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All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Data Parallel Line Relaxation (DPLR) Code User Manual: Acadia - Version 4.01.1

Data-Parallel Line Relaxation (DPLR) code is a computational fluid dynamic (CFD) solver that was developed at NASA Ames Research Center to help mission support teams generate high-value predictive solutions for hypersonic flow field problems. The DPLR Code Package is an MPI-based, parallel, full three-dimensional Navier-Stokes CFD solver with generalized models for finite-rate reaction kinetics, thermal and chemical non-equilibrium, accurate high-temperature transport coefficients, and ionized flow physics incorporated into the code. DPLR also includes a large selection of generalized realistic surface boundary conditions and links to enable loose coupling with external thermal protection system (TPS) material response and shock layer radiation codes.

Wright, Michael J.↗
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 NTRS1979

Codes for a priority queue on a parallel data bus

Some codes for arbitration of priorities among subsystem computers or peripheral device controllers connected to a parallel data bus are described. At arbitration time, several subsystems present wire-OR, parallel code words to the bus, and the central computer can identify the subsystem of highest priority and determine which of two or more transmission services the subsystem requires. A mathematical discussion of the optimality of the codes with regard to the number of subsystems that may participate in the scheme for a given number of wires is presented along with the number of services that each subsystem may request.

Wallis, D. E.↗
NASA NTRS1993

Generating local addresses and communication sets for data-parallel programs

Generating local addresses and communication sets is an important issue in distributed-memory implementations of data-parallel languages such as High Performance FORTRAN. We show that, for an array A affinely aligned to a template that is distributed across p processors with a cyclic(k) distribution and a computation involving the regular section A(l:h:s), the local memory access sequence for any processor is characterized by a finite state machine of at most k states. We present fast algorithms for computing the essential information about these state machines, and extend the framework to handle multidimensional arrays. We also show how to generate communication sets using the state machine approach. Performance results show that this solution requires very little run-time overhead and acceptable preprocessing time.

Chatterjee, Siddhartha↗
NASA NTRS1993

Generating local addresses and communication sets for data-parallel programs

Generating local addresses and communication sets is an important issue in distributed-memory implementations of data-parallel languages such as High Performance Fortran. We show that for an array A affinely aligned to a template that is distributed across p processors with a cyclic(k) distribution, and a computation involving the regular section A, the local memory access sequence for any processor is characterized by a finite state machine of at most k states. We present fast algorithms for computing the essential information about these state machines, and extend the framework to handle multidimensional arrays. We also show how to generate communication sets using the state machine approach. Performance results show that this solution requires very little runtime overhead and acceptable preprocessing time.

Chatterjee, Siddhartha↗
NASA NTRS1994

Data-parallel lower-upper relaxation method for reacting flows

The implicit lower-upper symmetric Gauss-Seidel (LU-SGS) method of Yoon and Jameson is modified for use on massively parallel computers. The method has been implemented on the Thinking Machines CM-5 and the MasPar MP-1 and MP-2, where large percentages of the theoretical peak floating point performance are obtained. It is shown that the new data-parallel LU relaxation method has better convergence properties than the original method for two different inviscid compressible flow simulations. The convergence is also improved for five-species reacting air computations. The performance of the method on various partitions of the CM-5 and on the MasPar computers is discussed. The new method shows promise for the efficient simulation of very large perfect gas and reacting flows.

Candler, Graham V.↗
NASA NTRS1992

Data parallel sorting for particle simulation

Sorting on a parallel architecture is a communications intensive event which can incur a high penalty in applications where it is required. In the case of particle simulation, only integer sorting is necessary, and sequential implementations easily attain the minimum performance bound of O (N) for N particles. Parallel implementations, however, have to cope with the parallel sorting problem which, in addition to incurring a heavy communications cost, can make the minimun performance bound difficult to attain. This paper demonstrates how the sorting problem in a particle simulation can be reduced to a merging problem, and describes an efficient data parallel algorithm to solve this merging problem in a particle simulation. The new algorithm is shown to be optimal under conditions usual for particle simulation, and its fieldwise implementation on the Connection Machine is analyzed in detail. The new algorithm is about four times faster than a fieldwise implementation of radix sort on the Connection Machine.

