The lattice cellular Potts model is widely used to represent physical and biological cellular systems. Standard implementations of this model in the literature employ inefficient Monte Carlo protocols to select elemen...
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The lattice cellular Potts model is widely used to represent physical and biological cellular systems. Standard implementations of this model in the literature employ inefficient Monte Carlo protocols to select elements (labels) of the lattice storing the investigated system. Recently, we proposed a new parallel algorithm, the Random Walker algorithm (RW), that can generate speedups from 3 to 10 times in simulations of this model. In this paper we present a distributed implementation of the RW algorithm exploiting parallel architectures. Our tests in a computer cluster show speedups between 5.7 and 15.6 in relation to the distributed standard algorithm.
In this paper, an efficient parallel algorithm to search large time series databases is proposed. There are existing parallel algorithms for performing such tasks, which generally utilize multidimensional tree structu...
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In this paper, an efficient parallel algorithm to search large time series databases is proposed. There are existing parallel algorithms for performing such tasks, which generally utilize multidimensional tree structures and thus are subjected to the performance of multidimensional trees. On the other hand, there have been a number of serial algorithms proposed in the past decade. Most of them use certain transformation techniques to reduce the dimensionality and then build an index to facilitate the search process. This again results in performance degradation. This work develops a parallel algorithm to process range query and k-nearest neighbor query in parallel time series databases, assuming a shared nothing multi-processor architecture. Both analytical and experimental results show that the new approach has near linear scaleup and linear speedup with little more effort than non-index based sequential scan and thus another alternative to index based approach
A parallel algorithm to detect retinal blood vessels has been developed for use in an automated diabetic retinopathy detection system. Localized adaptive thresholding and a multi-window Radon transform (RT) are utiliz...
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A parallel algorithm to detect retinal blood vessels has been developed for use in an automated diabetic retinopathy detection system. Localized adaptive thresholding and a multi-window Radon transform (RT) are utilized to detect the vascular system in retinal images. Multi-window parameter transforms are intrinsically parallel and offer increased performance over conventional transforms. The image is adoptively thresholded and then the multi-window RT is applied at different window sizes or partition levels. Results from each partition level are combined and morphologically processed to improve final performance. Multiple partitions are necessary to account for the size variation present in retinal blood vessels. The algorithm was tested with 20 images, 10 normal and 10 abnormal and the results demonstrate the robustness of the algorithm in the presence of noise. An average true positive rate of 86.3 % with a false positive rate of 3.9% is accomplished with this algorithm when tested against hand-labeled data
One of the most expensive part of a VQ compression algorithm is a codebook generation. PNN algorithm constructs a codebook by merging the "nearest" vectors and its parallel algorithm needs "Allsort"...
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One of the most expensive part of a VQ compression algorithm is a codebook generation. PNN algorithm constructs a codebook by merging the "nearest" vectors and its parallel algorithm needs "Allsort" procedure that sorts locally-sorted lists of all processors into a globally-sorted list and broadcasts the list to all processors on a multiprocessor system. We propose a new collective function, called Allsort for such a procedure and preliminarily implement the collective based on the dissemination method. We confirm the effectiveness of our proposed collective analytically and empirically. The results of our experiments show that the elapsed time of our implementation of the Allsort collective is improved by a factor of 2.0 to 2.7 compared with the combination of the ordinal MPI Allgather collective and the global sort on both power-of-2 number processors and non-power-of-2 number processors. We also show that the speedup of the aggressive PNN algorithm for a codebook generation for VQ compression is improved by around 8% to 20% on an 8 CPU cluster.
L-systems are powerful rule-based languages for modeling fractal objects and their animation in the fields of virtual plant. But the efficiency of this parallel algorithm needs to be improved because many times rewrit...
