5,169 research outputs found
Turbomachinery CFD on parallel computers
The role of multistage turbomachinery simulation in the development of propulsion system models is discussed. Particularly, the need for simulations with higher fidelity and faster turnaround time is highlighted. It is shown how such fast simulations can be used in engineering-oriented environments. The use of parallel processing to achieve the required turnaround times is discussed. Current work by several researchers in this area is summarized. Parallel turbomachinery CFD research at the NASA Lewis Research Center is then highlighted. These efforts are focused on implementing the average-passage turbomachinery model on MIMD, distributed memory parallel computers. Performance results are given for inviscid, single blade row and viscous, multistage applications on several parallel computers, including networked workstations
A compiler approach to scalable concurrent program design
The programmer's most powerful tool for controlling complexity in program design is abstraction. We seek to use abstraction in the design of concurrent programs, so as to
separate design decisions concerned with decomposition, communication, synchronization, mapping, granularity, and load balancing. This paper describes programming and compiler techniques intended to facilitate this design strategy. The programming techniques are based on a core programming notation with two important properties: the ability to separate concurrent programming concerns, and extensibility with reusable programmer-defined
abstractions. The compiler techniques are based on a simple transformation system together with a set of compilation transformations and portable run-time support. The
transformation system allows programmer-defined abstractions to be defined as source-to-source transformations that convert abstractions into the core notation. The same
transformation system is used to apply compilation transformations that incrementally transform the core notation toward an abstract concurrent machine. This machine can be implemented on a variety of concurrent architectures using simple run-time support.
The transformation, compilation, and run-time system techniques have been implemented and are incorporated in a public-domain program development toolkit. This
toolkit operates on a wide variety of networked workstations, multicomputers, and shared-memory
multiprocessors. It includes a program transformer, concurrent compiler, syntax checker, debugger, performance analyzer, and execution animator. A variety of substantial
applications have been developed using the toolkit, in areas such as climate modeling and fluid dynamics
Simulation modelling and visualisation: toolkits for building artificial worlds
Simulations users at all levels make heavy use of compute resources to drive computational
simulations for greatly varying applications areas of research using different simulation
paradigms. Simulations are implemented in many software forms, ranging from highly standardised
and general models that run in proprietary software packages to ad hoc hand-crafted
simulations codes for very specific applications. Visualisation of the workings or results of a
simulation is another highly valuable capability for simulation developers and practitioners.
There are many different software libraries and methods available for creating a visualisation
layer for simulations, and it is often a difficult and time-consuming process to assemble a
toolkit of these libraries and other resources that best suits a particular simulation model. We
present here a break-down of the main simulation paradigms, and discuss differing toolkits and
approaches that different researchers have taken to tackle coupled simulation and visualisation
in each paradigm
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
A Survey on Parallel Architecture and Parallel Programming Languages and Tools
In this paper, we have presented a brief review on the evolution of parallel computing to multi - core architecture. The survey briefs more than 45 languages, libraries and tools used till date to increase performance through parallel programming. We ha ve given emphasis more on the architecture of parallel system in the survey
A Test Suite for High-Performance Parallel Java
The Java programming language has a number of features that make it attractive for writing high-quality, portable parallel programs. A pure object formulation, strong typing and the exception model make programs easier to create, debug, and maintain. The elegant threading provides a simple route to parallelism on shared-memory machines. Anticipating great improvements in numerical performance, this paper presents a suite of simple programs that indicate how a pure Java Navier-Stokes solver might perform. The suite includes a parallel Euler solver. We present results from a 32-processor Hewlett-Packard machine and a 4-processor Sun server. While speedup is excellent on both machines, indicating a high-quality thread scheduler, the single-processor performance needs much improvement
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