Manipulation of terrain data for a real-time display application

Recent progress in the algorithm as well as the processor power have made the dynamics simulation of complex kinematic chains more realistic in various fields such as human motion simulation and molecular dynamics. The computation can be further accelerated by employing parallel processing on multiple processors. In fact, parallel processing environment is becoming more affordable thanks to recent release of multiplecore processors. Although several parallel algorithms for the forward dynamics computation have been proposed in literature, there still remains the problem of automatic scheduling, or load distribution, for handling arbitrary kinematic chains on a given parallel processing environment. In this paper, we propose a method for finding the schedule that minimizes the computation time. We test the method using three human character models with different complexities and show that parallel processing on two processors reduces the computation time by 35–36%.

A programming system has been implemented in which annotated Petri nets are used as machine-processable high-evel design representations. The nets can be used to express the parallelism and the dynamic sequential dependencies found in complex software. They can then be interactively fired to facilitate debugging of the design. The nets are processed into a procedure language, called XL/1, to which a variety of transformations are applied in order to produce more efficient programs. These programs are generated for either a serial or a parallel processing environment. Finally, the XL/1 programs may be translated into PL/I or PL/S. The serial processing versions have been compiled and run successfully, but the parallel processing versions have not yet been run in a parallel processing environment.

Terrain database correlation is a major requirement for interoperability in distributed simulation. There are numerous situations in which terrain database correlation problems can occur that, in turn, lead to lack of interoperability in distributed training simulations. Examples are the use of different run-time terrain databases derived from inconsistent on source data, the use of different resolutions, and the use of different data models between databases for both terrain and culture data. IST has been developing a suite of software tools, named ZCAP, to address terrain database interoperability issues. In this paper we discuss recent enhancements made to this suite, including improved algorithms for sampling and calculating line-of-sight, an improved method for measuring terrain roughness, and the application of a sparse matrix method to the terrain remediation solution developed at the Visual Systems Lab of the Institute for Simulation and Training. We review the application of some of these new algorithms to the terrain correlation measurement processes. The application of these new algorithms improves our support for very large terrain databases, and provides the capability for performing test replications to estimate the sampling error of the tests. With this set of tools, a user can quantitatively assess the degree of correlation between large terrain databases.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Biodegrading plumes in groundwater are often typified by relatively reactive zones around the fringes and less reactive zones in the core. A high degree of refinement is required at the fringes if a model is to be of use in improving the conceptual understanding of plumes. Two strategies for dealing with the potentially high computational demands are (i) parallel processing, where the workload is shared between multiple processors, and (ii) locally adaptive remeshing, where a refined area of the grid tracks the moving plume fringes through the domain. The partial differential equation toolbox, UG (Unstructured Grids) offers advanced numerical tools including adaptive remeshing, sparse matrix storage schemes, and multigrid solvers. It embraces many of these features within a parallel processing environment. This paper reports on a recent development of UG to simulate field scale reactive biogeochemistry including Monod kinetics, NAPL dissolution, mineral precipitation/dissolution and ion exchange. The non-linear multicomponent reactive transport system is solved with the fully coupled method. Test cases have been used for verification of the new capability. The paper illustrates an application to a 3D field site. It is demonstrated that both adaptive remeshing and parallel processing can improve efficiency and in turn facilitate the incorporation of a more complex set of species and reactions such that understanding of plume processes is enhanced.

The paper presents a methodology for optimizing the design of large, complex, real-time systems in distributed and parallel processing environments. It can be used as a front-end component in a prototyping process providing increased capabilities for system engineers. The method incorporates various optimization approaches including: heuristic, probabilistic, deterministic, and hybrids. These approaches are applied to the system design structuring techniques and resource allocation techniques to perform optimization and trade-off based on the classes of rules, classes of objective functions, classes of algorithms, sets of analytical equations, and sets of probabilistic reasoning, This method optimizes the system design structure and generates a near-optimal allocation of the logical systems functions onto the implementation resources to meet the overall system requirements.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Many advanced ground-based solar telescopes improve the spatial resolution of observation images using an adaptive optics (AO) system. As any AO correction remains only partial, it is necessary to use post-processing image reconstruction techniques such as speckle masking or shift-and-add (SAA) to reconstruct a high-spatial-resolution image from atmospherically degraded solar images. In the New Vacuum Solar Telescope (NVST), the spatial resolution in solar images is improved by frame selection and SAA. In order to overcome the burden of massive speckle data processing, we investigate the possibility of using the speckle reconstruction program in a real-time application at the telescope site. The code has been written in the C programming language and optimized for parallel processing in a multi-processor environment. We analyze the scalability of the code to identify possible bottlenecks, and we conclude that the presented code is capable of being run in real-time reconstruction applications at NVST and future large aperture solar telescopes if care is taken that the multi-processor environment has low latencies between the computation nodes.

