12805154
Efficient rectilinear Steiner tree construction with rectilinear blockages
Given n points on a plane, a rectilinear Steiner minimal tree (RSMT) connects these points through some extra points called Steiner points to achieve a tree with minimal total wire length. Taking blockages into account dramatically increases the problem complexity. It is extremely unlikely that an efficient optimal algorithm exists for rectilinear Steiner minimal tree construction with rectilinear blockages (RSMTRB). Although there exist some heuristic algorithms for this problem, they have either poor quality or expensive running time. In this paper, we propose an efficient and effective approach to solve RSMTRB. The connection graph we used in this approach is called spanning graph which only contains O(n) edges and vertices. An O(n log n) time algorithm is proposed to construct spanning graph for RSMTRB. The experimental results show that this approach can achieve a solution with significantly reduced wire length. The total run time increased is negligible in the whole design flow.
79941
Floorplan area minimization using Lagrangian relaxation
ABSTRACT Floorplan area minimization is an important problem because many modules have shape exibilities during the oorplanning stage. Area minimization in general non-slicing oorplan is a complicated problem. Many previous works have attempted to tackle this problem [9; 6; 5; 1] using heuristics or numerical methods but none of them can solve it optimally and e ciently. In this paper, we show how this problem can be solved optimally by a geometric programming using Lagrangian relaxation. The resulting Lagrangian relaxation subproblem is so simple that the size of each module can be found in constant time. We implemented our idea in a simulated annealing framework based on the sequence pair representation. The area minimization procedure is invoked in every iteration of the annealing process but the total execution time is still very much faster than that of the most updated previous work [4]. For a benchmark data with 49 modules, we take 19.5 hours using a 270 MHz Sun Ultra 5 while the convex programming approach in [4] takes seven days using a 250 MHz DEC Alpha. This area minimization method will be applicable to any other oorplanning algorithm which uses constraint graphs to nd module positions in the nal packing.
24078054
Greedy wire-sizing is linear time
The greedy wire-sizing algorithm (GWSA) has been experimentally shown to be very efficient, but no mathematical analysis on its convergence rate has ever been reported. In this paper, we consider GWSA for continuous wire sizing. We prove that GWSA converges linearly to the optimal solution, which implies that the run time of GWSA is linear with respect to the number of wire segments for any fixed precision of the solution. Moreover, we also prove that this is true for any starting solution. This is a surprising result because previously it was believed that in order to guarantee convergence, GWSA had to start from a solution in which every wire segment is set to the minimum (or maximum) possible width. Our result implies that GWSA can use a good starting solution to achieve faster convergence. We demonstrate this point by showing that the minimization of maximum delay and the minimization of area subject to maximum delay bound using Lagrangian relaxation can be sped up by more than 50%.
6347443
IPR: An Integrated Placement and Routing Algorithm
In nanometer-scale VLSI technologies, several interconnect issues like routing congestion and interconnect delay have become the main concerns in placement. However, all previous placement approaches optimize some very primitive interconnect models during placement. These models are far from the actual interconnect implementation in the routing stage. As a result, placement solution considered to be good by primitive interconnect models may turn out to be poor after routing. In addition, the placement may not even be routable and timing closure may not be achievable. In this paper, we propose to address the inconsistency between the placement and routing objectives by fully integrating global routing into placement. As a first attempt to this novel approach, we focus on routability issue. We call the proposed algorithm for routing congestion minimization IPR (integrated placement and routing). To ensure the algorithm to be computationally efficient, efficient placement and routing algorithms FastPlace, FastDP and FastRoute are integrated, and well-designed methods are proposed to integrate them efficiently and effectively. Experimental results show that IPR reduces overflow by 36%, global routing wirelength by 3.6%, and runtime by 36% comparing to ROOSTER, which is the previous best academic routability- driven placer.
52810492
Optimal cell flipping in placement and floorplanning
In a placed circuit, there are a lot of movable cells that can be flipped to further reduce the total wirelength, without affecting the original placement solution. We aim at solving this flipping problem optimally. However, solving such a problem optimally is non-trivial given the gigantic sizes of modern circuits. We are able to identify a large portion of cells (about 75%) of which the orientation (flipped or not flipped) can be determined independent of the orientations of all the other cells. We have derived three non-trivial conditions to identify those so called independent cells, strictly solvable cells and conditionally solvable cells. In this way, we can greatly reduce the number of cells whose orientations are dependent on each other. Finally, the cell flipping problem of the remaining dependent cells can be formulated as a mixed integer linear programming (MILP) problem and solved optimally. However, this may still be too slow for extremely large circuits and we have applied two other methods, linear programming (LP) and linear programming followed by mixed integer linear programming (LP+MILP) to solve the problem. Experimental results show that by identifying those independent and solvable cells first and applying the LP+MILP technique, we can solve this flipping problem effectively and obtain results just 0.01% more than the optimal. In addition, we can improve the wirelength and number of overflow tiles by 5% and 9% respectively on the floorplanning benchmarks
6722156
An efficient and effective detailed placement algorithm
In the past few years, there has been a lot of research in the area of global placement. In comparison, not much attention has been paid to the detailed placement problem. Existing detailed placers either fail to improve upon the excellent solution quality enabled by good global placers or are very slow. To handle the above problems, we focus on the detailed placement problem. We present an efficient and effective detailed placement algorithm to handle the wirelength minimization problem. The main contributions of our work are: (1) an efficient Global Swap technique to identify a pair of cells that can be swapped to reduce wirelength; (2) a flow that combines the Global Swap technique with other heuristics to produce very good wirelength; (3) an efficient single-segment clustering technique to optimally shift cells within a segment to minimize wirelength. On legalized mPL5 global placements on the IBM standard-cell benchmarks, our detailed placer can achieve 19.0%, 13.2% and 0.5% more wirelength reduction compared to Fengshui5.0, rowironing and Domino respectively. Correspondingly we are 3.6/spl times/ 2.8/spl times/ and 15/spl times/ faster. On the ISPD05 benchmarks (Gi-Joon Nam et al., 2005), we achieve 8.1% and 9.1% more wirelength reduction compared to Fengshui5.0 and rowironing respectively. Correspondingly we are 3.1/spl times/ and 2.3/spl times/ faster.
