Shared Arrangements: practical inter-query sharing for streaming dataflows

Current systems for data-parallel, incremental processing and view maintenance over high-rate streams isolate the execution of independent queries. This creates unwanted redundancy and overhead in the presence of concurrent incrementally maintained queries: each query must independently maintain the same indexed state over the same input streams, and new queries must build this state from scratch before they can begin to emit their first results. This paper introduces shared arrangements: indexed views of maintained state that allow concurrent queries to reuse the same in-memory state without compromising data-parallel performance and scaling. We implement shared arrangements in a modern stream processor and show order-of-magnitude improvements in query response time and resource consumption for interactive queries against high-throughput streams, while also significantly improving performance in other domains including business analytics, graph processing, and program analysis

Parallel algorithms for interactive manipulation of digital terrain models

Interactive three-dimensional graphics applications, such as terrain data representation and manipulation, require extensive arithmetic processing. Massively parallel machines are attractive for this application since they offer high computational rates, and grid connected architectures provide a natural mapping for grid based terrain models. Presented here are algorithms for data movement on the massive parallel processor (MPP) in support of pan and zoom functions over large data grids. It is an extension of earlier work that demonstrated real-time performance of graphics functions on grids that were equal in size to the physical dimensions of the MPP. When the dimensions of a data grid exceed the processing array size, data is packed in the array memory. Windows of the total data grid are interactively selected for processing. Movement of packed data is needed to distribute items across the array for efficient parallel processing. Execution time for data movement was found to exceed that for arithmetic aspects of graphics functions. Performance figures are given for routines written in MPP Pascal

Basic research planning in mathematical pattern recognition and image analysis

Fundamental problems encountered while attempting to develop automated techniques for applications of remote sensing are discussed under the following categories: (1) geometric and radiometric preprocessing; (2) spatial, spectral, temporal, syntactic, and ancillary digital image representation; (3) image partitioning, proportion estimation, and error models in object scene interference; (4) parallel processing and image data structures; and (5) continuing studies in polarization; computer architectures and parallel processing; and the applicability of "expert systems" to interactive analysis

Initial operating capability for the hypercluster parallel-processing test bed

The NASA Lewis Research Center is investigating the benefits of parallel processing to applications in computational fluid and structural mechanics. To aid this investigation, NASA Lewis is developing the Hypercluster, a multi-architecture, parallel-processing test bed. The initial operating capability (IOC) being developed for the Hypercluster is described. The IOC will provide a user with a programming/operating environment that is interactive, responsive, and easy to use. The IOC effort includes the development of the Hypercluster Operating System (HYCLOPS). HYCLOPS runs in conjunction with a vendor-supplied disk operating system on a Front-End Processor (FEP) to provide interactive, run-time operations such as program loading, execution, memory editing, and data retrieval. Run-time libraries, that augment the FEP FORTRAN libraries, are being developed to support parallel and vector processing on the Hypercluster. Special utilities are being provided to enable passage of information about application programs and their mapping to the operating system. Communications between the FEP and the Hypercluster are being handled by dedicated processors, each running a Message-Passing Kernel, (MPK). A shared-memory interface allows rapid data exchange between HYCLOPS and the communications processors. Input/output handlers are built into the HYCLOPS-MPK interface, eliminating the need for the user to supply separate I/O support programs on the FEP

Somoclu: An Efficient Parallel Library for Self-Organizing Maps

Somoclu is a massively parallel tool for training self-organizing maps on large data sets written in C++. It builds on OpenMP for multicore execution, and on MPI for distributing the workload across the nodes in a cluster. It is also able to boost training by using CUDA if graphics processing units are available. A sparse kernel is included, which is useful for high-dimensional but sparse data, such as the vector spaces common in text mining workflows. Python, R and MATLAB interfaces facilitate interactive use. Apart from fast execution, memory use is highly optimized, enabling training large emergent maps even on a single computer.Comment: 26 pages, 9 figures. The code is available at https://peterwittek.github.io/somoclu

Impact of an interactive anti-speeding threat appeal: how much threat is too much?

This study investigates the impact of an interactive television public service announcement (PSA) containing an anti-speeding threat appeal on feelings of telepresence and behavioral intention. In a 2 x 2 x 2 between-subjects factorial design with 213 participants, the level of threat evoked by a traditional PSA, by the interactive part of the PSA (dedicated advertising location) and by the preceding program context are manipulated to be either low or high. The results support the assumptions of the Extended Parallel Processing Model with regard to the effect of the level of perceived threat and perceived efficacy in an interactive media environment, and the important role of telepresence as a processing variable. The results of the three-way interaction effect of threat evoked by the program, the PSA, and the DAL on telepresence show that when the threat levels of the program and the PSA are both either low or high, exposure to the threatening information in the DAL does not generate a significantly higher feeling of telepresence. However, when a low-threat program is followed by a high-threat PSA, the threat level of the DAL has a positive effect on telepresence. The same trend is found with a high-threat program and a low-threat PSA, although the effect of the threat evoked by the DAL on telepresence is not significant at conventional levels. Finally, there is a positive effect of telepresence on the behavioral intention to reduce speeding which is partly mediated by the viewer‟s perceived efficacy to follow the recommended behavior

Ray Casting Architectures for Volume Visualization

Real-time visualization of large volume datasets demands high performance computation, pushing the storage, processing, and data communication requirements to the limits of current technology. General purpose parallel processors have been used to visualize moderate size datasets at interactive frame rates; however, the cost and size of these supercomputers inhibits the widespread use for real-time visualization. This paper surveys several special purpose architectures that seek to render volumes at interactive rates. These specialized visualization accelerators have cost, performance, and size advantages over parallel processors. All architectures implement ray casting using parallel and pipelined hardware. We introduce a new metric that normalizes performance to compare these architectures. The architectures included in this survey are VOGUE, VIRIM, Array Based Ray Casting, EM-Cube, and VIZARD II. We also discuss future applications of special purpose accelerators.Engineering and Applied Science