Adaptive rate control for H.264
This paper presents a rate control scheme for H.264 by introducing the concept of basic unit and a linear prediction model. The basic unit can be a macroblock (MB), a slice, or a frame. It can be used to obtain a trade-off between the overall coding efficiency and the bits fluctuation. The linear model is used to solve the chicken and egg dilemma existing in the rate control of H.264. Both constant bit rate (CBR) and variable bit rate (VBR) cases are studied. Our scheme has been adopted by H.264.

title: Adaptive rate control for H.264
abstract: This paper presents a rate control scheme for H.264 by introducing the concept of basic unit and a linear prediction model. The basic unit can be a macroblock (MB), a slice, or a frame. It can be used to obtain a trade-off between the overall coding efficiency and the bits fluctuation. The linear model is used to solve the chicken and egg dilemma existing in the rate control of H.264. Both constant bit rate (CBR) and variable bit rate (VBR) cases are studied. Our scheme has been adopted by H.264.

title: Basic Topological Models for Spatial Entities in 3-Dimensional Space
abstract: In recent years, models of spatial relations, especially topological relations, have attracted much attention from the GIS community. In this paper, some basic topologic models for spatial entities in both vector and raster spaces are discussed.It has been suggested that, in vector space, an open set in 1-D space may not be an open set any more in 2-D and 3-D spaces. Similarly, an open set in 2-D vector space may also not be an open set any more in 3-D vector spaces. As a result, fundamental topological concepts such as boundary and interior are not valid any more when a lower dimensional spatial entity is embedded in higher dimensional space. For example, in 2-D, a line has no interior and the line itself (not its two end-points) forms a boundary. Failure to recognize this fundamental topological property will lead to topological paradox. It has also been stated that the topological models for raster entities are different in Z2 and R2. There are different types of possible boundaries depending on the definition of adjacency or connectedness. If connectedness is not carefully defined, topological paradox may also occur. In raster space, the basic topological concept in vector space—connectedness—is implicitly inherited. This is why the topological properties of spatial entities can also be studied in raster space. Study of entities in raster (discrete) space could be a more efficient method than in vector space, as the expression of spatial entities in discrete space is more explicit than that in connected space.

title: An Efficient Sort-Based DDM Matching Algorithm for HLA Applications with a Large Spatial Environment
abstract: Simulation is a low cost and safe alternative to solve complex problems in various areas. To promote reuse and interoperability of simulation applications and link geographically dispersed simulation components, distributed simulation was introduced. The high level architecture (HLA) is the IEEE standard for distributed simulation. To optimize communication efficiency between simulation components, HLA defines a data distribution management (DDM) service group for filtering out unnecessary data exchange. It relies on the computation of overlap between update and subscription regions, which is called matching. In this paper, we propose an efficient sort-based DDM matching algorithm for HLA applications with a large spatial environment. A theoretical analysis of our algorithm concludes that it should have good storage and computational scalability. The experimental results have verified the theoretical conclusions by showing that our algorithm has much less storage requirement than the original sort-based matching algorithm and generally has the best computational performance when compared with region-based and the original sort-based matching algorithms.

title: Efficient and distributed computation of maximum multicast rates
abstract: The transmission of information within a data network is constrained by network topology and link capacities. In this paper, we study the fundamental upper bound of information multicast rates with these constraints, given the unique replicable and encodable property of information flows. Based on recent information theory advances in coded multicast rates, we are able to formulate the maximum multicast rate problem as a linear network optimization problem, assuming the general undirected network model. We then proceed to apply Lagrangian relaxation techniques to obtain (1) a necessary and sufficient condition for multicast rate feasibility, and (2) a subgradient solution for computing the maximum rate and the optimal routing strategy to achieve it. The condition we give is a generalization of the well-known conditions for the unicast and broadcast cases. Our subgradient solution takes advantage of the underlying network flow structure of the problem, and therefore outperforms general linear programming solving techniques. It also admits a natural intuitive interpretation, and is amenable to fully distributed implementations.

title: Factoring zero-dimensional ideals of linear partial differential operators
abstract: We present an algorithm for factoring a zero-dimensional left ideal in the ring <b>Q</b>(<i>x, y</i>) [∂<inf><i>x</i></inf>, ∂<inf><i>y</i></inf>], i.e. factoring a linear homogeneous partial differential system whose coefficients belong to <b>Q</b>(<i>x, y</i>), and whose solution space is finite-dimensional over <b>Q.</b> The algorithm computes all the zero-dimensional left ideals containing the given ideal. It generalizes the Beke-Schlesinger algorithm for factoring linear ordinary differential operators, and uses an algorithm for finding hyperexponential solutions of such ideals.

title: Experience in the Automatic Parallelization of Four Perfect-Benchmark Programs
abstract: This paper discusses the techniques used to hand-parallelize, for the Alliant FX/80, four Fortran programs from the Perfect-Benchmark suite. The paper also includes the execution times of the programs before and after the transformations. The four programs considered here were not effectively parallelized by the automatic translators available to the authors. However, most of the techniques used for hand parallelization, and perhaps all of them, have wide applicability and can be incorporated into existing translators.

title: Probabilistic Congestion Prediction with Partial Blockages
abstract: Fast and accurate routing congestion estimation is essential for optimizations such as floorplanning, placement, buffering, and physical synthesis that need to avoid routing congestion. Using a probabilistic technique instead of a global router has the advantage of speed and easy updating. Previously proposed probabilistic models (Lou, et al., 2001) (Westra et al., 2004) do not account for wiring that may already be fixed in the design, e.g., due to macro blocks or power rails. These "partial wiring blockages" certainly influence the global router, so they should also influence a probabilistic routing prediction algorithm. This work proposes a probabilistic congestion prediction metric that extends the work of (Westra et al., 2004) to model partial wiring blockages. The authors also show a new fast algorithm to efficiently generate the congestion map and demonstrate the effectiveness of our methods on real routing problems