45880739
Optimal circuit clustering with variable interconnect delay
The paper aims at extending the circuit clustering algorithm of Rajaraman and Wong (1995) to handle a more sophisticated delay model, which practically takes variable interconnect delay into account. Our delay model is particularly applicable in allowing the back-annotation of actual delay information to drive the clustering process. We first show that the original algorithm fails to produce optimal solutions for this delay model. In order to solve the problem, a generalized algorithm based on an extension of Rajaraman and Wong is proposed such that the problem can be solved optimally while the polynomial time complexity is maintained.
30326495
Performance-driven channel pin assignment algorithms
In this paper we consider two channel pin assignment problems which take circuit performance into account. The first one is the module implementation selection problem. We are given a net span bound for each critical net and each module has several possible placements of its pins. Our objective is to minimize channel density while satisfying net span constraints. We proved that this problem is NP-complete. For the case when each module has at most 2 pin placements, the problem can be transformed to the 2-SAT problem and hence is polynomial time solvable. We present a heuristic based on this algorithm to solve the general case. The second problem we consider is the module shifting problem. We are given a set of modules whose relative ordering is fixed on each side of the channel but their exact positions are not fixed. We present a polynomial time algorithm to test the feasibility of satisfying the net span constraints by shifting the modules. The algorithm is based on formulating the problem as a special integer linear programming problem which is solvable in polynomial time. We also extend our algorithms to handle multiple channels. >
195349922
Routing for symmetric FPGAs and FPICs
33246096
Optimal net assignment
We study in this paper the net assignment problem subject to the capacity constraint, selection constraint and routing constraint. Given two adjacent channels separated by a cell row, and a set of nets in each of the two channels, this problem is to assign to the cell row a subset of nets in each channel such that without violating any given constraint, the sum of the remaining densities of the two channels is minimized. The capacity constraint requires the density caused by the nets, which are assigned to the cell row, to be no more than a user-specified number k, where k is no more than the number of tracks available for routing over that cell row. The selection constraint specifies in each channel the subset of nets which are candidates to be assigned to the cell row. The routing constraint requires each net to be either completely assigned to the cell row or to stay in its channel. This problem can find its application in modeling a practical over-the-cell routing problem in which the whole region over the cell row is two-layer routable for the nets in the two adjacent channels. We present an optimal algorithm to solve this problem and provide experimental results to support our algorithm. >
2339232
Maze routing with OPC consideration
47136995
Routing for symmetric FPGAs and FPICs
A new class of routing structures with fixed orthogonal wire segments and field programmable switches at the intersections of the wire segments is proposed. In comparison with the conventional two-dimensional field-programmable gate array (FPGA) routing structure, this class of routing structures has the advantage of using a smaller number of active programmable switches. An existing field-programmable interconnect chip (FPIC) routing structure can be included as a special case in our class of routing structures. Using a probabilistic model, we prove that complete routing can be achieved with a high degree of probability in a routing structure of this class in which the number of tracks in each channel approaches the lower bound asymptotically. We present a sequential routing algorithm based on the solution of the single net routing problem. We take into account the delay introduced by the active programmable switches on a routing path and formulate the single net routing problem as a node-weighted Steiner minimum tree (NWSMT) problem in a bipartite graph G. Since our single net routing problem is NP-complete, a polynomial time approximate algorithm is proposed. We prove that our single net routing algorithm produces an optimal solution for some special classes of bipartite graphs. In general, the solution obtained by our algorithm bas a performance bound of min{/spl Delta/(V/Z), |Z|-1}. Experimental results for several industrial circuits show a reduction of up to 41% in the number of active programmable switches when compared with corresponding results for the conventional FPGA routing structure.
32386430
An Object-Oriented BSP Tree Algorithm for Hidden Surface Removal
Since the BSP tree algorithm was introduced, many extended or applied algorithms for the original BSP tree algorithm have been reported. Most of the previous work dealt with polygons that are components of polyhedra. If a scene consists of many polyhedra and they are allowed to move, the management cost of a BSP tree becomes expensive and the size of the tree becomes large. This paper presents an object-oriented BSP tree algorithm that can more efficiently deal with a large number of moving polyhedra.
29522196
On uniquely intersectable graphs
Abstract The concept of unique intersectability of a graph is introduced; this is related to the intersection number of a graph. The triangle-free condition is sufficient but not necessary for a graph to be uniquely intersectable. Other results related to the intersection number of a graph and its unique intersectability are established. Four families of graphs with triangles are shown to be uniquely intersectable.
10441616
Automatic Gait Optimization with Gaussian Process Regression
Gait optimization is a basic yet challenging problem for both quadrupedal and bipedal robots. Although techniques for automating the process exist, most involve local function optimization procedures that suffer from three key drawbacks. Local optimization techniques are naturally plagued by local optima, make no use of the expensive gait evaluations once a local step is taken, and do not explicitly model noise in gait evaluation. These drawbacks increase the need for a large number of gait evaluations, making optimization slow, data inefficient, and manually intensive. We present a Bayesian approach based on Gaussian process regression that addresses all three drawbacks. It uses a global search strategy based on a posterior model inferred from all of the individual noisy evaluations. We demonstrate the technique on a quadruped robot, using it to optimize two different criteria: speed and smoothness. We show in both cases our technique requires dramatically fewer gait evaluations than state-of-the-art local gradient approaches.
15371718
Automatic Chromosome Classification Using Medial Axis Approximation and Band Profile Similarity
Automated chromosome classification is an essential task in cytogenetics and has been an important pattern recognition problem. Numerous attempts were made in the past to characterize chromosome to perform clinical and cancer cytogenetics research. It is important to determine optimum features and develop feature extraction schemes for chromosome classification. In this paper we propose novel approaches for medial axis determination and profile matching of human chromosome. The medial axis determination plays a critical role for precise and complete extraction of band patterns of chromosomes. The features of the band profile obtained along the axis are then used in the classification process. In particular, the medial axis is obtained by simple cross-section analysis and the classification is accomplished through iterative pairing of band profiles. According to the experimental results, the developed automatic system can efficiently extract band profiles of the chromosomes along their medial axes, and satisfactory chromosome classification results can be obtained.
5669766
Automatic Estimation of 3D Transformations using Skeletons for Object Alignment
An algorithm for automatic estimation of 3D transformations between two objects is presented in this paper. Skeletons of the 3D objects are created using a fully parallel thinning technique, feature point pairs (land markers) are automatically extracted from skeletons, and a least squares method is applied to solve an over determined linear system to estimate the 3D transformation matrix. Experiments show that this method is quite accurate when the translations and rotation angles are small, even when there is some noise in the data. The estimation process requires about 2 seconds on an Intel Centrino Laptop with 512 MB memory, for a complex model with about 37,000 object points and 500 object points for its skeletons