Dennis J.-H. Huang

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Recent work has illustrated the promise ofmultilevel approaches for partitioning large circuits. Multilevel partitioningrecursively clusters the instance until its size is smallerthan a given threshold, then unclusters the instance while applyinga partitioning refinement algorithm. Our multilevel partitioner usesa new technique to control the number of(More)
Iterative improvement partitioning algorithms such as those due to Fiduccia and Mattheyses (FM) [2] and Krishnamurthy [5] exploit an e cient gain bucket data structure in selecting modules that are moved from one partition to the other. In this paper, we investigate three gain bucket implementations and their e ect on the performance of the FM partitioning(More)
Motivated by analysis of distributed RC delay in routing trees, we propose a new tree construction for performance-driven global routing which directly trades o between Prim's minimum spanning tree algorithm and Dijkstra's shortest path tree algorithm. This direct combination of two objective functions and their corresponding optimal algorithms contrasts(More)
A linear wirelength objective more e ectively captures timing, congestion, and other global placement considerations than a squared wirelength objective. The GORDIAN-L cell placement tool [16] minimizes linear wirelength by rst approximating the linear wirelength objective by a modi ed squared wirelength objective, then executing the following loop { (1)(More)
The "quadratic placement" methodology is rooted in [Module Placement Based on Resistive Network Optimization, Proud: A Sea-Of-Gate Placement Algorithm, A Combined Force and Cut Algorithm for Hierarchical VLSI Layout]and is reputedly used in many commercial and in-house tools forplacement of standard-cell and gate-array designs. The methodologyiterates(More)
We show how to quantify the suboptimality of heuristic algorithms for NP-hard problems arising in VLSI layout. Our approach is based on the notion of constructing new scaled instances from an initial problem instance. From the given problem instance, we essentially construct doubled, tripled, etc. instances which have optimum solution costs at most twice,(More)
ePlace is a generalized analytic algorithm to handle large-scale standard-cell and mixed-size placement. We use a novel density function based on electrostatics to remove overlap and Nesterov's method to minimize the nonlinear cost. Steplength is estimated as the inverse of Lipschitz constant, which is determined by our dynamic prediction and backtracking(More)
Top-down partitioning has focused on minimum cut or ratio cut objectives, while bottom-up clustering has focused on density-based objectives. In seeking a more unified perspective, we propose a new sum of densities measure for multi-way circuit decomposition, where the density of a subhypergraph is the ratio of the number of edges to the number of nodes in(More)
Estrogen receptor (ER) and progesterone receptor (PR) status in breast carcinomas are considered validated predictive factors for selecting patients for antihormonal therapy. Published surveys have shown a significant rate of disagreement and lack of reproducibility of immunohistochemistry (IHC) results from laboratories around the world. To address these(More)