Engineering topics

Mehrotra, Piyush

Publications and source records attributed to Mehrotra, Piyush.

At least 37 records · Page 2

NASA NTRS2001

XML Based Scientific Data Management Facility

The World Wide Web consortium has developed an Extensible Markup Language (XML) to support the building of better information management infrastructures. The scientific computing community realizing the benefits of HTML has designed markup languages for scientific data. In this paper, we propose a XML based scientific data management facility, XDMF. The project is motivated by the fact that even though a lot of scientific data is being generated, it is not being shared because of lack of standards and infrastructure support for discovering and transforming the data. The proposed data management facility can be used to discover the scientific data itself, the transformation functions, and also for applying the required transformations. We have built a prototype system of the proposed data management facility that can work on different platforms. We have implemented the system using Java, and Apache XSLT engine Xalan. To support remote data and transformation functions, we had to extend the XSLT specification and the Xalan package.

Mehrotra, Piyush↗

NASA NTRS2000

High Performance Fortran for Aerospace Applications

This paper focuses on the use of High Performance Fortran (HPF) for important classes of algorithms employed in aerospace applications. HPF is a set of Fortran extensions designed to provide users with a high-level interface for programming data parallel scientific applications, while delegating to the compiler/runtime system the task of generating explicitly parallel message-passing programs. We begin by providing a short overview of the HPF language. This is followed by a detailed discussion of the efficient use of HPF for applications involving multiple structured grids such as multiblock and adaptive mesh refinement (AMR) codes as well as unstructured grid codes. We focus on the data structures and computational structures used in these codes and on the high-level strategies that can be expressed in HPF to optimally exploit the parallelism in these algorithms.

Mehrotra, Piyush↗

NASA NTRS2000

Arcade: A Web-Java Based Framework for Distributed Computing

Distributed heterogeneous environments are being increasingly used to execute a variety of large size simulations and computational problems. We are developing Arcade, a web-based environment to design, execute, monitor, and control distributed applications. These targeted applications consist of independent heterogeneous modules which can be executed on a distributed heterogeneous environment. In this paper we describe the overall design of the system and discuss the prototype implementation of the core functionalities required to support such a framework.

Chen, Zhikai↗

NASA NTRS1999

Parallelization of a Multigrid Incompressible Viscous Cavity Flow Solver Using OpenMP

We describe a multigrid scheme for solving the viscous incompressible driven cavity problem that has been parallelized using OpenMP. The incremental parallelization allowed by OpenMP was of great help during the parallelization process. Results show good parallel efficiencies for reasonable problem sizes on an SGI Origin 2000. Since OpenMP allowed us to specify the number of threads (and in turn processors) at runtime, we were able to improve performance when solving on smaller/coarser meshes. This was accomplished by giving each processor a more reasonable amount of work rather than having many processors work on very small segments of the data (and thereby adding significant overhead).

Roe, Kevin↗

NASA NTRS1997

A Comparison of PETSC Library and HPF Implementations of an Archetypal PDE Computation

Two paradigms for distributed-memory parallel computation that free the application programmer from the details of message passing are compared for an archetypal structured scientific computation a nonlinear, structured-grid partial differential equation boundary value problem using the same algorithm on the same hardware. Both paradigms, parallel libraries represented by Argonne's PETSC, and parallel languages represented by the Portland Group's HPF, are found to be easy to use for this problem class, and both are reasonably effective in exploiting concurrency after a short learning curve. The level of involvement required by the application programmer under either paradigm includes specification of the data partitioning (corresponding to a geometrically simple decomposition of the domain of the PDE). Programming in SPAM style for the PETSC library requires writing the routines that discretize the PDE and its Jacobian, managing subdomain-to-processor mappings (affine global- to-local index mappings), and interfacing to library solver routines. Programming for HPF requires a complete sequential implementation of the same algorithm, introducing concurrency through subdomain blocking (an effort similar to the index mapping), and modest experimentation with rewriting loops to elucidate to the compiler the latent concurrency. Correctness and scalability are cross-validated on up to 32 nodes of an IBM SP2.

