A block SPP algorithm for multidimensional tridiagonal equations with optimal message vector length

A parallel strategy for solving multidimensional tridiagonal equations is investigated in this paper. We present in detail an improved version of single parallel partition (SPP) algorithm in conjunction with message vectorization, which aggregates several communication messages into one to reduce the communication cost. We show the resulting block SPP can achieve good speedup for a wide range of message vector length (MVL), especially when the number of grid points in the divided direction is large. Instead of only using the largest possible MVL, we adopt numerical tests and modeling analysis to determine an optimal MVL so that significant improvement in speedup can be obtained.

On optimal message vector length for block single parallel partition algorithm in a three-dimensional ADI solver

It has long been recognized that many direct parallel tridiagonal solvers are only efficient for solving a single tridiagonal equation of large sizes, and they become inefficient when naively used in a three-dimensional ADI solver. In order to improve the parallel efficiency of an ADI solver using a direct parallel solver, we implement the single parallel partition (SPP) algorithm in conjunction with message vectorization, which aggregates several communication messages into one to reduce the communication costs. The measured performances show that the longest allowable message vector length (MVL) is not necessarily the best choice. To understand this observation and optimize the performance, we propose an improved model that takes the cache effect into consideration. The optimal MVL for achieving the best performance is shown to depend on number of processors and grid sizes. Similar dependence of the optimal MVL is also found for the popular block pipelined method.

Three-dimensional self-assembly of brush block copolymers to photonic crystals

The development of Ring Opening Metathesis Polymerization has allowed the world of block copolymers to expand into brush block copolymers. Brush block copolymers consist of a polymer backbone with polymeric side chains, forcing the backbone to hold a stretched conformation and giving it a worm-like shape. These brush block copolymers have a number of advantages over tradition block copolymers, including faster self-assembly behavior, larger domain sizes, and much less entanglement. This makes them an ideal candidate in the development of a bottom-up approach to forming photonic crystals. Photonic crystals are periodic nanostructures that transmit and reflect only certain wavelengths of light, forming a band gap. These are used in a number of coatings and other optical uses. One and two dimensional photonic crystals are commercially available, though are often expensive and difficult to manufacture. Previous work has focused on the creation of one dimensional photonic crystals from brush block copolymers. In this thesis, I will focus on the synthesis and characterization of asymmetric brush block copolymers for self-assembly into two and three dimensional photonic crystals. Three series of brush block copolymers were made and characterized by Gel Permeation Chromatography and Nuclear Magnetic Resonance spectroscopy. They were then made into films through compressive thermal annealing and characterized by UV-Vis Spectroscopy and Scanning Electron Microscopy. Evidence of non-lamellar structures were seen, indicating the first reported creation of two or three dimensional photonic crystals from brush block copolymers.