17686405
A time-series biclustering algorithm for revealing co-regulated genes
Although existing bicluster algorithms claimed to be able to discover co-regulated genes under a subset of given experiment conditions, they ignore the inherent sequential relationship between crucial time points and thus are not applicable to analyze time-series gene expression data. A simple and effective deletion-based algorithm, using the mean squared residue score as a measure, was developed to bicluster time-series gene expression data. While enforcing a threshold value for the score, the algorithm alternately eliminates genes and time points according to their correlation to the bicluster. To ensure the time locality, only the starting and ending points in the time interval are eligible for deletion. As a result, the number of genes and the length of time interval are simultaneously maximized. Our experimental results shown that the proposed method is capable of identifying co-regulated genes characterized by partial time-course data that previous methods failed to discover.
27561759
Splice site prediction using support vector machines with a Bayes kernel
One of the most important tasks in correctly annotating genes in higher organisms is to accurately locate the DNA splice sites. Although relatively high accuracy has been achieved by existing methods, most of these prediction methods are computationally extensive. Due to the enormous amount of DNA sequences to be processed, the computational speed is an important issue to consider. In this paper, we present a new machine learning method for predicting DNA splice sites, which first applies a Bayes feature mapping (kernel) to project the data into a new feature space and then uses a linear Support Vector Machine (SVM) as a classifier to recognize the true splice sites. The computation time is linear to the number of sequences tested, while the performance is notably improved compared with the Naive Bayes classifier in terms of classification accuracy, precision, and recall. Our classification results are also comparable to the solution quality obtained by the SVMs with polynomial kernels, while the speed of our proposed method is significantly faster. This is a notable improvement in computational modeling considering the huge amount of DNA sequences to be processed.
10162254
In-broker access control: towards efficient end-to-end performance of information brokerage systems
An XML brokerage system is a distributed XML database system that comprises data sources and brokers which, respectively, hold XML documents and document distribution information. However, all existing information brokerage systems view or handle query brokering and access control as two orthogonal issues: query brokering is a system issue that concerns costs and performance, while access control is a security issue that concerns information confidentiality. As a result, access control deployment strategies (in terms of where and when to do access control) and the impact of such strategies on end-to-end system performance are neglected by existing information brokerage systems. In addition, data source side access control deployment is taken-for-granted as the "right" thing to do. In this paper, we challenge this traditional, taken-for-granted access control deployment methodology, and argue that query brokering and access control are not two orthogonal issues because access control deployment strategies can have a significant impact on the "whole" system's end-to-end performance. We propose the first in-broker access control deployment strategy where access control is "pushed" from the boundary into the "heart" of the information brokerage system
41639900
An Evolutionary Fuzzy Multi-objective Approach to Cell Formation
Fuzzy mathematical programming (FMP) has been shown not only providing a better and more flexible way of representing the cell formation (CF) problem of cellular manufacturing, but also improving solution quality and computational efficiency. However, FMP cannot meet the demand of real-world applications because it can only be used to solve small-size problems. In this paper, we propose a heuristic genetic algorithm (HGA) as a viable solution for solving large-scale fuzzy multi-objective CF problems. Heuristic crossover and mutation operators are developed to improve computational efficiency. Our results show that the HGA outperforms the FMP and goal programming (GP) models in terms of clustering results, computational time, and user friendliness.
5646511
KTR: an efficient key management scheme for air access control
To provide secure access to data in wireless broadcast services, symmetric key-based encryption is used to ensure that only users who own the valid keys can decrypt the data. In this paper, we propose an efficient key management scheme (namely KTR) to handle key distribution with regarding to complex subscription options and user activities. KTR has the following advantages. First, it supports all subscription activities in wireless broadcast services. Second, in KTR, a user only needs to hold one set of keys for all subscribed programs, instead of separate sets of keys for each program. Third, KTR identifies the minimum set of keys that must be changed to ensure broadcast security and minimize the rekey cost. Our simulations show that KTR can save about 45% of communication overhead in the broadcast channel and about 50% of decryption cost for each user, compared with conventional approaches based on logical key hierarchy.