47282304
Buffer insertion with adaptive blockage avoidance
Buffer insertion is a fundamental technology for very large scale integration interconnect optimization. This work presents the repeater insertion with adaptive tree adjustment (RIATA) heuristic that directly extends van Ginneken's classic algorithm to handle blockages in the layout. Given a Steiner tree containing a Steiner point that overlaps a blockage, a local adjustment is made to the tree topology that enables additional buffer insertion candidates to be considered. This adjustment adapts to the demand on buffer insertion and is incurred only when it facilitates the maximal slack solution. RIATA can be combined with any performance-driven Steiner tree algorithm and permits various solution search schemes to achieve different solution quality and runtime tradeoffs. Experiments on several large nets confirms that high-quality solutions can be obtained through this technique with greater efficiency than simultaneous approaches.
1271597
An improved AMG-based method for fast power grid analysis
The continuing VLSI technology scaling leads to increasingly significant power supply fluctuations, which needs to be modeled accurately in circuit design and verification. Meanwhile, the huge size of power grid requires its analysis to be fast and highly scalable. Algebraic multigrid (AMG) has been recognized as a promising approach for fast power grid analysis. We propose several techniques to improve AMG-based power grid analysis: (1) dynamic reduction threshold; (2) weighted interpolation; and (3) a new error smoothing scheme. Experimental results on power grid with up to 1.6 million nodes show that these techniques can improve accuracy by over 10 times compared to a reported industrial method while retaining the same fast speed
11408697
Path-Based Buffer Insertion
Along with the progress of very-large-scale-integration technology, buffer insertion plays an increasingly critical role on affecting circuit design and performance. Traditional buffer insertion algorithms are mostly net based and therefore often result in suboptimal delay or unnecessary buffer expense due to the lack of global view. In this paper, we propose a novel path-based-buffer-insertion (PBBI) scheme which can overcome the weakness of the net-based approaches. We also discuss some potential difficulties of the PBBI approach and propose solutions to them. A fast estimation on buffered delay is employed to improve the solution quality. Gate sizing is also considered at the same time. Experimental results show that our method can efficiently reduce buffer/gate cost significantly (by 71% on average) when compared to traditional net-based approaches. To the best of our knowledge, this is the first work on path based buffer insertion and simultaneous gate sizing.
10406726
Associative Skew Clock Routing for Difficult Instances
In clock network synthesis, sometimes skew constraints are required only within certain groups of clock sinks and do not exist between different groups. This is the so-called associative skew clock routing problem. Although the number of constraints is reduced, the problem becomes more difficult to solve due to the enlarged solution space. The perhaps only previous work used a very primitive delay model and cannot handle difficult instances in which sink groups are intermingled. We reuse existing techniques to solve this problem, including the difficult instances, based on a more accurate and popular delay model. Experimental results show that our algorithm can reduce the total clock routing wirelength by 12% on average compared to greedy-DME which is one of the best zero skew routing algorithms
7189153
Antenna avoidance in layer assignment
The sustained progress of very-large-scale-integration (VLSI) technology has dramatically increased the likelihood of the antenna problem in the manufacturing process and calls for corresponding considerations in the routing stage. In this paper, the authors propose a technique that can handle the antenna problem during the layer-assignment (LA) stage, which is an important step between global routing and detailed routing. The antenna-avoidance problem is modeled as a tree-partitioning problem with a linear-time-optimal-algorithm solution. This algorithm is customized to guide antenna avoidance in the LA stage. A linear-time optimal jumper-insertion algorithm is also derived. Experimental results on benchmark circuits show that the proposed techniques can lead to an average of 76% antenna-violation reduction and 99% via-violation reduction.
28075982
Clock buffer polarity assignment for power noise reduction
17924285
StoryML: Enabling Distributed Interfaces for Interactive Media
This paper introduces an adaptive architecture for presenting interactive timed media onto distributed networked devices. The interactive presentation is documented in StoryML, an XMLbased language, and presented to multiple interface devices organized in an agent-based architecture.
