The k-Winners-Take-All (kWTA) is an operation to find the largest k (> 1) inputs among N inputs. parallel search algorithm of kWTA for digital inputs is not invented yet, so most of digital kWTA architectures have ...
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The k-Winners-Take-All (kWTA) is an operation to find the largest k (> 1) inputs among N inputs. parallel search algorithm of kWTA for digital inputs is not invented yet, so most of digital kWTA architectures have O(N) time complexity. A parallel search algorithm for digital kWTA operation and the circuits for its VLSI implementation are presented in this paper. The proposed kWTA architecture can compare all inputs simultaneously in parallel. The time complexity of the new architecture is O(logN), so that it is scalable to a large number of digital data. The high-speed kWTA operation and its O(logN) dependency of the new architecture are verified by simulations. It takes 290 ns in searching for 5 winners among 1024 of 32 bit data, which is more than thousands of times faster than existing digital kWTA circuits, as well as existing analog kWTA circuits.
Hadamard spectroscopy has earlier been used to speed-up multi-dimensional NMR experiments. In this work, we speed-up the two-dimensional quantum computing scheme, by using Hadamard spectroscopy in the indirect dimensi...
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Hadamard spectroscopy has earlier been used to speed-up multi-dimensional NMR experiments. In this work, we speed-up the two-dimensional quantum computing scheme, by using Hadamard spectroscopy in the indirect dimension, resulting in a scheme which is faster and requires the Fourier transformation only in the direct dimension. Two and three qubit quantum gates are implemented with an extra observer qubit. We also use one-dimensional Hadamard spectroscopy for binary information storage by spatial encoding and implementation of a parallel search algorithm. (c) 2006 Elsevier Inc. All rights reserved.
This paper introduces a parallelsearch system for dynamic multi-objective traveling salesman problem. We design a multi-objective TSP in a stochastic dynamic environment. This dynamic setting of the problem is very u...
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This paper introduces a parallelsearch system for dynamic multi-objective traveling salesman problem. We design a multi-objective TSP in a stochastic dynamic environment. This dynamic setting of the problem is very useful for routing in ad-hoc networks. The proposed search system first uses parallel processors to identify the extreme solutions of the search space for each ofk objectives individually at the same time. These solutions are merged into the so-called hit-frequency matrix E. The solutions in E are then searched by parallel processors and evaluated for dominance relationship. The search system is implemented in two different ways master-worker architecture and pipeline architecture.
This paper evaluates a distributed memory parallel search algorithm based on hierarchical pincers attack search (HPAS). HPAS is a parallel tree searchalgorithm with depth first search that uses a master processor and...
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ISBN:
(纸本)9781538691847
This paper evaluates a distributed memory parallel search algorithm based on hierarchical pincers attack search (HPAS). HPAS is a parallel tree searchalgorithm with depth first search that uses a master processor and some slave processors. This algorithm is efficient because it can implicitly share data frequently with all processors using shared memory. The communication overhead costs of HPAS on a distributed memory system will increase because of the need for frequent inter -processor communication. Thus, few studies have reported implementations of HPAS on a distributed memory system, and the effectiveness of this method is unclear. Therefore, this paper proposes an HPAS implementation method on a distributed memory system and evaluates its effectiveness. As a result of the evaluation, the maximum speedup ratio of the proposed method compared with the branch and hound method is approximately 52.78 times.
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