Parallel Trellis Based Stereo Matching Using Constraints

Usually, the stereo correspondence for a feature point in the first image is obtained by searching in a predefined region of the second image, based on the epipolar line and the maximum disparity. The reduction of the search region can increase the performance of the matching process, in the context of the execution time and the accuracy. For edge-based stereo correspondence, we obtain the relationship between the maximum search space in the second image and the parameters like relative position of the edges, the disparity under consideration and the focal length. Considering the maximum of the disparity gradient in the real scene, we formulate the relation between the maximum search space in the second images with respect to the relative displacement of the continuous edges (as the feature points) in the successive scan lines of the first images. Then regarding the pdf of the disparity gradient, we obtain the maximum of the disparity gradient based on parameters like disparity under consideration and focal length. Finally we develop some very fast stereo matching algorithms, based on the normalized cross correlation criteria (NCC) for different sizes of the matching block.

Exploring the Role of Domain Partitioning on Efficiency of Parallel Distributed Hydrologic Model Simulations Spatially distributed hydrologic models of watersheds and river basins are data and computation intensive because of the combined nature of hydrodynamics, complex forcings and heterogeneous parameter fields. Application of these models at fine temporal and spatial resolutions, and on large problem domains, is facilitated by parallel computation on multi-processor clusters. Notably, the computation efficiency of parallel simulations is crucially determined by the efficiency with which data are divided-and-distributed in a multiprocessor environment and how the information is shared between processors. While numerous data partitioning algorithms exist and have been extensively studied in computer science literature, detailed elucidation of the role of hydrologic model structure on data partitioning has not been presented yet. In addition, the relative role of computational load balance and interprocessor communication on parallel computation efficiency of a hydrologic model is not known. Considering the unstructured domain discretization scheme used in PIHM hydrologic model as an example, the paper first presents a generic methodology for incorporating hydrologic factors in optimal domain partitioning algorithms. The partitions are then used to explore the isolated role of computation load balance and interprocessor communication on parallel efficiency. Results confirm that parallel simulations on partitions that minimize interprocessor communication and divide the computational load equally are the most efficient. More importantly, load balance between processors is observed to be a more sensitive control on parallel efficiency than minimization of interprocessor communication. Further analyses of the efficiency and scalability of the parallel code for different partitioning configurations reveal a direct correspondence between parallel efficiency and theoretical metrics such as load balance ratio and communication to computation ratio. Results indicate that theoretical metrics can be used for the selection of best partitions before computationally intensive parallel simulations are performed. The study serves as a proof-of-concept evaluation of the impact of computation and communication on the efficiency of parallelized distributed hydrologic models at multiple resolutions.

Demonstrates that the vertical constraint graph (VCG) is not a complete representation of the vertical constraints of a channel, and proposes an edge-weight augmented VCG that is proved to be complete. Examples demonstrate the feasibility of a deterministic approach to the locally optimal resolution of cyclic vertical constraints when the information provided by the new model is used. >

The absence of explicit Green's functions for piezoelectric media has hindered progress in the modeling of material properties of piezoelectric materials for a long time. Due to the importance of piezoelectrics in smart structures, the construction of explicit Green's functions for such materials is highly desirable. We introduce here a method of integral transformation to construct the electroelastic Green's function for a piezoelectric hexagonal infinitely extended medium in explicit compact form. This Green's function gives the elastic displacements and electric potentials caused by a unit point force and a unit point charge, respectively. This explicit form of the Green's function is convenient for many applications due to its natural representation in a tensor basis of hexagonal symmetry. For vanishing piezoelectric coupling the derived Green's function coincides with two well known results: Kroner's expression for the elastic Green's functional tensor is reproduced and the electric part then coincides with the electric potential caused by a unit point charge. For spheroidal inclusions having the same electroelastic characteristics and orientation as the hexagonal matrix the constructed Green's function is used to obtain the electroelastic analogue of Eshelby tensor in explicitly form.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Transformer-based models, based on multi-head attention, have revolutionized the field of deep learning and have excelled in a wide range of tasks. The core computation task, multi-head attention, is typically carried out in distributed computing framework, where stragglers are the most important factor that affects inference efficiency. To this end, we propose to alleviate the effect of stragglers by coding techniques. In particular, polynomial coding is applied to the parallel computation of multi-head attention block, which achieves the optimal tradeoff between computation load and robustness against stragglers.