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L-systems are powerful rule-based languages for modeling fractal objects and their animation in the fields of virtual plant. But the efficiency of this parallel algorithm needs to be improved because many times rewriting will cost much time and waste lot of computer memory. In this article, an improved algorithm based on the idea of sub-structure is proposed to ameliorate L-systems. Those structures with same features that appear frequently during the process of production iteration are defined as different sub-structures. In the following repetitive process, when the same structure appears, the program will directly paste this sub-structure to the designated position instead of calculating again. Through this method, the storage size of the geometrical information can be decreased and the efficiency of modeling virtual plant can be improved.
Accurate models of parallel computation are often crucial to optimize parallel algorithms for their running time. In general the easier the model's use and the smaller the number of parameters and interdependencie...
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ISBN:
(纸本)9781424400546
Accurate models of parallel computation are often crucial to optimize parallel algorithms for their running time. In general the easier the model's use and the smaller the number of parameters and interdependencies among them, the more inaccuracies are introduced by simplification. On the other hand a too complex model is unusable. We show that it is possible to derive a relatively accurate and easy model for small message performance over the InfiniBand network. This model allows the developer to gain knowledge about the inherent parallelism of a specific InfiniBand hardware and encourages him to use this parallelism efficiently. Several well known models hide this feature and some of them even penalize the use of parallelism because the model designers were not aware of new emerging architectures like InfiniBand
Computing the 1-D fast Fourier transform (FFT) using the conventional six-step FFT on parallel computers requires intensive all-to-all communication due to the necessity of transposing an array three times. This all-t...
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Computing the 1-D fast Fourier transform (FFT) using the conventional six-step FFT on parallel computers requires intensive all-to-all communication due to the necessity of transposing an array three times. This all-to-all communication significantly reduces the performance of FFT in parallel systems. In this paper, we present a two-step parallel algorithm for implementing the 1-D FFT without inter-processor communication, at the expense of extra computation as opposed to the conventional six-step FFT. The advantage of the two-step FFT algorithm over its six-step counterpart becomes obvious in systems where the cost of computation is lower that of inter-processor communication. The 32-node Beowulf cluster is such a system with fast 2 GHz processors but relatively slow inter-processor communication by using 100 Mbit/s network switches. Our simulation results show that the two-step FFT algorithm without inter-processor communication outperforms the six-step 1-D FFT on this cluster
Many methods of generating behavior sequences of agents by evolution have been reported. A new evolutionary computation method named genetic network programming (GNP) has also been developed recently along with these ...
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Many methods of generating behavior sequences of agents by evolution have been reported. A new evolutionary computation method named genetic network programming (GNP) has also been developed recently along with these trends. In this paper, a new method for evolving GNP considering breadth and depth is proposed. The performance of the proposed method is shown from simulations using garbage collector problem
This paper traverses the relations between the amplitude-frequency response of FIR filters with the linear phase and the parallel algorithm of neural network, which its activation matrix is H d - C T W , presents and...
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This paper traverses the relations between the amplitude-frequency response of FIR filters with the linear phase and the parallel algorithm of neural network, which its activation matrix is H d - C T W , presents and proves the convergence theorem of the neural-network parallel algorithm, and gives the optimal design examples of high order FIR multi-band-stop digital filters. The results show that the parallel algorithm is efficient in the field of optimal design on the high order FIR multi-band-stop digital filters with the linear phase
This paper presents a novel generalized particle duality approach (GPDA) to transform the problem-solving for multi-agent systems into the kinematics and dynamics of particles in dual force-fields. Since the resources...
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This paper presents a novel generalized particle duality approach (GPDA) to transform the problem-solving for multi-agent systems into the kinematics and dynamics of particles in dual force-fields. Since the resources allocation and task assignment in complex distributed network environment is a typical problem of multi-agent systems, GPDA is used to optimize the bandwidth allocation and QoS assignment in ATM networks. The construction, dynamics and properties of the GPDA and corresponding algorithm are discussed. The GPDA has many advantages in terms of the high-scale parallelism, multi-objective optimization, multi-type coordination, multi-degree autonomy, and the ability to deal randomly occurring phenomena in MAS systems
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