11142145
An Optimal Design Method for De-synchronous Circuit Based on Control Graph
De-synchronous is a very useful method to design asynchronous circuit automatically from synchronous description of circuits. This paper introduces an optimal design method based on Control Graph which is an abstract model of the de-synchronous circuit. The main purpose of this optimal design method is to reduce the extra overhead in the area of the de-synchronous circuit. The optimization algorithm takes the performance evaluation function based on the Control Graph of the de-synchronous circuit as its heuristic function. The performance evaluation function presented in this paper is a linear programming problem. In the end of this paper, the optimal method is applied to a set of benchmark circuits. The number of the local controllers in these circuits is markedly reduced by 54%, and the number of C-elements that is required to construct the handshake circuitry between local controllers is also reduced by 76.3%. So the entire area of the circuit is sharply reduced. Because this design method is directed by the performance evaluation function of the circuit, there is no penalty in performance of the de-synchronous circuit.
32146489
Cycle Period Analysis and Optimization of Timed Circuits
In this paper, a method is proposed to analyze the minimum average cycle period of the timed circuits. Timed Petri net is used to model timed circuits. Our method is focus on structural analysis of the Petri net model of the timed circuits, which is another way to reduce the state space of the analyzed model. Then an algorithm is proposed to optimize the performance of timed circuit by asynchronous retiming technique. The algorithm balances the asynchronous pipelines to gain the target cycle period while minimize the area at the same time. Experimental results demonstrate the computational feasibility and effectiveness of both approaches.
22959134
The Design of Asynchronous Microprocessor Based on Optimized NCL_X Design-Flow
NCL X circuit is a very efficient way to implement the QDI circuit, which can get all the advantages of the asynchronous circuit, especially the average performance. But the NCL_X circuits suffer from its huge area overhead. To solve this problem, a method for optimizing the complete detection network in the NCL_X circuit has been introduced in this paper. Using this method can dramatically reduced the area of the NCL_X circuit, according to the experimental result, the area of the NCL_X circuit may be reduced more than 60%. We also use this optimized method to implement an asynchronous microprocessor pipeline (APC). Compared to the synchronous implementation, this NCL_X implementation can achieve higher performance because the NCL_X circuit can get the average performance.
7324862
A New Description Language for Data-Driven Asynchronous Circuits and its Design Flow
A lot of up-to-date asynchronous circuit design tools are based on the control-driven asynchronous circuit style, such as Balsa and Haste/Tangram. The control-driven approach will limit the performance of the result circuits. To improve the performance of the asynchronous circuits, a new description language - Biscotti, which is suitable for the data-driven asynchronous circuit design, has been introduced in this paper. And a data-driven asynchronous circuit design flow is also be presented here. The experimental results show that this design flow is a fast and efficient way to design the data-driven asynchronous circuit, which can achieve higher performance compared with the control-driven design approach.
17076624
Performance Bound Analysis and Retiming of Timed Circuits
Timed asynchronous circuits are efficient in performance and power consumption. Traditional performance analysis method can not analyze timed circuits efficiently. In this paper, we model timed circuits using timed Petri net and digraph. We studied the mean cycle time of timed Petri net model. The upper bound and lower bound of mean cycle time were given. Then we proposed an algorithm for timed circuits retiming. The algorithm can efficiently distribute buffers along communication channels of timed circuits to gain maximal performance and minimal area. These algorithms were applied to phased logic circuitspsila design and optimization.
8970759
Linux kernels as complex networks: A novel method to study evolution
In recent years, many graphs have turned out to be complex networks. This paper presents a novel method to study Linux kernel evolution — using complex networks to understand how Linux kernel modules evolve over time. After studying the node degree distribution and average path length of the call graphs corresponding to the kernel modules of 223 different versions (V1.1.0 to V2.4.35), we found that the call graphs of the file system and drivers module are scale-free small-world complex networks. In addition, both of the file system and drivers module exhibit very strong preferential attachment tendency. Finally, we proposed a generic method that could be used to find major structural changes that occur during the evolution of software systems.
26794680
Texture segmentation based on MRMRF modeling
Texture segmentation remains a fundamental issue in low-level image analysis, pattern recognition and computer vision. Texture segmentation problem can be solved in two directions: model fitting and non-parametric classification. In this paper, we propose to use multiresolution MRF (MRMRF) modeling in texture segmentation. A novel MRMRF parameter estimation method based on MCMC approach is presented. The experimental result shows that the method is suitable to segment textured images.
14334349
Learning Cascaded Reduced-Set SVMs Using Linear Programming
This paper proposes a simple and efficient detection framework that uses reduced-set kernels. We first describe our approach which reduces the number of kernels. A convex optimization method is used for calculating the reduced sets. Following this, we propose a method that optimally designs the cascade. Our experimental results indicate that our method minimizes complexity regarding the number of kernels in the cascaded structure while preserving the low error rates. Our algorithm generates the optimal weight of kernels for each cascade stage. This proposed algorithm achieves high detection-rates at low computational cost.
44863002
Comparative Study on Bionic Optimization Algorithms for Sewer Optimal Design
Sewer network as a necessary urban infrastructure plays an important role in people’s daily life. Conventional optimization techniques have significant limitations on solving the problems of sewer optimal design. Because as a high-dimensional discrete complex optimization problem, sewer optimal design is characterized by its discrete objective function and, as an integer discrete variable, its decision variable amount keeps the same pace with engineering scales. Over the last decade, various kinds of modern bionic optimization algorithms with their special advantages have been created and applied into sewer optimal design successfully. Based on previous studies, this paper analyses and compares the solution performances of Genetic Algorithms (GA), Particle Swarm Optimization (PSO) and Ant Colony Algorithms (ACA) from the three aspects respectively, they are convergence, speed and complexity of algorithm. The research result shows that compared with the other two algorithms, the ACA manifests its superiority for better convergence, satisfactory speed and relatively small algorithm complexity, which are very suitable for solving the problems of sewer optimal design.
16394212
A pharmacogenomic study on the polymorphic gene response to risperidone in schizophrenia patients
Risperidone is a widely used atypical antipsychotic medication, which has currently raised considerable interest in individual differences in patient response to it. Although risperidone is one of the major atypical anti-psychotics, there is a lack of pharmacogenetic studies on it, especially in Asian populations. This paper investigates the relationship between the -1438 A/G polymorphism of 5-HT2A and response to risperidone treatment. In this study, 130 schizophrenia patients were recruited, who were treated with risperidone monotherapy for eight weeks. Clinical response was assessed on the positive and negative syndrome scale (PANSS) on the day of admission and was subsequently assessed after eight weeks following the treatment. The -1438 A/G polymorphism was identified by direct sequencing. The confounding effects of nongenetic factors were estimated and the baseline symptom score was included as a covariate for adjustment. Association tests between genotype and percentage improvement in total PANSS scores, as well as positive symptom scores and negative symptom scores, were performed using analysis of variance (ANOVA). We find no significant differences in response to the treatment in terms of PANSS or subscore improvements among the subgroups according to different genotypes. Further studies on larger groups are planned to confirm the result.