To reduce the processing time in Global Navigation Satellite System (GNSS) signal acquisition and tracking, we first propose a parallel method of signal acquisition and tracking as well as the associated software implementation in this paper. This paper applies the Message Passing Interface (MPI) and Open Multi-Processing (OpenMP) techniques for parallel computation implementation. This parallel method could put the multi-cores microprocessors to be efficiently used in GNSS signal acquisition and tracking processes. To further enhance the performance, this paper then proposes a new GNSS acquisition and tracking method, and it includes the multi-PRN code acquisition method we proposed in [Y. C. Lin and C. C. Sun, ION GNSS 2007] to reduce the acquisition processing time and a new FFT (Fast Fourier Transform)-based tracking method. This FFT-based tracking method combines the conventional tracking method and the FFT technique to track the incoming signal. Consequently, the tracking process is divided into two phases: detection and FFT-based phases. This proposed FFT-based tracking method can reduce the computational load as well. This new acquisition and tracking method will be combined with the above parallel method to gain the maximum improvement in GNSS signal acquisition and tracking. Finally, we use the real data collected by a software GNSS receiver to validate the proposed method. This paper will also conduct the comparison between the proposed method and the conventional GNSS acquisition and tracking method, and the comparison criterions are the computational load and the processing time. The experiment results of this paper show the effectiveness of this proposed approach for GNSS signal acquisition and tracking.

Dynamic load balancing for parallel GFD on NT networks

Micro-CT scans provide visualization of core samples that can be used to quantify physical properties important for subsurface flow including, as examples, porosity and pore size distribution, pore connectivity and permeability, amongst many others. 3D scans can deliver a very high level of detail, but at a cost of many hours of scan time. This also implies enormous numerical datasets and associated computational processing load. It is therefore important to understand (1) the voxel resolution that is required to retain physical structure fidelity (e.g., pore size and tortuosity) and (2) the smallest sample size that provides reliable and representative transport calculations (e.g., directional permeability and connectivity). As an application example, we analyze a 3D sandstone sample from the Chinchilla area of the Surat Basin comprising a cuboid of 6.6 mm × 6.6 mm × 12.276 mm. The CT image at 6.6 μm voxel resolution generates 1.86 billion grid elements. The work then examines the effect on physical properties and flow simulation of coarsening the voxel resolution, and reducing the physical size of the sample. For each of the different cases relating to voxel size, the major physical properties are evaluated. For different sample sizes at constant (small) voxel size, the fluid flow is modeled using a lattice Boltzmann method (LBM) on multicore supercomputers. The LBM is efficient and convenient for application in parallel computing, which is required to meet the computational resources needs of 3D simulations with large datasets. Comparison of the results obtained at different resolution scales reveals the minimum representative elementary volume (REV) for voxels to characterize the physical features of porous media, and for sample sizes that effectively eliminate boundary effects, capturing and describing the transport phenomena that underpin reservoir analysis.

