15834423
A quadratic programming approach to simultaneous buffer insertion/sizing and wire sizing
In this paper, we present a completely new approach to the problem of delay minimization by simultaneous buffer insertion and wire sizing for a wire. We show that the problem can be formulated as a convex quadratic program, which is known to be solvable in polynomial time. Nevertheless, we explore some special properties of our problem and derive an optimal and very efficient algorithm, modified active set method (MASM), to solve the resulting program. Given m buffers and a set of m discrete choices of wire width, the running time of our algorithm is O(mn/sup 2/) and is independent of the wire length in practice. For example, an instance of 100 buffers and 100 choices of wire width can be solved in 0.92 s. In addition, we extend MASM to consider simultaneous buffer insertion, buffer sizing, and wire sizing. The resulting algorithm MASM-BS is again optimal and very efficient. For example, with six choices of buffer size and 10 choices of wire width, the optimal solution for a 15000 /spl mu/m long wire can be found in 0.05 s. Besides, our formulation is so versatile that it is easy to consider other objectives like wire area or power dissipation, or to add constraints to the solution. Also, wire capacitance lookup tables, or very general wire capacitance models which can capture area capacitance, fringing capacitance, coupling capacitance, etc. can be used.
53246587
A revisit to floorplan optimization by Lagrangian relaxation
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.
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.
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
39715098
A Requirement-Based Project Estimation Approach
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.
7900750
A Web-service oriented framework for building SCORM compatible learning management systems
Managing the large amount of learning content involved in the development of an expandable learning management system (LMS) is a critical task for most educational organizations. In designing such a system, consideration must be given not only to the requirement of instructors and students, but also to the adaptive qualities of the system itself, because of the rapidly changing software environment. Unlike most enterprises, educational organization can't afford high system maintenance. Development of a flexible, expandable and reliable learning management system is, therefore, imperative. This paper proposes a Web service oriented framework in building a sharable content object reference model (SCORM) compatible LMS. We integrated the SCORM concept with distributed computing technologies to build the components of the LMS and demonstrate how these services can be configured to create a complete system. This framework increases reusability and reduces the maintenance requirements of the LMS. It provides a way for small educational organizations, with limited resources, to build a complete SCORM compatible LMS. In such an ideal situation, the content provider not only provides the content, but also the service for the consumers of that content.
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.