Current and future parallel computing model has been suggested for running and solving large-scale application problems such as climate, bio, cryptology, and astronomy, etc. Parallel computing is a form of computation in which many calculations are carried out simultaneously. And we are able to shorten the execution time of the program, as well as can extend the scale of the problem that can be solved. In this paper, we perform the actual cryptographic algorithms through parallel processing and evaluate its efficiency. Length of the key, which is stable criterion of cryptographic algorithm, judged according to the amount of complete enumeration computation. So we present a detailed procedure of DES key search cryptographic algorithms for executing of enumeration computation in parallel processing environment. And then, we did the simulation through applying to clustering system. As a result, we can measure the safety and solidity of cryptographic algorithm.

SummaryPower system monitoring relies on the reliability of state estimation (SE) results. SE plays a dominant role in data debugging if sufficient data is available. Criticality analysis (CA) integrates SE as a module in which measurements—taken one‐by‐one or in groups (tuples) of minimal cardinality—are designated crucial. The combinatorial nature of extensive CA (not restricted to identifying low‐cardinality critical tuples) characterizes its computational complexity and imposes challenging limits to go beyond. In simple terms, these limits are established by the number of measurements to be combined, the cardinality of tuples, and the computing time required to check the criticality condition. This paper proposes an innovative computational solution to expand CA limits found to date in the literature. A framework with multi‐threads designed cleverly on a graphics processing unit (GPU) parallel processing environment is built. The conceived architecture favors evaluating massive measurement combinations of diverse cardinality in extensive CA. Numerical results reveal significant speed‐ups with the proposed approach, contrasting with those reported in research efforts published so far.

Automated Hard Real-Time Scheduling

The development of a systematic procedure for evolving a computational model that is particularly amenable for parallel processing in a multiprocessor environment is described. Any real-time system may be represented in general by a set of differential equations which govern the dynamic behavior of the system. As a specific example, a prototype real-time control problem is modeled as a set of differential equations. These are mapped onto a task graph which is then allocated to a set of processors in accordance with an allocation algorithm. This is followed by a verification and comparison stage wherein the results of such a mapping are compared with those of traditional uniprocessor methods in terms of speed-up ratio, efficiency, and average processor utilization. Results of simulation and scheduling are compared on the basis of standard performance indices. >

A real-time interactive orthographic-view image display of integral imaging (II) microscopy that includes the generation of intermediate-view elemental images (IVEIs) for resolution enhancement is proposed. Unlike the conventional II microscopes, parallel processing through a graphics processing unit is required for real-time display that generates the IVEIs and interactive orthographic-view images in high speed, according to the user interactive input. The real-time directional-view display for the specimen for which 3D information is acquired through II microscopy is successfully demonstrated by using resolution-enhanced elemental image arrays. A user interactive feature is also satisfied in the proposed real-time interactive display for II microscopy.

