Zipcode is a message-passing and process-management system that was designed for multicomputers and homogeneous networks of computers in order to support libraries and large-scale multicomputer software. The system has evolved significantly over the last five years, based on our experiences and identified needs. Features of Zipcode that were originally unique to it, were its simultaneous support of static process groups, communication contexts, and virtual topologies, forming the "mailer" data structure. Point-to-point and collective operations reference the underlying group, and use contexts to avoid mixing up messages. Recently, we have added "gather-send" and "receive-scatter" semantics, based on persistent Zipcode "invoices," both as a means to simplify message passing, and as a means to reveal more potential runtime optimizations. Key features in Zipcode appear in the forthcoming MPI standard. Keywords: Static Process Groups, Contexts, Virtual Topologies, Point-to-Point Communica...

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The Multicomputer Toolbox is a set of "firstgeneration " scalable parallel libraries. The Toolbox includes sparse, dense, direct and iterative linear algebra, a stiff ODE/DAE solver, and an open software technology for additional numerical algorithms. The Toolbox has an object-oriented design; C-based strategies for classes of distributed data structures (including distributed matrices and vectors) as well as uniform calling interfaces are defined. At a high level in the Toolbox, data-distributionindependence (DDI) support is provided. DDI is needed to build scalable libraries, so that applications do not have to redistribute data before calling libraries. Data-distribution-independent mapping functions implement this capability. Data-distribution-independent algorithms are sometimes more efficient than fixeddata -distribution counterparts, because redistribution of data can be avoided. Underlying the system is a "performance and portability layer," which includes interfaces to sequent...

The Multicomputer Toolbox includes sparse, dense, and iterative scalable linear algebra libraries. Dense direct, and iterative linear algebra libraries are covered in this paper, as well as the distributed data structures used to implement these algorithms; concurrent BLAS are covered elsewhere. We discuss uniform calling interfaces and functionality for linear algebra libraries. We include a detailed explanation of how the level-3 dense LU factorization works, including features that support data distribution independence with a blocked algorithm. We illustrate the data motion for this algorithm, and for a representative iterative algorithm, PCGS. We conclude that data distribution independent libraries are feasible and highly desirable. Much work remains to be done in performance tuning of these algorithms, though good portability and application-relevance have already been achieved.

In this paper we describe our perspective of the issues and strategies involved in state-of-the-art scalable parallel library research and development. We divide the discussion into four key areas: data distribution independence, issues in redistribution, local storage schemes, and the role of poly-algorithms.

The draft of the MPI (Message-Passing Interface) standard was released at Supercomputing '93, November 1993. The final MPI document is expected to be released in mid-April of 1994. Language bindings for C and FORTRAN were included in the draft; however, a language binding for C++ was not included. MPI provides support for datatypes and topologies that is needed for developing numerical libraries, however the interfaces described in the MPI draft document for these two features have several disadvantages. In this paper we describe and offer examples of a C++ interface to MPI that can be used to build scalable, object-oriented numerical libraries in a language that directly supports objectoriented programming. We also introduce several ideas from the Zipcode message-passing library related to datatypes and topologies, then compare and contrast these to the MPI approach. The best ideas from both approaches are combined to make a better interface to datatypes and topologies. Work support...

Real-time or faster-than-real-time power system transient stability simulations will have significant impact on the future design and operations of both individual electrical utility companies and large interconnected power systems. The analysis involves solution of extremely large systems of differential and algebraic equations. Differential-Algebraic Equation (DAE) solvers have been used to solve problems similar in nature to the transient stability analysis (TSA) problem. This paper discusses the possibility of the use of the existing DAE solvers to solve the transient stability analysis application. We also discuss our research in developing a scalable, parallel DAE solver for use by the power system community and in related applications [13].

The Parallel Mathematics Libraries Project (PMLP), a joint effort of Intel, Lawrence Livermore National Laboratory, the Russian Federal Nuclear Laboratory (VNIIEF), and Mississippi State University (MSU), constitutes a concerted effort to create a supportable, comprehensive "Sparse Object-Oriented Mathematical Library suite."With overall design and software validation work at MSU, and most software development and testing at VNIIEF, this international collaboration brings objectoriented programming techniques and C++ to the task of providing linear and nonlinear algebraic-oriented algorithms for scientists and engineers. Language bindings for C, Fortran-77, and C++ are provided, offering the widest possible applicability. PMLP differs from other major library efforts in its systematic use of software engineering and design, including efforts to provide high performance, portability, and usability. In addition, important contributions of this effort, in design principles such as storageformat independence, data-distribution independence etc., which contributes towards the performance, ease-of-use, application interoperability and portability etc., will be highlighted. Finally,we will also provide an initial set of benchmarked results. 1

In this paper, we present a new, parallel, mathematical library suite for sparse matrices. The Parallel Mathematical Libraries Project (PMLP), a joint effort of Intel, Lawrence Livermore National Laboratory, the Russian Federal Nuclear Laboratory (VNIIEF), and Mississippi State University (MSU), constitutes a concerted effort to create a supportable, comprehensive "Sparse Object-oriented Mathematical Library Suite." With overall design and software validation work at MSU, most software development and testing at VNIIEF, and logistics and other miscellaneous support provided by LLNL and Intel, this international collaboration brings object-oriented programming techniques and C++ to the task of providing linear and non-linear algebraic-oriented algorithms for scientists and engineers. Language bindings for C, Fortran-77, and C++ are provided.