Semi-automatic process partitioning for parallel computation

On current multiprocessor architectures one must carefully distribute data in memory in order to achieve high performance. Process partitioning is the operation of rewriting an algorithm as a collection of tasks, each operating primarily on its own portion of the data, to carry out the computation in parallel. A semi-automatic approach to process partitioning is considered in which the compiler, guided by advice from the user, automatically transforms programs into such an interacting task system. This approach is illustrated with a picture processing example written in BLAZE, which is transformed into a task system maximizing locality of memory reference

Vienna FORTRAN: A FORTRAN language extension for distributed memory multiprocessors

Exploiting the performance potential of distributed memory machines requires a careful distribution of data across the processors. Vienna FORTRAN is a language extension of FORTRAN which provides the user with a wide range of facilities for such mapping of data structures. However, programs in Vienna FORTRAN are written using global data references. Thus, the user has the advantage of a shared memory programming paradigm while explicitly controlling the placement of data. The basic features of Vienna FORTRAN are presented along with a set of examples illustrating the use of these features

Compiling global name-space programs for distributed execution

Distributed memory machines do not provide hardware support for a global address space. Thus programmers are forced to partition the data across the memories of the architecture and use explicit message passing to communicate data between processors. The compiler support required to allow programmers to express their algorithms using a global name-space is examined. A general method is presented for analysis of a high level source program and along with its translation to a set of independently executing tasks communicating via messages. If the compiler has enough information, this translation can be carried out at compile-time. Otherwise run-time code is generated to implement the required data movement. The analysis required in both situations is described and the performance of the generated code on the Intel iPSC/2 is presented

Cumulative reports and publications through December 31, 1988

This document contains a complete list of ICASE Reports. Since ICASE Reports are intended to be preprints of articles that will appear in journals or conference proceedings, the published reference is included when it is available

The work/exchange model: a generalized approach to dynamic load balancing

A crucial concern in software development is reducing program execution time. Parallel processing is often used to meet this goal. However, parallel processing efforts can lead to many pitfalls and problems. One such problem is to distribute the workload among processors in such a way that minimum execution time is obtained. The common approach is to use a load balancer to distribute equal or nearly equal quantities of workload on each processor. Unfortunately, this approach relies on a naive definition of load imbalance and often fails to achieve the desired goal. A more sophisticated definition should account for the affects of additional factors including communication delay costs, network contention, and architectural issues. Consideration of additional factors led us to the realization that optimal load distribution does not always result from equal load distribution. In this dissertation, we tackle the difficult problem of defining load imbalance. This is accomplished through the development of a parallel program model called the Generalized Work/Exchange Model. Associated with the model are equations for a restricted set of deterministically balanced programs that characterize idle time, elapsed time, and potential speedup. With the aid of the model, several common myths about load imbalance are exposed. A useful application called a load balancer enhancer is also presented which is applicable to the more general, quasi-static load unbalanced program