This paper proposes an architecture for accomplishing transport protocol processing at Gbps rates. The limitations of currently used transport protocols have been analyzed extensively in recent literature. Several benchmark studies have established the achievable throughput of ISO TP4 and TCP to be in the low Mbps range; several new protocols and implementation techniques have been proposed to achieve 100 Mbps and higher throughput rates. We briefly review some of these protocols and establish the need for a radically different approach to meet our objective. An estimate of the aggregate processing power required for Gbps throughput is developed. It is proposed that a cost effective and practical solution to the processing requirements could be based on a multi-processor system. The opportunities for parallel processing in a typical transport protocol are examined. Several alternate parallel processing approaches are examined and arguments are advanced for selecting a favored approach. A corresponding parallel processing architecture is described. Data structures used to preserve packet ordering and techniques for reducing contention in a multi-processing environment are discussed. An implementation methodology for conventional transport protocols (e.g. TP4) is outlined. Some suggestions are made for improving efficiency by making modifications to the protocol that do not compromise functionality. The performance achievable with this modified architecture is analyzed and some suggestions for further work are presented.

This chapter presents the main background knowledge relevant to the book. Sections 2.1 and 2.2 describe the areas of processing complex data and knowledge discovery in traditional databases. The task of clustering complex data is discussed in Sect. 2.3, while the task of labeling such kind of data is described in Sect. 2.4. Section 2.5 introduces the MapReduce framework, a promising tool for large scale data analysis, which has been proven to offer one valuable support to the execution of data mining algorithms in a parallel processing environment. Section 2.6 concludes the chapter.KeywordsComplex dataModerate-to-high dimensionality data Big dataSubspace clusteringProjected clustering Correlation clusteringLabeling MapReduceHadoop

Delta is an object-oriented code architecture based on the finite element method which enables simulation of a wide range of engineering mechanics problems in a parallel processing environment. Written in C{sup ++}, Delta is a natural framework for algorithm development and for research involving coupling of mechanics from different Engineering Science disciplines. To enhance flexibility and encourage code reuse, the architecture provides a clean separation of the major aspects of finite element programming. Spatial discretization, temporal discretization, and the solution of linear and nonlinear systems of equations are each implemented separately, independent from the governing field equations. Other attractive features of the Delta architecture include support for constitutive models with internal variables, reusable ``matrix-free`` equation solvers, and support for region-to-region variations in the governing equations and the active degrees of freedom. A demonstration code built from the Delta architecture has been used in two-dimensional and three-dimensional simulations involving dynamic and quasi-static solid mechanics, transient and steady heat transport, and flow in porous media.

Online makespan minimization is a classical problem in which a sequence of jobs $$\sigma = J_1, \ldots , J_n$$ź=J1,ź,Jn has to be scheduled on m identical parallel machines so as to minimize the maximum completion time of any job. In this paper we investigate the problem with an essentially new model of resource augmentation. More specifically, an online algorithm is allowed to build several schedules in parallel while processing $$\sigma $$ź. At the end of the scheduling process the best schedule is selected. This model can be viewed as providing an online algorithm with extra space, which is invested to maintain multiple solutions. The setting is of particular interest in parallel processing environments where each processor can maintain a single or a small set of solutions. As a main result we develop a $$(4/3+\varepsilon )$$(4/3+ź)-competitive algorithm, for any $$0<\varepsilon \le 1$$0<ź≤1, that uses a constant number of schedules. The constant is equal to $$1/\varepsilon ^{O(\log (1/\varepsilon ))}$$1/źO(log(1/ź)). We also give a $$(1+\varepsilon )$$(1+ź)-competitive algorithm, for any $$0<\varepsilon \le 1$$0<ź≤1, that builds a polynomial number of $$(m/\varepsilon )^{O(\log (1/\varepsilon ) / \varepsilon )}$$(m/ź)O(log(1/ź)/ź) schedules. This value depends on m but is independent of the input $$\sigma $$ź. The performance guarantees are nearly best possible. We show that any algorithm that achieves a competitiveness smaller than 4 / 3 must construct $$\Omega (m)$$Ω(m) schedules. Our algorithms make use of novel guessing schemes that (1) predict the optimum makespan of a job sequence $$\sigma $$ź to within a factor of $$1+\varepsilon $$1+ź and (2) guess the job processing times and their frequencies in $$\sigma $$ź. In (2) we have to sparsify the universe of all guesses so as to reduce the number of schedules to a constant. We remark that the competitive ratios achieved using parallel schedules are considerably smaller than those in the standard problem without resource augmentation. Furthermore they are at least as good and in most cases better than the ratios obtained with other means of resource augmentation for makespan minimization.