Scheduling system of affine recurrence equations by means of piecewise affine timing functions

Many systematic methods exist for mapping algorithms to processor arrays. The algorithm is usually specified as a set of recurrence equations, and the processor arrays are synthesized by finding timing and allocation functions which transform index points in the recurrences into points in a space-time domain. The problem of scheduling (i.e. finding the timing function) of recurrence equations has been studied by a number of researchers. Of particular interest here are Systems of Affine Recurrence Equations (SAREs). The existing methods are limited to affine (or linear) schedules over the entire domain of computation. For some algorithms, there are points in the computation domain where the dependencies point in opposite directions, and an affine schedule does not exist, although a valid Piecewise Affine Schedule (PAS) can exist. The objective of this thesis is to examine these schedules and obtain a systematic method for deriving such schedules for SAREs. PAS can be found by first partitioning the computation domain and then obtaining a new SARE by renaming the variables. By partitioning the computation domain, we can obtain additional parallelism from the dependency graph, and find faster schedules over subspaces of the domain. In this paper, we describe a procedure for partitioning the domain and to generate a new SARE by renaming the variables. Some heuristics are introduced for partitioning the domain based on the properties of dependence vectors. After the partitioning and renaming, an existing method (due to Mauras et al.) is applied to find the schedules. Examples of Toeplitz System and Algebraic Path Problem are used to illustrate the results

Glosarium Matematika

273 p.; 24 cm

Design and optimisation of scientific programs in a categorical language

This thesis presents an investigation into the use of advanced computer languages for scientific computing, an examination of performance issues that arise from using such languages for such a task, and a step toward achieving portable performance from compilers by attacking these problems in a way that compensates for the complexity of and differences between modern computer architectures. The language employed is Aldor, a functional language from computer algebra, and the scientific computing area is a subset of the family of iterative linear equation solvers applied to sparse systems. The linear equation solvers that are considered have much common structure, and this is factored out and represented explicitly in the lan-guage as a framework, by means of categories and domains. The flexibility introduced by decomposing the algorithms and the objects they act on into separate modules has a strong performance impact due to its negative effect on temporal locality. This necessi-tates breaking the barriers between modules to perform cross-component optimisation. In this instance the task reduces to one of collective loop fusion and array contrac

Proceedings of the 3rd Annual Conference on Aerospace Computational Control, volume 1

Conference topics included definition of tool requirements, advanced multibody component representation descriptions, model reduction, parallel computation, real time simulation, control design and analysis software, user interface issues, testing and verification, and applications to spacecraft, robotics, and aircraft