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At least 1,261 records · Page 70

Accessing and Visualizing scientific spatiotemporal data

This paper discusses work done by JPL 's Parallel Applications Technologies Group in helping scientists access and visualize very large data sets through the use of multiple computing resources, such as parallel supercomputers, clusters, and grids These tools do one or more of the following tasks visualize local data sets for local users, visualize local data sets for remote users, and access and visualize remote data sets The tools are used for various types of data, including remotely sensed image data, digital elevation models, astronomical surveys, etc The paper attempts to pull some common elements out of these tools that may be useful for others who have to work with similarly large data sets.

data sets↗

Application of data flow concepts to a multigrid solver for the Euler equations

In this study a multigrid solver for Euler equations (FLO52R) was examined to determine its performance potential on a hypothetical computer using a data flow architecture. The proposed computer would require massive parallelism to realize its design performance. On the other hand this parallelism would be more easily realized than with a conventional vector processor such as the Cray-1S. Several changes to the proposed design substantially alleviated most of the remaining bottlenecks to parallel processing. Other changes allowed clearer definition of memory access and disk I/O. Finally, a portion of the algorithm was rewritten to improve parallel performance. With these changes, performance levels approaching that of a Cray-1S may be possible for a computer costing far less. Estimates are given for overall speed, memory, and network bandwidth, and for instruction memory requirements.

Merriam, M. L.↗

A distributed Clips implementation: dClips

A distributed version of the Clips language, dClips, was implemented on top of two existing generic distributed messaging systems to show that: (1) it is easy to create a coarse-grained parallel programming environment out of an existing language if a high level messaging system is used; and (2) the computing model of a parallel programming environment can be changed easily if we change the underlying messaging system. dClips processes were first connected with a simple master-slave model. A client-server model with intercommunicating agents was later implemented. The concept of service broker is being investigated.

Li, Y. Philip↗

Accessing and visualizing scientific spatiotemporal data

This paper discusses work done by JPL's Parallel Applications Technologies Group in helping scientists access and visualize very large data sets through the use of multiple computing resources, such as parallel supercomputers, clusters, and grids.

rendering↗

The Software Correlator of the Chinese VLBI Network

The software correlator of the Chinese VLBI Network (CVN) has played an irreplaceable role in the CVN routine data processing, e.g., in the Chinese lunar exploration project. This correlator will be upgraded to process geodetic and astronomical observation data. In the future, with several new stations joining the network, CVN will carry out crustal movement observations, quick UT1 measurements, astrophysical observations, and deep space exploration activities. For the geodetic or astronomical observations, we need a wide-band 10-station correlator. For spacecraft tracking, a realtime and highly reliable correlator is essential. To meet the scientific and navigation requirements of CVN, two parallel software correlators in the multiprocessor environments are under development. A high speed, 10-station prototype correlator using the mixed Pthreads and MPI (Massage Passing Interface) parallel algorithm on a computer cluster platform is being developed. Another real-time software correlator for spacecraft tracking adopts the thread-parallel technology, and it runs on the SMP (Symmetric Multiple Processor) servers. Both correlators have the characteristic of flexible structure and scalability.

Zheng, Weimin↗

Parallel Rendering of Large Time-Varying Volume Data

Interactive visualization of large time-varying 3D volume datasets has been and still is a great challenge to the modem computational world. It stretches the limits of the memory capacity, the disk space, the network bandwidth and the CPU speed of a conventional computer. In this SURF project, we propose to develop a parallel volume rendering program on SGI's Prism, a cluster computer equipped with state-of-the-art graphic hardware. The proposed program combines both parallel computing and hardware rendering in order to achieve an interactive rendering rate. We use 3D texture mapping and a hardware shader to implement 3D volume rendering on each workstation. We use SGI's VisServer to enable remote rendering using Prism's graphic hardware. And last, we will integrate this new program with ParVox, a parallel distributed visualization system developed at JPL. At the end of the project, we Will demonstrate remote interactive visualization using this new hardware volume renderer on JPL's Prism System using a time-varying dataset from selected JPL applications.

Garbutt, Alexander E.↗

Scalability of GlennICE in a Parallel Environment

The Glenn Icing Computational Environment (GlennICE) is a computational tool designed to calculate ice growth on complex three-dimensional geometries using the input from a user-supplied computational fluid dynamics (CFD) solution for the geometry of interest. The most significant developments in the advancement of GlennICE have been investigating the convergence of the collection efficiency, efficiently finding trajectories, and improving the refinement methodology. Such developments have increased the efficiency of GlennICE for practical engineering application. With the increasing demand for applying GlennICE for more memory-intensive problems, the scalability of GlennICE has yet to be investigated. This paper is aimed at presenting a method to benchmark the scalability of GlennICE utilizing a relevant engineering problem within a parallel environment. This leads to the final goal of investigating whether an increase in the number of processors utilized results in a linear speedup of the GlennICE software.

