ADF95: Tool for automatic differentiation of a FORTRAN code designed for large numbers of independent variables

ADF95 is a tool to automatically calculate numerical first derivatives for any mathematical expression as a function of user defined independent variables. Accuracy of derivatives is achieved within machine precision. ADF95 may be applied to any FORTRAN 77/90/95 conforming code and requires minimal changes by the user. It provides a new derived data type that holds the value and derivatives and applies forward differencing by overloading all FORTRAN operators and intrinsic functions. An efficient indexing technique leads to a reduced memory usage and a substantially increased performance gain over other available tools with operator overloading. This gain is especially pronounced for sparse systems with large number of independent variables. A wide class of numerical simulations, e.g., those employing implicit solvers, can profit from ADF95.Comment: 24 pages, 2 figures, 4 tables, accepted in Computer Physics Communication

AD in Fortran, Part 1: Design

We propose extensions to Fortran which integrate forward and reverse Automatic Differentiation (AD) directly into the programming model. Irrespective of implementation technology, embedding AD constructs directly into the language extends the reach and convenience of AD while allowing abstraction of concepts of interest to scientific-computing practice, such as root finding, optimization, and finding equilibria of continuous games. Multiple different subprograms for these tasks can share common interfaces, regardless of whether and how they use AD internally. A programmer can maximize a function F by calling a library maximizer, XSTAR=ARGMAX(F,X0), which internally constructs derivatives of F by AD, without having to learn how to use any particular AD tool. We illustrate the utility of these extensions by example: programs become much more concise and closer to traditional mathematical notation. A companion paper describes how these extensions can be implemented by a program that generates input to existing Fortran-based AD tools

The Taming of QCD by Fortran 90

We implement lattice QCD using the Fortran 90 language. We have designed machine independent modules that define fields (gauge, fermions, scalars, etc...) and have defined overloaded operators for all possible operations between fields, matrices and numbers. With these modules it is very simple to write QCD programs. We have also created a useful compression standard for storing the lattice configurations, a parallel implementation of the random generators, an assignment that does not require temporaries, and a machine independent precision definition. We have tested our program on parallel and single processor supercomputers obtaining excellent performances.Comment: Talk presented at LATTICE96 (algorithms) 3 pages, no figures, LATEX file with ESPCRC2 style. More information available at: http://hep.bu.edu/~leviar/qcdf90.htm

Using Java for distributed computing in the Gaia satellite data processing

In recent years Java has matured to a stable easy-to-use language with the flexibility of an interpreter (for reflection etc.) but the performance and type checking of a compiled language. When we started using Java for astronomical applications around 1999 they were the first of their kind in astronomy. Now a great deal of astronomy software is written in Java as are many business applications. We discuss the current environment and trends concerning the language and present an actual example of scientific use of Java for high-performance distributed computing: ESA's mission Gaia. The Gaia scanning satellite will perform a galactic census of about 1000 million objects in our galaxy. The Gaia community has chosen to write its processing software in Java. We explore the manifold reasons for choosing Java for this large science collaboration. Gaia processing is numerically complex but highly distributable, some parts being embarrassingly parallel. We describe the Gaia processing architecture and its realisation in Java. We delve into the astrometric solution which is the most advanced and most complex part of the processing. The Gaia simulator is also written in Java and is the most mature code in the system. This has been successfully running since about 2005 on the supercomputer "Marenostrum" in Barcelona. We relate experiences of using Java on a large shared machine. Finally we discuss Java, including some of its problems, for scientific computing.Comment: Experimental Astronomy, August 201

The impact of fourth generation computers on NASTRAN

The impact of 'fourth generation' computers (STAR 100 or ILLIAC 4) on NASTRAN is considered. The desired characteristics of large programs designed for execution on 4G machines are described

The space science data service: A study of its efficiencies and costs

Factors affecting the overall advantages and disadvantages of a centralized facility for both the data base and processing capability for NASA's Office of Space Science programs are examined in an effort to determine the best approach to data management in the light of the increasing number of data bits collected annually. Selected issues considered relate to software and storage savings, security precautions, and the phase-in plan. Information on the current mode of processing and on the potential impact of changes resulting from a conversion to a space science data base service was obtained from five user groups and is presented as an aid in determining the dollar benefits and advantages of a centralized system

Parallel Implementation of the PHOENIX Generalized Stellar Atmosphere Program

We describe the parallel implementation of our generalized stellar atmosphere and NLTE radiative transfer computer program PHOENIX. We discuss the parallel algorithms we have developed for radiative transfer, spectral line opacity, and NLTE opacity and rate calculations. Our implementation uses a MIMD design based on a relatively small number of MPI library calls. We report the results of test calculations on a number of different parallel computers and discuss the results of scalability tests.Comment: To appear in ApJ, 1997, vol 483. LaTeX, 34 pages, 3 Figures, uses AASTeX macros and styles natbib.sty, and psfig.st

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