Min–max-boundary domain decomposition

In this article we describe a set of canonical transformations of the image spaces that make the description of three-view geometry very simple. The transformations depend on the three-view geometry and the canonically transformed trifocal tensor $\mathcal {T}'$ takes the form of a sparse array where 17 elements in well-defined positions are zero, it has a linear relation to the camera matrices and to two of the fundamental matrices, a third order relation to the third fundamental matrix, a second order relation to the other two trifocal tensors, and first order relations to the 10 three-view all-point matching constraints. In this canonical form, it is also simple to determine if the corresponding camera configuration is degenerate or co-linear. An important property of the three canonical transformations of the images spaces is that they are in SO(3). The 9 parameters needed to determine these transformations and the 9 parameters that determine the elements of $\mathcal {T}'$ together provide a minimal parameterization of the tensor. It does not have problems with multiple maps or multiple solutions that other parameterizations have, and is therefore simple to use. It also provides an implicit representation of the trifocal internal constraints: the sparse canonical representation of the trifocal tensor can be determined if and only if it is consistent with its internal constraints. In the non-ideal case, the canonical transformation can be determined by solving a minimization problem and a simple algorithm for determining the solution is provided. This allows us to extend the standard linear method for estimation of the trifocal tensor to include a constraint enforcement as a final step, similar to the constraint enforcement of the fundamental matrix. Experimental evaluation of this extended linear estimation method shows that it significantly reduces the geometric error of the resulting tensor, but on average the algebraic estimation method is even better. For a small percentage of cases, however, the extended linear method gives a smaller geometric error, implying that it can be used as a complement to the algebraic method for these cases.

We present Armus, a dynamic verification tool for deadlock detection and avoidance specialised in barrier synchronisation. Barriers are used to coordinate the execution of groups of tasks, and serve as a building block of parallel computing. Our tool verifies more barrier synchronisation patterns than current state-of-the-art. To improve the scalability of verification, we introduce a novel event-based representation of concurrency constraints, and a graph-based technique for deadlock analysis. The implementation is distributed and fault-tolerant, and can verify X10 and Java programs. To formalise the notion of barrier deadlock, we introduce a core language expressive enough to represent the three most widespread barrier synchronisation patterns: group, split-phase, and dynamic membership. We propose a graph analysis technique that selects from two alternative graph representations: the Wait-For Graph, that favours programs with more tasks than barriers; and the State Graph, optimised for programs with more barriers than tasks. We prove that finding a deadlock in either representation is equivalent, and that the verification algorithm is sound and complete with respect to the notion of deadlock in our core language. Armus is evaluated with three benchmark suites in local and distributed scenarios. The benchmarks show that graph analysis with automatic graph-representation selection can record a 7-fold execution increase versus the traditional fixed graph representation. The performance measurements for distributed deadlock detection between 64 processes show negligible overheads.

With the increasing bevel of automation in assembly planning and assembly execution, it becomes more obvious that there is a gap between the output of a mechanical designer and an assembly planner. The question is: How to describe a designed assembly to an assembly planning system? The input to almost all the current reported automatic assembly planning systems is one-static-state of the final assembly configuration regardless the assembly is meant to be rigid or articulated. The inability to represent the assembly design completely, accurately and computationally has hindered the power of an assembly planner in dealing with articulated assemblies as simple as taking something out of a drawer. In this paper we identify a computational representation (specification) of an assembly. The basic idea of this representation is to use each oriented surface on a solid as a descriptive primitive and the symmetry group of the surface as a computational primitive. The relative motions (degree of freedom) under various contacts between a part or a subassembly and the rest of the assembly can be efficiently determined by computing these basic symmetry groups in a proved correct manner. The results reported in this paper lay out a more realistic and precise group theoretic framework than our previous work, and provide a concise, complete and computational representation for rigid and articulated assembly.

Data-Driven Learning of 3-Point Correlation Functions as Microstructure Representations

High-density recording and topographic analysis of the auditory oddball event-related potential in patients with schizophrenia

Design considerations of wide-band r-f (radio-frequency) transformers operating over a frequency range of 10 to 100 mc (megacycles) are reviewed. The complete basic equivalent circuit representation of transformers must be used in the analysis of the input impedance characteristics. A synthesized equivalent network is used in determining the critical transformer parameters. Experimental data and characteristics of a 25-watt, 20-to 70-megacycle unit are presented.