A Theoretical Approach Involving Recurrence Resolution, Dependence Cycle Statement Ordering and Subroutine Transformation for the Exploitation of Parallelism in Sequential Code.

To exploit parallelism in Fortran code, this dissertation consists of a study of the following three issues: (1) recurrence resolution in Do-loops for vector processing, (2) dependence cycle statement ordering in Do-loops for parallel processing, and (3) sub-routine parallelization. For recurrence resolution, the major findings include: (1) the node splitting algorithm cannot be used directly to break an essential antidependence link, of which the source variable that results in antidependence is itself the sink variable of another true dependence so a correction method is proposed, (2) a sink variable renaming technique is capable of breaking an antidependence and/or output-dependence link, (3) for recurrences formed by only true dependences, a dynamic dependence concept and the derived technique are powerful, and (4) by integrating related techniques, an algorithm for resolving a general multistatement recurrence is developed. The performance of a parallel loop is determined by the level of parallelism and the time delay due to interprocessor communication and synchronization. For a dependence cycle of a single parallel loop executed in a general synchronization mode, the parallelism exposed varies with the alignment of statements. Statements are reordered on the basis of execution-time of the loop as estimated at compile-time. An improved timing formula and a derived statement ordering algorithm are proposed. Further extension of this algorithm to multiple perfectly nested Do-loops with simple global dependence cycle is also presented. The subroutine is a potential source for parallel processing. Several problems must be solved for subroutine parallelization: (1) the precedence of parallel executions of subroutines, (2) identification of the optimum execution mode for each subroutine and (3) the restructuring of a serial program. A five-step approach to parallelize called subroutines for a calling subroutine is proposed: (1) computation of control dependence, (2) approximation of the global effects of subroutines, (3) analysis of data dependence, (4) identification of execution mode, and (5) restructuring of calling and called subroutines. Application of these five steps in a recursive manner to different levels of calling subroutines in a program addresses the parallelization of subroutines

Concurrent processing simulation of the space station

The development of a new capability for the time-domain simulation of multibody dynamic systems and its application to the study of a large angle rotational maneuvers of the Space Station is described. The effort was divided into three sequential tasks, which required significant advancements of the state-of-the art to accomplish. These were: (1) the development of an explicit mathematical model via symbol manipulation of a flexible, multibody dynamic system; (2) the development of a methodology for balancing the computational load of an explicit mathematical model for concurrent processing; and (3) the implementation and successful simulation of the above on a prototype Custom Architectured Parallel Processing System (CAPPS) containing eight processors. The throughput rate achieved by the CAPPS operating at only 70 percent efficiency, was 3.9 times greater than that obtained sequentially by the IBM 3090 supercomputer simulating the same problem. More significantly, analysis of the results leads to the conclusion that the relative cost effectiveness of concurrent vs. sequential digital computation will grow substantially as the computational load is increased. This is a welcomed development in an era when very complex and cumbersome mathematical models of large space vehicles must be used as substitutes for full scale testing which has become impractical

Probabilistic structural mechanics research for parallel processing computers

Aerospace structures and spacecraft are a complex assemblage of structural components that are subjected to a variety of complex, cyclic, and transient loading conditions. Significant modeling uncertainties are present in these structures, in addition to the inherent randomness of material properties and loads. To properly account for these uncertainties in evaluating and assessing the reliability of these components and structures, probabilistic structural mechanics (PSM) procedures must be used. Much research has focused on basic theory development and the development of approximate analytic solution methods in random vibrations and structural reliability. Practical application of PSM methods was hampered by their computationally intense nature. Solution of PSM problems requires repeated analyses of structures that are often large, and exhibit nonlinear and/or dynamic response behavior. These methods are all inherently parallel and ideally suited to implementation on parallel processing computers. New hardware architectures and innovative control software and solution methodologies are needed to make solution of large scale PSM problems practical

Parallel Computation of Large-Scale Nonlinear Network Problems in the Social and Economic Sciences