Hayder, M. Ehtesham↗

NASA NTRS1997

Opus: A Coordination Language for Multidisciplinary Applications

Data parallel languages, such as High Performance fortran, can be successfully applied to a wide range of numerical applications. However, many advanced scientific and engineering applications are multidisciplinary and heterogeneous in nature, and thus do not fit well into the data parallel paradigm. In this paper we present Opus, a language designed to fill this gap. The central concept of Opus is a mechanism called ShareD Abstractions (SDA). An SDA can be used as a computation server, i.e., a locus of computational activity, or as a data repository for sharing data between asynchronous tasks. SDAs can be internally data parallel, providing support for the integration of data and task parallelism as well as nested task parallelism. They can thus be used to express multidisciplinary applications in a natural and efficient way. In this paper we describe the features of the language through a series of examples and give an overview of the runtime support required to implement these concepts in parallel and distributed environments.

Chapman, Barbara↗

NASA NTRS1996

Thread Migration in the Presence of Pointers

Dynamic migration of lightweight threads supports both data locality and load balancing. However, migrating threads that contain pointers referencing data in both the stack and heap remains an open problem. In this paper we describe a technique by which threads with pointers referencing both stack and non-shared heap data can be migrated such that the pointers remain valid after migration. As a result, threads containing pointers can now be migrated between processors in a homogeneous distributed memory environment.

Cronk, David↗

NASA NTRS1995

Smartfiles: An OO approach to data file interoperability

Data files for scientific and engineering codes typically consist of a series of raw data values whose descriptions are buried in the programs that interact with these files. In this situation, making even minor changes in the file structure or sharing files between programs (interoperability) can only be done after careful examination of the data file and the I/O statement of the programs interacting with this file. In short, scientific data files lack self-description, and other self-describing data techniques are not always appropriate or useful for scientific data files. By applying an object-oriented methodology to data files, we can add the intelligence required to improve data interoperability and provide an elegant mechanism for supporting complex, evolving, or multidisciplinary applications, while still supporting legacy codes. As a result, scientists and engineers should be able to share datasets with far greater ease, simplifying multidisciplinary applications and greatly facilitating remote collaboration between scientists.

Haines, Matthew↗

NASA NTRS1995

Ropes: Support for collective opertions among distributed threads

Lightweight threads are becoming increasingly useful in supporting parallelism and asynchronous control structures in applications and language implementations. Recently, systems have been designed and implemented to support interprocessor communication between lightweight threads so that threads can be exploited in a distributed memory system. Their use, in this setting, has been largely restricted to supporting latency hiding techniques and functional parallelism within a single application. However, to execute data parallel codes independent of other threads in the system, collective operations and relative indexing among threads are required. This paper describes the design of ropes: a scoping mechanism for collective operations and relative indexing among threads. We present the design of ropes in the context of the Chant system, and provide performance results evaluating our initial design decisions.

Haines, Matthew↗

NASA NTRS1995

On the utility of threads for data parallel programming

Threads provide a useful programming model for asynchronous behavior because of their ability to encapsulate units of work that can then be scheduled for execution at runtime, based on the dynamic state of a system. Recently, the threaded model has been applied to the domain of data parallel scientific codes, and initial reports indicate that the threaded model can produce performance gains over non-threaded approaches, primarily through the use of overlapping useful computation with communication latency. However, overlapping computation with communication is possible without the benefit of threads if the communication system supports asynchronous primitives, and this comparison has not been made in previous papers. This paper provides a critical look at the utility of lightweight threads as applied to data parallel scientific programming.

Fahringer, Thomas↗

NASA NTRS1994

High Performance FORTRAN

High performance FORTRAN is a set of extensions for FORTRAN 90 designed to allow specification of data parallel algorithms. The programmer annotates the program with distribution directives to specify the desired layout of data. The underlying programming model provides a global name space and a single thread of control. Explicitly parallel constructs allow the expression of fairly controlled forms of parallelism in particular data parallelism. Thus the code is specified in a high level portable manner with no explicit tasking or communication statements. The goal is to allow architecture specific compilers to generate efficient code for a wide variety of architectures including SIMD, MIMD shared and distributed memory machines.

Mehrotra, Piyush↗

NASA NTRS1994

Directions in parallel programming: HPF, shared virtual memory and object parallelism in pC++

Fortran and C++ are the dominant programming languages used in scientific computation. Consequently, extensions to these languages are the most popular for programming massively parallel computers. We discuss two such approaches to parallel Fortran and one approach to C++. The High Performance Fortran Forum has designed HPF with the intent of supporting data parallelism on Fortran 90 applications. HPF works by asking the user to help the compiler distribute and align the data structures with the distributed memory modules in the system. Fortran-S takes a different approach in which the data distribution is managed by the operating system and the user provides annotations to indicate parallel control regions. In the case of C++, we look at pC++ which is based on a concurrent aggregate parallel model.