Computational Icing, Icing, CFD, MPI↗

An MPA-IO interface to HPSS

This paper describes an implementation of the proposed MPI-IO (Message Passing Interface - Input/Output) standard for parallel I/O. Our system uses third-party transfer to move data over an external network between the processors where it is used and the I/O devices where it resides. Data travels directly from source to destination, without the need for shuffling it among processors or funneling it through a central node. Our distributed server model lets multiple compute nodes share the burden of coordinating data transfers. The system is built on the High Performance Storage System (HPSS), and a prototype version runs on a Meiko CS-2 parallel computer.

Jones, Terry↗

Towards a fast implementation of spectral nested dissection

We describe the spectral nested dissection (SND) algorithm, a new algorithm for computing orderings appropriate for parallel factorization of sparse, symmetric matrices. The algorithm makes use of spectral properties of the Laplacian matrix associated with the given matrix to compute separators. We evaluate the quality of the spectral orderings with respect to several measures: fill, elimination tree height, height and weight balances of elimination trees, and clique tree heights. We use some very large structural analysis problems as test cases and demonstrate on these real applications (such as the Space Shuttle Solid Rocket Booster) that spectral orderings compare quite favorably with commonly used orderings, outperforming them by a wide margin for some of these measures. The only disadvantage of SND is its relatively long execution time. We will present some recent efforts to improve the execution time using both a multilevel and a hybrid approach. We use SND in computing a multifrontal numerical factorization with the different orderings on an eight processor Cray Y-MP and show its effectiveness. We believe that spectral nested dissection is a major breakthrough in terms of generating efficient sparse orderings for parallel machines.

Pothen, Alex↗

Complexity Computational Environment: Data Assimilation SERVOGrid

We are using Web (Grid) service technology to demonstrate the assimilation of multiple distributed data sources (a typical data grid problem) into a major parallel high-performance computing earthquake forecasting code. Such a linkage of Geoinformatics with Geocomplexity demonstrates the value of the Solid Earth Research Virtual Observatory (SERVO) Grid concept, and advance Grid technology by building the first real-time large-scale data assimilation grid Here we develop the next steps for both the SERVO concept and the identified need for a Solid Earth problem-solving environment. We use a challenging motivating problem of importance to NASA namely integrating NASA space geodetic observations with numerical simulations of a changing earth.

data assimiliation↗

Multiprogramming and the performance of parallel programs

A programming methodology is introduced that utilizes computational synchronization and avoids tight control flow synchronization in parallel programs. In this methodology, each phase of the computation is assigned a status that can be ready, blocked, or completed, and tasks in each computational phase are self-scheduled to ensure computational progress by the available executing processes. Results indicate that this methodology avoids the catastrophic performance losses resulting from the swapping of processes in multiprogrammed multiprocessors.

Benten, Muhammad S.↗

PVM Enhancement for Beowulf Multiple-Processor Nodes

A recent version of the Parallel Virtual Machine (PVM) computer program has been enhanced to enable use of multiple processors in a single node of a Beowulf system (a cluster of personal computers that runs the Linux operating system). A previous version of PVM had been enhanced by addition of a software port, denoted BEOLIN, that enables the incorporation of a Beowulf system into a larger parallel processing system administered by PVM, as though the Beowulf system were a single computer in the larger system. BEOLIN spawns tasks on (that is, automatically assigns tasks to) individual nodes within the cluster. However, BEOLIN does not enable the use of multiple processors in a single node. The present enhancement adds support for a parameter in the PVM command line that enables the user to specify which Internet Protocol host address the code should use in communicating with other Beowulf nodes. This enhancement also provides for the case in which each node in a Beowulf system contains multiple processors. In this case, by making multiple references to a single node, the user can cause the software to spawn multiple tasks on the multiple processors in that node.

