Parallel computer architectures: state of the art and trends

Summary An increasing number of parallel architectures is becoming available for numerically intensive applications. Many chemical problems need intensive calculations due to the complexity of the underlying physical models. Very often these applications show an intrinsic parallelism and therefore can be easily adapted to parallel machines. In the future, in addition to the classical numerically intensive applications, the use of these machines will be extended to a more general purpose use (e.g. data base machines, advanced graphics, AI and expert systems applications, etc.). The principal aim of this paper is to show the state of the art of the commercially available parallel architectures and related trends. A comparison of the main features of shared and distributed memory systems will be presented. The characteristics of coarse and fine grained architectures will be discussed. The analysis will include not only the large-scale machines (usually called supercomputers), but also smaller machines (e.g. minisuper and multicomputers) having a very favourable price/performance ratio.     

Tight-binding "dihedral orbitals" approach to the degree of folding of macromolecular chains

We develop a tight-binding molecular approach to quantify the degree of folding of a macromolecular chain. This approach is based on the linear combination of "dihedral" orbitals to give molecular orbitals (LCDO-MO). The dihedral orbitals are a set of orbitals situated in each dihedral angle of the chain. The LCDO-MO approach remains basically topological, and we display its direct relation to known graph theoretical concepts. Using this approach, we define the dihedral electronic energy and the dihedral electronic partition function of a linear macromolecular chain. We show that the partition function per dihedral angle quantifies the degree of folding of the dihedral graph. We analyze the empirical relationship between these two functions by using a series of 100 proteins. We also study the relation between these two functions and the percentages of secondary structure for these proteins. Finally, we illustrate the use of the dihedral energy and the partition function in structure-property studies of proteins by analyzing the binding of steroids to DB3 antibody.