The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Takahiro Hanyu - One of the best experts on this subject based on the ideXlab platform.
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high throughput low energy self timed cam based on reordered overlapped Search Mechanism
IEEE Transactions on Circuits and Systems, 2014Co-Authors: Naoya Onizawa, Shoun Matsunaga, Vincent Gaudet, Warren J Gross, Takahiro HanyuAbstract:This paper introduces a reordered overlapped Search Mechanism for high-throughput low-energy content-addressable memories (CAMs). Most mismatches can be found by Searching a few bits of a Search word. To lower power dissipation, a word circuit is often divided into two sections that are sequentially Searched or even pipelined. Because of this process, most of match lines in the second section are unused. Since Searching the last few bits is very fast compared to Searching the rest of the bits, we propose to increase throughput by asynchronously initiating second-stage Searches on the unused match lines as soon as a first-stage Search is complete. In our circuit implementation, each word circuit is independently controlled by a locally generated timing signal rather than a global signal. This allows the circuits to be in the required phase for their own local operation: evaluate or precharge, instead of having to synchronize their phase to the rest of the word circuits, which greatly reduces the cycle time. As a design example, a 128 × 64-bit CAM is implemented and evaluated by HSPICE simulation under a 90 nm CMOS technology. The proposed asynchronous CAM operates 5.98 times faster than a synchronous CAM with 14.2% smaller energy dissipation. The post-layout proposed CAM achieves 385-ps cycle delay time and 0.773 fJ/bit/Search and is also evaluated under different corner conditions and PVT variations to guarantee it operates properly.
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high throughput low energy content addressable memory based on self timed overlapped Search Mechanism
IEEE International Symposium on Asynchronous Circuits and Systems, 2012Co-Authors: Naoya Onizawa, Shoun Matsunaga, Vincent Gaudet, Takahiro HanyuAbstract:This paper introduces a self-timed overlapped Search Mechanism for high-throughput content-addressable memories (CAMs) with low Search energy. Most mismatches can be found by Searching the first few bits in a Search word. Consequently, if a word circuit is divided into two sections that are sequentially Searched, most match lines in the second section are unused. As Searching the first section is faster than Searching an entire word, we could potentially increase throughput by initiating a second-stage Search on the unused match lines as soon as a first-stage Search is complete. The overlapped Search Mechanism is realized using a self-timed word circuit that is independently controlled by a locally generated control signal, reducing the power dissipation of global clocking. A 256 x 144-bit CAM is designed under in 90 nm CMOS that operates with 5.57x faster throughput than a synchronous CAM, with 38% energy saving and 8% area overhead.
Chee Peng Lim - One of the best experts on this subject based on the ideXlab platform.
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an artificial bee colony algorithm with a modified choice function for the traveling salesman problem
Swarm and evolutionary computation, 2019Co-Authors: Shin Siang Choong, Lipei Wong, Chee Peng LimAbstract:Abstract The Artificial Bee Colony (ABC) algorithm is a swarm intelligence approach which has initially been proposed to solve optimisation of mathematical test functions with a unique neighbourhood Search Mechanism. This neighbourhood Search Mechanism could not be directly applied to combinatorial discrete optimisation problems. In order to tackle combinatorial discrete optimisation problems, the employed and onlooker bees need to be equipped with problem-specific perturbative heuristics. However, a large variety of problem-specific heuristics are available, and it is not an easy task to select an appropriate heuristic for a specific problem. In this paper, a hyper-heuristic method, namely a Modified Choice Function (MCF), is applied such that it can regulate the selection of the neighbourhood Search heuristics adopted by the employed and onlooker bees automatically. The Lin-Kernighan (LK) local Search strategy is integrated to improve the performance of the proposed model. To demonstrate the effectiveness of the proposed model, 64 Traveling Salesman Problem (TSP) instances available in TSPLIB are evaluated. On average, the proposed model solves the 64 instances to 0.055% from the known optimum within approximately 2.7 min. A performance comparison with other state-of-the-art algorithms further indicates the effectiveness of the proposed model.
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an artificial bee colony algorithm with a modified choice function for the traveling salesman problem
Systems Man and Cybernetics, 2017Co-Authors: Shin Siang Choong, Lipei Wong, Chee Peng LimAbstract:The Artificial Bee Colony (ABC) algorithm is a swarm intelligence approach which has initially been proposed to solve optimization of mathematical test functions with a unique neighbourhood Search Mechanism. However, this neighbourhood Search Mechanism could not be directly applied to combinatorial discrete optimization problems. The employed and onlooker bees need to be equipped with problem-specific perturbative heuristics in order to tackle combinatorial discrete optimization problems. However, there is a large variety of available problem-specific heuristics. In this paper, a hyper-heuristic method, namely a Modified Choice Function (MCF), is applied such that it can regulate the selection of the neighbourhood Search heuristics adopted by the employed and onlooker bees automatically. The proposed MCF-based ABC model is implemented using the Hyper-heuristic Flexible Framework (HyFlex). To demonstrate the effectiveness of the proposed model, ten Traveling Salesman Problem (TSP) instances available in HyFlex have been evaluated. The empirical results show that the proposed model is able to statistically outperform four out of five ABC variants throughout the optimization process.