Dagum, Leonardo↗
NASA NTRS1990

Balancing Loads Among Parallel Data Processors

Heuristic algorithm minimizes amount of memory used by multiprocessor system. Distributes load of many identical, short computations among multiple parallel digital data processors, each of which has its own (local) memory. Each processor operates on distinct and independent set of data in larger shared memory. As integral part of load-balancing scheme, total amount of space used in shared memory minimized. Possible applications include artificial neural networks or image processors for which "pipeline" and vector methods of load balancing inappropriate.

Baffes, Paul Thomas↗
NASA NTRS1987

Optical Interferometric Parallel Data Processor

Image data processed faster than in present electronic systems. Optical parallel-processing system effectively calculates two-dimensional Fourier transforms in time required by light to travel from plane 1 to plane 8. Coherence interferometer at plane 4 splits light into parts that form double image at plane 6 if projection screen placed there.

Breckinridge, J. B.↗
NASA NTRS1993

A parallel data management system for large-scale NASA datasets

The past decade has experienced a phenomenal growth in the amount of data and resultant information generated by NASA's operations and research projects. A key application is the reprocessing problem which has been identified to require data management capabilities beyond those available today (PRAT93). The Intelligent Information Fusion (IIF) system (ROEL91) is an ongoing NASA project which has similar requirements. Deriving our understanding of NASA's future data management needs based on the above, this paper describes an approach to using parallel computer systems (processor and I/O architectures) to develop an efficient parallel database management system to address the needs. Specifically, we propose to investigate issues in low-level record organizations and management, complex query processing, and query compilation and scheduling.

Srivastava, Jaideep↗
NASA NTRS1992

Proposal for massively parallel data storage system

An architecture for integrating large numbers of data storage units (drives) to form a distributed mass storage system is proposed. The network of interconnected units consists of nodes and links. At each node there resides a controller board, a data storage unit and, possibly, a local/remote user-terminal. The links (twisted-pair wires, coax cables, or fiber-optic channels) provide the communications backbone of the network. There is no central controller for the system as a whole; all decisions regarding allocation of resources, routing of messages and data-blocks, creation and distribution of redundant data-blocks throughout the system (for protection against possible failures), frequency of backup operations, etc., are made locally at individual nodes. The system can handle as many user-terminals as there are nodes in the network. Various users compete for resources by sending their requests to the local controller-board and receiving allocations of time and storage space. In principle, each user can have access to the entire system, and all drives can be running in parallel to service the requests for one or more users. The system is expandable up to a maximum number of nodes, determined by the number of routing-buffers built into the controller boards. Additional drives, controller-boards, user-terminals, and links can be simply plugged into an existing system in order to expand its capacity.

Mansuripur, M.↗
NASA NTRS1985

Priority Queuing On A Parallel Data Bus

Queuing strategy for communications along shared data bus minimizes number of data lines while always assuring user of highest priority given access to bus. New system handles up to 32 user demands on 17 data lines that previously serviced only 17 demands.

Wallis, D. E.↗
NASA NTRS1989

A fast sorting algorithm for a hypersonic rarefied flow particle simulation on the connection machine

The data parallel implementation of a particle simulation for hypersonic rarefied flow described by Dagum associates a single parallel data element with each particle in the simulation. The simulated space is divided into discrete regions called cells containing a variable and constantly changing number of particles. The implementation requires a global sort of the parallel data elements so as to arrange them in an order that allows immediate access to the information associated with cells in the simulation. Described here is a very fast algorithm for performing the necessary ranking of the parallel data elements. The performance of the new algorithm is compared with that of the microcoded instruction for ranking on the Connection Machine.

Dagum, Leonardo↗
NASA NTRS1990

On the suitability of the connection machine for direct particle simulation

The algorithmic structure was examined of the vectorizable Stanford particle simulation (SPS) method and the structure is reformulated in data parallel form. Some of the SPS algorithms can be directly translated to data parallel, but several of the vectorizable algorithms have no direct data parallel equivalent. This requires the development of new, strictly data parallel algorithms. In particular, a new sorting algorithm is developed to identify collision candidates in the simulation and a master/slave algorithm is developed to minimize communication cost in large table look up. Validation of the method is undertaken through test calculations for thermal relaxation of a gas, shock wave profiles, and shock reflection from a stationary wall. A qualitative measure is provided of the performance of the Connection Machine for direct particle simulation. The massively parallel architecture of the Connection Machine is found quite suitable for this type of calculation. However, there are difficulties in taking full advantage of this architecture because of lack of a broad based tradition of data parallel programming. An important outcome of this work has been new data parallel algorithms specifically of use for direct particle simulation but which also expand the data parallel diction.