Springer, Paul↗

Understanding and Improving High-Performance I/O Subsystems

This research program has been conducted in the framework of the NASA Earth and Space Science (ESS) evaluations led by Dr. Thomas Sterling. In addition to the many important research findings for NASA and the prestigious publications, the program has helped orienting the doctoral research program of two students towards parallel input/output in high-performance computing. Further, the experimental results in the case of the MasPar were very useful and helpful to MasPar with which the P.I. has had many interactions with the technical management. The contributions of this program are drawn from three experimental studies conducted on different high-performance computing testbeds/platforms, and therefore presented in 3 different segments as follows: 1. Evaluating the parallel input/output subsystem of a NASA high-performance computing testbeds, namely the MasPar MP- 1 and MP-2; 2. Characterizing the physical input/output request patterns for NASA ESS applications, which used the Beowulf platform; and 3. Dynamic scheduling techniques for hiding I/O latency in parallel applications such as sparse matrix computations. This study also has been conducted on the Intel Paragon and has also provided an experimental evaluation for the Parallel File System (PFS) and parallel input/output on the Paragon. This report is organized as follows. The summary of findings discusses the results of each of the aforementioned 3 studies. Three appendices, each containing a key scholarly research paper that details the work in one of the studies are included.

El-Ghazawi, Tarek A.↗

Data Structure and Parallel Decomposition Considerations on a Fibonacci Grid

The Fibonacci grid, proposed by Swinbank and Purser (see companion abstract), provides attractive properties for global numerical atmospheric prediction by offering an optimally homogeneous, geometrically regular, and approximately isotropic discretization, with only the polar regions requiring special numerical treatment. It is a mathematical idealization, applied to the sphere, of the multi-spiral patterns often found in botanical structures, such as in pine cones and sunflower heads. Computationally, it is natural to organize the domain, into zones, in each of which the same pair, or triple, of "Fibonacci spirals" dominate. But the further subdivision of such zones into "tiles" of a shape and size suitable for distribution to the processors of a massively parallel computer requires very careful consideration if the subsequent spatial computations along the respective spirals, especially those computations (such as compact differencing schemes) that involve recursion, can be implemented in an efficient "load-balanced "manner without requiring excessive amounts of inter-processor communications. In this paper we show how certain "number theoretic" properties of the Fibonacci sequence (whose numbers prescribe the multiplicity of successive spirals) may be exploited in the decomposition of grid zones into tidy arrangements of triangular grid tiles, each tile possessing one side approximately parallel to the constant-latitude zone boundary. We also describe how the spatially recursive processes may be decomposed across such a tiling, and the directionality of the recursions reversed on alternate grid lines, to ensure a very high degree of load balancing throughout the execution of the computations required for one time step of a global model.

Michalakes, John↗

Parallel matrix multiplication on the Connection Machine

Matrix multiplication is a computation and communication intensive problem. Six parallel algorithms for matrix multiplication on the Connection Machine are presented and compared with respect to their performance and processor usage. For n by n matrices, the algorithms have theoretical running times of O(n to the 2nd power log n), O(n log n), O(n), and O(log n), and require n, n to the 2nd power, n to the 2nd power, and n to the 3rd power processors, respectively. With careful attention to communication patterns, the theoretically predicted runtimes can indeed be achieved in practice. The parallel algorithms illustrate the tradeoffs between performance, communication cost, and processor usage.

Tichy, Walter F.↗

A VLSI Processor Engine to Support Calculation of the Vector Wave Equation

The development of a VLSI processor engine tailored to support computation of the near-field vector wave equation (VWE) is presented. Calculation of the near field is essential for evaluation of the electromagnetic fields generated by a complex radiating structure. The processor engine presented is optimized such that it takes advantage of the extensive parallelism inherent in the computational algorithm. The utilization of very large scale integration (VLSI) circuit technology and a customized reduced instruction set computer (RISC) architecture support development of a system of these processor engines, each of which is capable of performing the VWE algorithm calculation. By taking maximum advantage of the parallelism present in the calculation and dividing the problem among an array of these processor engines, the calculation can be computed in a realistic time frame.

J W Degroat↗

A Debugger for Computational Grid Applications

This viewgraph presentation gives an overview of a debugger for computational grid applications. Details are given on NAS parallel tools groups (including parallelization support tools, evaluation of various parallelization strategies, and distributed and aggregated computing), debugger dependencies, scalability, initial implementation, the process grid, and information on Globus.

Hood, Robert↗

Computations on Wings With Full-Span Oscillating Control Surfaces Using Navier-Stokes Equations

A dual-level parallel procedure is presented for computing large databases to support aerospace vehicle design. This procedure has been developed as a single Unix script within the Parallel Batch Submission environment utilizing MPIexec and runs MPI based analysis software. It has been developed to provide a process for aerospace designers to generate data for large numbers of cases with the highest possible fidelity and reasonable wall clock time. A single job submission environment has been created to avoid keeping track of multiple jobs and the associated system administration overhead. The process has been demonstrated for computing large databases for the design of typical aerospace configurations, a launch vehicle and a rotorcraft.

Equations↗