Houbin Song - One of the best experts on this subject based on the ideXlab platform.
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a hybrid biogeography based optimization with variable neighborhood Search Mechanism for no wait flow shop scheduling problem
Expert Systems With Applications, 2019Co-Authors: Fuqing Zhao, Shuo Qin, Yi Zhang, Chuck Zhang, Houbin SongAbstract:Abstract The no-wait flow shop scheduling problem (NWFSP) plays an essential role in the manufacturing industry. Inspired by the overall process of biogeography theory, the standard biogeography-based optimization (BBO) was constructed with migration and mutation operators. In this paper, a hybrid biogeography-based optimization with variable neighborhood Search (HBV) is implemented for solving the NWFSP with the makespan criterion. The modified NEH and the nearest neighbor Mechanism are employed to generate a potential initial population. A hybrid migration operator, which combines the path relink technique and the block-based self-improvement strategy, is designed to accelerate the convergence speed of HBV. The iterated greedy (IG) algorithm is introduced into the mutation operator to obtain a promising solution in exploitation phase. A variable neighbor Search strategy, which is based on the block neighborhood structure and the insert neighborhood structure, is designed to perform the local Search around the current best solution in each generation. Furthermore, the global convergence performance of the HBV is analyzed with the Markov model. The computational results and comparisons with other state-of-art algorithms based on Taillard and VRF benchmark show that the efficiency and performance of HBV for solving NWFSP.
Kangping Wang - One of the best experts on this subject based on the ideXlab platform.
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hybrid ant colony algorithm for traveling salesman problem
Progress in Natural Science, 2003Co-Authors: Lan Huang, Chunguang Zhou, Kangping WangAbstract:Abstract A hybrid approach based on ant colony algorithm for the traveling salesman problem is proposed, which is an improved algorithm characterized by adding a local Search Mechanism, a cross-removing strategy and candidate lists. Experimental results show that it is competitive in terms of solution quality and computation time.
Naoya Onizawa - One of the best experts on this subject based on the ideXlab platform.
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high throughput low energy self timed cam based on reordered overlapped Search Mechanism
IEEE Transactions on Circuits and Systems, 2014Co-Authors: Naoya Onizawa, Shoun Matsunaga, Vincent Gaudet, Warren J Gross, Takahiro HanyuAbstract:This paper introduces a reordered overlapped Search Mechanism for high-throughput low-energy content-addressable memories (CAMs). Most mismatches can be found by Searching a few bits of a Search word. To lower power dissipation, a word circuit is often divided into two sections that are sequentially Searched or even pipelined. Because of this process, most of match lines in the second section are unused. Since Searching the last few bits is very fast compared to Searching the rest of the bits, we propose to increase throughput by asynchronously initiating second-stage Searches on the unused match lines as soon as a first-stage Search is complete. In our circuit implementation, each word circuit is independently controlled by a locally generated timing signal rather than a global signal. This allows the circuits to be in the required phase for their own local operation: evaluate or precharge, instead of having to synchronize their phase to the rest of the word circuits, which greatly reduces the cycle time. As a design example, a 128 × 64-bit CAM is implemented and evaluated by HSPICE simulation under a 90 nm CMOS technology. The proposed asynchronous CAM operates 5.98 times faster than a synchronous CAM with 14.2% smaller energy dissipation. The post-layout proposed CAM achieves 385-ps cycle delay time and 0.773 fJ/bit/Search and is also evaluated under different corner conditions and PVT variations to guarantee it operates properly.
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high throughput low energy content addressable memory based on self timed overlapped Search Mechanism
IEEE International Symposium on Asynchronous Circuits and Systems, 2012Co-Authors: Naoya Onizawa, Shoun Matsunaga, Vincent Gaudet, Takahiro HanyuAbstract:This paper introduces a self-timed overlapped Search Mechanism for high-throughput content-addressable memories (CAMs) with low Search energy. Most mismatches can be found by Searching the first few bits in a Search word. Consequently, if a word circuit is divided into two sections that are sequentially Searched, most match lines in the second section are unused. As Searching the first section is faster than Searching an entire word, we could potentially increase throughput by initiating a second-stage Search on the unused match lines as soon as a first-stage Search is complete. The overlapped Search Mechanism is realized using a self-timed word circuit that is independently controlled by a locally generated control signal, reducing the power dissipation of global clocking. A 256 x 144-bit CAM is designed under in 90 nm CMOS that operates with 5.57x faster throughput than a synchronous CAM, with 38% energy saving and 8% area overhead.