Dagum, Leonard↗
NASA NTRS1999

Reconstruction of the 1997/1998 El Nino from TOPEX/POSEIDON and TOGA/TAO Data Using a Massively Parallel Pacific-Ocean Model and Ensemble Kalman Filter

Two massively parallel data assimilation systems in which the model forecast-error covariances are estimated from the distribution of an ensemble of model integrations are applied to the assimilation of 97-98 TOPEX/POSEIDON altimetry and TOGA/TAO temperature data into a Pacific basin version the NASA Seasonal to Interannual Prediction Project (NSIPP)ls quasi-isopycnal ocean general circulation model. in the first system, ensemble of model runs forced by an ensemble of atmospheric model simulations is used to calculate asymptotic error statistics. The data assimilation then occurs in the reduced phase space spanned by the corresponding leading empirical orthogonal functions. The second system is an ensemble Kalman filter in which new error statistics are computed during each assimilation cycle from the time-dependent ensemble distribution. The data assimilation experiments are conducted on NSIPP's 512-processor CRAY T3E. The two data assimilation systems are validated by withholding part of the data and quantifying the extent to which the withheld information can be inferred from the assimilation of the remaining data. The pros and cons of each system are discussed.

Keppenne, C. L.↗
NASA NTRS2001

Method and Apparatus for High Data Rate Demodulation

A method to demodulate BPSK or QPSK data using clock rates for the receiver demodulator of one-fourth the data rate is presented. This is accomplished through multirate digital signal processing techniques. The data is sampled with an analog-to-digital converter and then converted from a serial data stream to a parallel data stream. This signal processing requires a clock cycle four times the data rate. Once converted into a parallel data stream, the demodulation operations including complex baseband mixing, lowpass filtering, detection filtering, symbol-timing recovery, and carrier recovery are all accomplished at a rate one-fourth the data rate. The clock cycle required is one-sixteenth that required by a traditional serial receiver based on straight convolution. The high rate data demodulator will demodulate BPSK, QPSK, UQPSK, and DQPSK with data rates ranging from 10 Mega-symbols to more than 300 Mega-symbols per second. This method requires less clock cycles per symbol tan traditional serial convolution techniques.

Gerald J Grebowsky↗
NASA NTRS1980

Parallel access alignment network with barrel switch implementation for d-ordered vector elements

An alignment network between N parallel data input ports and N parallel data outputs includes a first and a second barrel switch. The first barrel switch fed by the N parallel input ports shifts the N outputs thereof and in turn feeds the N-1 input data paths of the second barrel switch according to the relationship X=k.sup.y modulo N wherein x represents the output data path ordering of the first barrel switch, y represents the input data path ordering of the second barrel switch, and k equals a primitive root of the number N. The zero (0) ordered output data path of the first barrel switch is fed directly to the zero ordered output port. The N-1 output data paths of the second barrel switch are connected to the N output ports in the reverse ordering of the connections between the output data paths of the first barrel switch and the input data paths of the second barrel switch. The second switch is controlled by a value m, which in the preferred embodiment is produced at the output of a ROM addressed by the value d wherein d represents the incremental spacing or distance between data elements to be accessed from the N input ports, and m is generated therefrom according to the relationship d=k.sup.m modulo N.

Barnes, George H.↗
NASA NTRS1987

The use of transputers in processing telemetry data

Parallelism will be an essential ingredient of high performance systems of the future. The Inmos transputer is a high performance single-chip computer whose architecture facilitates the construction of parallel processing systems. Occam is a high level language developed for use with the Inmos transputer. This paper describes a project to evaluate the feasibility of using the transputer to implement real time processing of telemetry data.

Delgado, Hugo M., Jr.↗