17545097
Design of Rotary Clock Based Circuits
Rotary clock technique has been shown to reduce the power dissipation of clock distribution by up to 80%. However, to our knowledge, no practical digital synchronous circuit has been designed that utilizes the rotary technique due to the multi-phase nature of rotary clock signals and the strong coupling between a rotary clock network and the circuit it drives. In this paper, we make the first attempt to design rotary based circuit by proposing a unified clock and circuit design methodology. Given a sequential circuit and a clock frequency, our scheme derives a rotary clock network and a functionally equivalent circuit so that they can be integrated to operate reliably at the target frequency. We have applied our scheme to design several rotary clock based DSP modules. Simulation results show that all designs operate correctly with no timing violation. Compared with designs using conventional clock trees, our designs achieve an average clock power saving of more than 70%.
17082553
HyPE: hybrid power estimation for IP-based systems-on-chip
In this paper, we present a novel power estimation scheme for programmable systems consisting of predesigned datapath and memory components. The proposed hybrid methodology yields highly accurate estimates within short runtimes by combining high-level simulation with analytical macromodeling of circuit characteristics. The kernel of our methodology is a simulation-free power estimation scheme for memoryless datapaths comprising several IP blocks connected in fixed topologies. The outer shell of our hybrid scheme is a functional simulation, which is performed only on the interfaces between memoryless components and memory blocks. This simulation accurately captures the control signals that affect the flow of data and, consequently, the utilization and power dissipation of hardware. Experimental results validate the accuracy and efficiency of our methodology. We applied our static power estimation kernel to signal processing and data encryption datapaths. For designs of up to 576 IP blocks, the average error of our power estimates is 7.3% in comparison with switch-level simulation results. We implemented our hybrid scheme into a power estimation tool, called HYPE, and used it to explore various architectural alternatives in the design of a 256-state Viterbi decoder and a Rijndael encryptor. For designs with about 1 million transistors, our estimator terminates within seconds. Compared with commercial state-of-the-art gate-level power estimators, our proposed methodology is up to 1000 times faster with 5.4% deviation on average.
10662727
Power macromodeling of global interconnects considering practical repeater insertion
In this paper, we present a simple yet highly effective power macromodeling technique for global interconnects that considers optimal repeater insertion. Specifically,our model estimates the interconnect power dissipation from the interconnect length, the timing budget, the repeater location flexibility, and the signal activity using an analytical function that is derived for a given repeater library and fabrication technology. In experiments with different standard cell libraries, the average error of our technique is less than 2%.
26613748
A Markov chain sequence generator for power macromodeling
In this paper, we present a novel sequence generator based on a Markov chain model. Specifically, we formulate the problem of generating a sequence of vectors with given average input probability p, average transition density d, and spatial correlation s as a transition matrix computation problem, in which the matrix elements are subject to constraints derived from the specified statistics. We also give a practical heuristic that computes such a matrix and generates a sequence of l n-bit vectors in O(nl + n/sup 2/) time. Derived from a strongly mixing Markov chain, our generator yields binary vector sequences with accurate statistics, high uniformity, and high randomness. Experimental results show that our sequence generator can cover more than 99% of the parameter space. Sequences of 2,000 48-bit vectors are generated in less than 0.05 seconds, with average deviations of the signal statistics p, d, and s equal to 1.6%, 1.8%, and 2.8%, respectively. Our generator enables the detailed study of power macromodeling. Using our tool and the ISCAS-85 benchmark circuits, we have assessed the sensitivity of power dissipation to the three input statistics p, d, and s. Our investigation reveals that power is most sensitive to transition density, while only occasionally exhibiting high sensitivity to signal probability and spatial correlation. Our experiments also show that input signal imbalance can cause estimation errors as high as 100% in extreme cases, although errors are usually within 25%.
13241066
Retiming and clock scheduling for digital circuit optimization
This paper investigates the application of simultaneous retiming and clock scheduling for optimizing synchronous circuits under setup and hold constraints. Two optimization problems are explored: (1) clock period minimization and (2) tolerance maximization to clock-signal delay variations. Exact mixed-integer linear programming formulations and efficient heuristics are given for both problems. When both long and short paths are considered, circuits optimized by the combined application of retiming and clock scheduling can achieve shorter clock periods or demonstrate greater tolerance to clock-signal delay variations than circuits optimized by retiming or clock scheduling. Experiments with benchmark circuits demonstrate the effectiveness of the combined optimization. In comparison with the best result obtained by either of the two optimizations, the joint application of retiming and clock scheduling increased operating speeds by more than 8% on the average. It also increased tolerance to clock delay variations by an average of 12% over a broad range of target clock frequencies. Larger relative improvements were achieved for shorter clock periods, thus suggesting that simultaneous retiming and clock scheduling can play an important role in high-speed design.