In this paper we focus on the parallel computation of large - scale equilibrium and optimization problems arising in the social and economic sciences. In particular, we consider problems which can be visualized and conceptualized as nonlinear network flow problems. The underlying network structure is then exploited in the development of parallel decomposition algorithms. We first consider market equilibrium problems, both dynamic and static, which are formulated as variational inequality problems, and for which we propose parallel decomposition algorithms by time period and by commodity, respectively. We then turn to the parallel computation of large-scale constrained matrix problems which are formulated as optimization problems and discuss the results of parallel decomposition by row/column

Architecture independent environment for developing engineering software on MIMD computers

Engineers are constantly faced with solving problems of increasing complexity and detail. Multiple Instruction stream Multiple Data stream (MIMD) computers have been developed to overcome the performance limitations of serial computers. The hardware architectures of MIMD computers vary considerably and are much more sophisticated than serial computers. Developing large scale software for a variety of MIMD computers is difficult and expensive. There is a need to provide tools that facilitate programming these machines. First, the issues that must be considered to develop those tools are examined. The two main areas of concern were architecture independence and data management. Architecture independent software facilitates software portability and improves the longevity and utility of the software product. It provides some form of insurance for the investment of time and effort that goes into developing the software. The management of data is a crucial aspect of solving large engineering problems. It must be considered in light of the new hardware organizations that are available. Second, the functional design and implementation of a software environment that facilitates developing architecture independent software for large engineering applications are described. The topics of discussion include: a description of the model that supports the development of architecture independent software; identifying and exploiting concurrency within the application program; data coherence; engineering data base and memory management

A design methodology for portable software on parallel computers

This final report for research that was supported by grant number NAG-1-995 documents our progress in addressing two difficulties in parallel programming. The first difficulty is developing software that will execute quickly on a parallel computer. The second difficulty is transporting software between dissimilar parallel computers. In general, we expect that more hardware-specific information will be included in software designs for parallel computers than in designs for sequential computers. This inclusion is an instance of portability being sacrificed for high performance. New parallel computers are being introduced frequently. Trying to keep one's software on the current high performance hardware, a software developer almost continually faces yet another expensive software transportation. The problem of the proposed research is to create a design methodology that helps designers to more precisely control both portability and hardware-specific programming details. The proposed research emphasizes programming for scientific applications. We completed our study of the parallelizability of a subsystem of the NASA Earth Radiation Budget Experiment (ERBE) data processing system. This work is summarized in section two. A more detailed description is provided in Appendix A ('Programming Practices to Support Eventual Parallelism'). Mr. Chrisman, a graduate student, wrote and successfully defended a Ph.D. dissertation proposal which describes our research associated with the issues of software portability and high performance. The list of research tasks are specified in the proposal. The proposal 'A Design Methodology for Portable Software on Parallel Computers' is summarized in section three and is provided in its entirety in Appendix B. We are currently studying a proposed subsystem of the NASA Clouds and the Earth's Radiant Energy System (CERES) data processing system. This software is the proof-of-concept for the Ph.D. dissertation. We have implemented and measured the performance of a portion of this subsystem on the Intel iPSC/2 parallel computer. These results are provided in section four. Our future work is summarized in section five, our acknowledgements are stated in section six, and references for published papers associated with NAG-1-995 are provided in section seven

Off-line computing for experimental high-energy physics

The needs of experimental high-energy physics for large-scale computing and data handling are explained in terms of the complexity of individual collisions and the need for high statistics to study quantum mechanical processes. The prevalence of university-dominated collaborations adds a requirement for high-performance wide-area networks. The data handling and computational needs of the different types of large experiment, now running or under construction, are evaluated. Software for experimental high-energy physics is reviewed briefly with particular attention to the success of packages written within the discipline. It is argued that workstations and graphics are important in ensuring that analysis codes are correct, and the worldwide networks which support the involvement of remote physicists are described. Computing and data handling are reviewed showing how workstations and RISC processors are rising in importance but have not supplanted traditional mainframe processing. Examples of computing systems constructed within high-energy physics are examined and evaluated