Bodin, Francois↗

NASA NTRS1994

An overview of the Opus language and runtime system

We have recently introduced a new language, called Opus, which provides a set of Fortran language extensions that allow for integrated support of task and data parallelism. lt also provides shared data abstractions (SDA's) as a method for communication and synchronization among these tasks. In this paper, we first provide a brief description of the language features and then focus on both the language-dependent and language-independent parts of the runtime system that support the language. The language-independent portion of the runtime system supports lightweight threads across multiple address spaces, and is built upon existing lightweight thread and communication systems. The language-dependent portion of the runtime system supports conditional invocation of SDA methods and distributed SDA argument handling.

Mehrotra, Piyush↗

NASA NTRS1994

Extending HPF for advanced data parallel applications

The stated goal of High Performance Fortran (HPF) was to 'address the problems of writing data parallel programs where the distribution of data affects performance'. After examining the current version of the language we are led to the conclusion that HPF has not fully achieved this goal. While the basic distribution functions offered by the language - regular block, cyclic, and block cyclic distributions - can support regular numerical algorithms, advanced applications such as particle-in-cell codes or unstructured mesh solvers cannot be expressed adequately. We believe that this is a major weakness of HPF, significantly reducing its chances of becoming accepted in the numeric community. The paper discusses the data distribution and alignment issues in detail, points out some flaws in the basic language, and outlines possible future paths of development. Furthermore, we briefly deal with the issue of task parallelism and its integration with the data parallel paradigm of HPF.

Chapman, Barbara↗

NASA NTRS1994

Runtime support for data parallel tasks

We have recently introduced a set of Fortran language extensions that allow for integrated support of task and data parallelism, and provide for shared data abstractions (SDA's) as a method for communications and synchronization among these tasks. In this paper we discuss the design and implementation issues of the runtime system necessary to support these extensions, and discuss the underlying requirements for such a system. To test the feasibility of this approach, we implement a prototype of the runtime system and use this to support an abstract multidisciplinary optimization (MDO) problem for aircraft design. We give initial results and discuss future plans.

Haines, Matthew↗

NASA NTRS1994

A software architecture for multidisciplinary applications: Integrating task and data parallelism

Data parallel languages such as Vienna Fortran and HPF can be successfully applied to a wide range of numerical applications. However, many advanced scientific and engineering applications are of a multidisciplinary and heterogeneous nature and thus do not fit well into the data parallel paradigm. In this paper we present new Fortran 90 language extensions to fill this gap. Tasks can be spawned as asynchronous activities in a homogeneous or heterogeneous computing environment; they interact by sharing access to Shared Data Abstractions (SDA's). SDA's are an extension of Fortran 90 modules, representing a pool of common data, together with a set of Methods for controlled access to these data and a mechanism for providing persistent storage. Our language supports the integration of data and task parallelism as well as nested task parallelism and thus can be used to express multidisciplinary applications in a natural and efficient way.

Chapman, Barbara↗

NASA NTRS1993

Dynamic data distributions in Vienna Fortran

Vienna Fortran is a machine-independent language extension of Fortran, which is based upon the Single-Program-Multiple-Data (SPMD) paradigm and allows the user to write programs for distributed-memory systems using global addresses. The language features focus mainly on the issue of distributing data across virtual processor structures. Those features of Vienna Fortran that allow the data distributions of arrays to change dynamically, depending on runtime conditions are discussed. The relevant language features are discussed, their implementation is outlined, and how they may be used in applications is described.

Chapman, Barbara↗

NASA NTRS1993

High performance FORTRAN without templates: An alternative model for distribution and alignment

Language extensions of FORTRAN are being developed which permit the user to map data structures to the individual processors of distributed memory machines. These languages allow a programming style in which global data references are used. Current efforts are focussed on designing a common basis for such languages, the result of which is known as High Performance Fortran (HPF). One of the central debates in the HPF effort revolves around the concept of templates, introduced as an abstract index space to which data could be aligned. A model for the mapping of data which provides the functionality of High Performance Fortran distributions without the use of templates is presented.

Chapman, Barbara↗