routines and a variety of new algorithmic options.

Parallel computations on reconfigurable meshes

The mesh with reconfigurable bus is presented as a model of computation. The reconfigurable mesh captures salient features from a variety of sources, including the CAAPP, CHiP, polymorphic-torus network, and bus automation. It consists of an array of processors interconnected by a reconfigurable bus system that can be used to dynamically obtain various interconnection patterns between the processors. A variety of fundamental data-movement operations for the reconfigurable mesh are introduced. Based on these operations, algorithms that are efficient for solving a variety of problems involving graphs and digitized images are also introduced. The algorithms are asymptotically superior to those previously obtained for the aforementioned reconfigurable architectures, as well as to those previously obtained for the mesh, the mesh with multiple broadcasting, the mesh with multiple buses, the mesh-of-trees, and the pyramid computer. The power of reconfigurability is illustrated by solving some problems, such as the exclusive OR, more efficiently on the reconfigurable mesh than is possible on the programmable random-access memory (PRAM). >

SnB : crystal structure determination via shake-and-bake

Shake-and-bake is a direct-methods phasing algorithm for structure determination based on the minimal principle. SnB is a program based on shake-and-bake that has been used successfully to solve more than a dozen structures in a variety of space groups. The focus of this paper is on the details of this program, including its structure, system requirements, running times and the rationale for coding in a combination of C and Fortran. A summary of successful SnB applications is also provided. These include solving two previously unknown 100-atom structures and re-solving crambin (a structure containing the equivalent of approximately 400 fully occupied atomic positions) for the first time with a direct-methods technique.

Structure solution by minimal-function phase refinement and Fourier filtering. II. Implementation and applications

The minimal function, R(psi), has been used to provide the basis for a new computer-intensive direct-methods procedure that shows potential for providing fully automatic routine solutions for structures in the 200-400 atom range. This procedure, which has been called shake-and-bake, is an iterative process in which real-space filtering is alternated with phase refinement using a technique that reduces the value of R(psi). It has been successfully tested using experimental data for a dozen known structures ranging in size from 25 to 317 atoms and crystallizing in a variety of space groups. The details of this procedure, the parameters used and the results of these applications are described.

Data movement techniques for the pyramid computer

The pyramid computer was initially proposed for performing high-speed low-level image processing. However, its regular geometry can be adapted naturally to many other problems, providing effective solutions to problems more complex than those previously considered. We illustrate this by presenting pyramid computer solutions to problems involving component labeling, minimal spanning forests, nearest neighbors, transitive closure, articulation points, bridge edges, etc. Central to these algorithms is our collection of data movement techniques which exploit the pyramid’s mix of tree and mesh connections. Our pyramid algorithms are significantly faster than their mesh-connected computer counterparts. For example, given a black/white square picture with n pixels, we can label the connected components in

Mesh computer algorithms for computational geometry

\theta (n^{{1 / 4}} )

Efficient parallel convex hull algorithms

time, as compared with the

Geometric Algorithms for Digitized Pictures on a Mesh-Connected Computer

\Omega (n^{{1 / 2}} )

Optimizing Shake-and-Bake for proteins.

time required on the mesh-connected computer.

X-ray crystallographic analysis of the hydration of A- and B-form DNA at atomic resolution.

Asymptotically optimal parallel algorithms are presented for use on a mesh computer to determine several fundamental geometric properties of figures. For example, given multiple figures represented by the Cartesian coordinates of n or fewer planar vertices, distributed one point per processor on a two-dimensional mesh computer with n simple processing elements, Theta (n/sup 1/2/>or=-time algorithms are given for identifying the convex hull and smallest enclosing box of each figure. Given two such figures, a Theta (n/sup 1/2/>or=-time algorithm is given to decide if the two figures are linearly separable. Given n or fewer planar points, Theta (n/sup 1/2/>or=-time algorithms are given to solve the all-nearest neighbor problems for points and for sets of points. Given n or fewer circles, convex figures, hyperplanes, simple polygons, orthogonal polygons, or iso-oriented rectangles, Theta (n/sup 1/2/>or=-time algorithms are given to solve a variety of area and intersection problems. Since any serial computer has worst-case time of Omega (n) when processing n points, these algorithms show that the mesh computer provides significantly better solutions to these problems. >