3103928
Maximizing performance by retiming and clock skew scheduling
The application of retiming and clock skew scheduling for improving the operating speed of synchronous circuits under setup and hold constraints is investigated in this paper. It is shown that when both long and short paths are considered, circuits optimized by the simultaneous application of retiming and clock scheduling can achieve shorter clock periods than optimized circuits generated by applying either of the two techniques separately. A mixed-integer linear programming formulation and an efficient heuristic are given for the problem of simultaneous retiming and clock skew scheduling under setup and hold constraints. Experiments with benchmark circuits demonstrate the efficiency of this heuristic and the effectiveness of the combined optimization. All of the test circuits show improvement. For more than half of them, the maximum operating speed increases by more than 21% over the optimized circuits obtained by applying retiming or clock skew scheduling separately.
1211146
Multi-hop probing asymptotics in available bandwidth estimation: stochastic analysis
This paper analyzes the asymptotic behavior of packet-train probing over a multi-hop network path P carrying arbitrarily routed bursty cross-traffic flows. We examine the statistical mean of the packet-train output dispersions and its relationship to the input dispersion. We call this relationship the response curve of path P. We show that the real response curve Z is tightly lower-bounded by its multi-hop fluid counterpart F, obtained when every cross-traffic flow on P is hypothetically replaced with a constant-rate fluid flow of the same average intensity and routing pattern. The real curve Z asymptotically approaches its fluid counterpart F as probing packet size or packet train length increases. Most existing measurement techniques are based upon the single-hop fluid curve S associated with the bottleneck link in P. We note that the curve S coincides with F in a certain large-dispersion input range, but falls below F in the remaining small-dispersion input ranges. As an implication of these findings, we show that bursty cross-traffic in multi-hop paths causes negative bias (asymptotic underestimation) to most existing techniques. This bias can be mitigated by reducing the deviation of Z from S using large packet size or long packet-trains. However, the bias is not completely removable for the techniques that use the portion of S that falls below F.
18685518
A novel 2-DOF parallel mechanism based design of a new 5-axis hybrid machine tool
In this paper, the concept of a new 5-axis hybrid machine tool is proposed. The machine is a tool being with both parallel and serial structures, which is based on a novel 2-DOF parallel platform and serial orientations. The machine tool has advantages in terms of high stiffness, high dexterity, high speed, and being capable of long components manufacturing. The kinematics characteristics, such as inverse and forward kinematics, conditioning indices, of the novel 2-DOF parallel platform are studied. The dimensional synthesis based on the workspace and conditioning indices is presented. The results of the paper are very useful for the design of the hybrid machine tool.
7555324
BioProspector: Discovering Conserved DNA Motifs in Upstream Regulatory Regions of Co-Expressed Genes
The development of genome sequencing and DNA microarray analysis of gene expression gives rise to the demand for data-mining tools. BioProspector, a C program using a Gibbs sampling strategy, examines the upstream region of genes in the same gene expression pattern group and looks for regulatory sequence motifs. BioProspector uses zero to third-order Markov background models whose parameters are either given by the user or estimated from a specified sequence file. The significance of each motif found is judged based on a motif score distribution estimated by a Monte Carlo method. In addition, BioProspector modifies the motif model used in the earlier Gibbs samplers to allow for the modeling of gapped motifs and motifs with palindromic patterns. All these modifications greatly improve the performance of the program. Although testing and development are still in progress, the program has shown preliminary success in finding the binding motifs for Saccharomyces cerevisiae RAP1, Bacillus subtilis RNA polymerase, and Escherichia coli CRP. We are currently working on combining BioProspector with a clustering program to explore gene expression networks and regulatory mechanisms.
9910585
Video based human animation technique
Human animation is a challenging domain in computer animation. To aim at many shortcomings in conventional techniques, this paper proposes a new video based human animation technique. Given a clip of video, firstly human joints are tracked with the support of Kalman filter and morph-block based match in the image sequence. Then corresponding sequence of three-dimension (3D) human motion skeleton is constructed under the perspective projection using camera calibration and human anatomy knowledge. Finally a motion library is established automatically by annotating multiform motion attributes, which can be browsed and queried by the animator. This approach has the characteristic of rich source material, low computing cost, efficient production, and realistic animation result. We demonstrate it on several video clips of people doing full body movements, and visualize the results by re-animating a 3D human skeleton model.
40113853
A Framework for Modelling Short, High-Dimensional Multivariate Time Series: Preliminary Results in Virus Gene Expression Data Analysis
Short, high-dimensional Multivariate Time Series (MTS) data are common in many fields such as medicine, finance and science, and any advance in modelling this kind of data would be beneficial. Nowhere is this more true than functional genomics where effective ways of analysing gene expression data are urgently needed. Progress in this area could help obtain a "global" view of biological processes, and ultimately lead to a great improvement in the quality of human life. We present a computational framework for modelling this type of data, and report preliminary experimental results of applying this framework to the analysis of gene expression data in the virology domain. The framework contains a threestep modelling strategy: correlation search, variable grouping, and short MTS modelling. Novel research is involved in each step which has been individually tested on different real-world datasets in engineering and medicine. This is the first attempt to integrate all these components into a coherent computational framework, and test the framework on a very challenging application area, which has produced promising results.