2207402
Bias properties of infinitesimal perturbation analysis for systems with parallel servers
Abstract Infinitesimal pertubation analysis (IPA) is a technique for estimating derivatives of performance measures from a single simulation of a stochastic discrete-event system, which might, for example, be modeling a computer/communication network or a manufacturing system. Such derivative estimates are useful in sensitivity analysis of the system and in optimizing—or at least improving—the performance of the system through gradient algorithms. However, it is well-known that IPA gives biased estimates for systems with multiple servers (channels or machines) in parallel when the server characteristics are not identical. In this paper, we investigate the seriousness of the bias both theoretically and experimentally. From our study, we believe the IPA estimator is relatively insensitive to small differences in the service time distributions of the servers. Specifially, we conjecture that for nearly-identical servers, the bias is proportional to the square of the difference between the means of the service time distributions. To support this conjecture, we present a tractable analytical example and investigate, via simulation experiments, more general systems.
15489348
A Gradient Based Weighted Averaging Method for Estimation of Fingerprint Orientation Fields
Estimation of orientation fields is an essential module in a fingerprint recognition system. Conventional gradient based approaches are popular but very sensitive to noise. In this paper, we propose a new implementation that is more resistant to noise. Our basic idea is to conduct redundant estimation over four overlapping neighborhoods for each target block. Following this idea, we devise a weighted averaging scheme operated on the base blocks directly. Thus, each block (including the target one) in the overlapping neighborhoods has different impact on estimation of the dominant orientation fields. Our preliminary experiment results suggest that the proposed weighted averaging algorithm is more robust against noise in comparison with other gradient based methods.
15595451
HEMO: A Sustainable Multi-objective Evolutionary Optimization Framework
The capability of multi-objective evolutionary algorithms (MOEAs) to handle premature convergence is critically important when applied to real-world problems. Their highly multi-modal and discrete search space often makes the required performance out of reach to current MOEAs. Examining the fundamental cause of premature convergence in evolutionary search has led to proposing of a generic framework, named Hierarchical Fair Competition (HFC)[9], for robust and sustainable evolutionary search. Here an HFC-based Hierarchical Evolutionary Multi-objective Optimization framework (HEMO) is proposed, which is characterized by its simultaneous maintenance of individuals of all degrees of evolution in hierarchically organized repositories, by its continuous inflow of random individuals at the base repository, by its intrinsic hierarchical elitism and hyper-grid-based density estimation. Two experiments demonstrate its search robustness and its capability to provide sustainable evolutionary search for difficult multi-modal problems. HEMO makes it possible to do reliable multi-objective search without risk of premature convergence. The paradigmatic transition of HEMO to handle premature convergence is that instead of trying to escape local optima from converged high fitness populations, it tries to maintain the opportunity for new optima to emerge from the bottom up as enabled by its hierarchical organization of individuals of different fitnesses.
4517069
A Fingerprint Orientation Model Based on 2D Fourier Expansion (FOMFE) and Its Application to Singular-Point Detection and Fingerprint Indexing
In this paper, we have proposed a fingerprint orientation model based on 2D Fourier expansions (FOMFE) in the phase plane. The FOMFE does not require prior knowledge of singular points (SPs). It is able to describe the overall ridge topology seamlessly, including the SP regions, even for noisy fingerprints. Our statistical experiments on a public database show that the proposed FOMFE can significantly improve the accuracy of fingerprint feature extraction and thus that of fingerprint matching. Moreover, the FOMFE has a low-computational cost and can work very efficiently on large fingerprint databases. The FOMFE provides a comprehensive description for orientation features, which has enabled its beneficial use in feature-related applications such as fingerprint indexing. Unlike most indexing schemes using raw orientation data, we exploit FOMFE model coefficients to generate the feature vector. Our indexing experiments show remarkable results using different fingerprint databases