6422073
Efficient Collective Communications in Dual-Cube
The hypercube, or n-cube, has been widely used as the interconnection network in parallel computers. However, the major drawback of the hypercube is the increase in the number of communication links for each node with the increase in the total number of nodes in the system. This paper introduces a new interconnection network, namely dual-cube, for large-scale parallel computers and describes the algorithms for efficient collective communications in dual-cube. The dual-cube network mitigates the problem of increasing number of links in the large-scale hypercube network while retains hypercube's topological properties. Design of efficient routing algorithms for collective communications is the key issue for any interconnection network. In this paper, we show that the collective communications can be done in dual-cube with almost the same communication times as in hypercube.
7971918
An Efficient Algorithm for Fault Tolerant Routing Based on Adaptive Binomial-Tree Technique in Hypercubes
We propose an efficient fault-tolerant routing algorithm for hypercube networks with a very large number of faulty nodes. The algorithm is distributed and local-information-based in the sense that each node in the network knows only its neighbors’ status and no global information of the network is required by the algorithm. For any two given nonfaulty nodes in a hypercube network that may contain a large fraction of faulty nodes, the algorithm can find a fault-free path of nearly optimal length with very high probability. The algorithm uses the adaptive binomial-tree to select a suitable dimension to route a node. We perform empirical analysis of our algorithm through simulations under a uniform node failure distribution and a clustered node failure distribution. The experimental results show that the algorithm successfully finds a fault-free path of nearly optimal length with the probability larger than 90 percent in a hypercube network that may contain up to 50 percent faulty nodes.
17836895
Binomial-Tree Fault Tolerant Routing in Dual-Cubes with Large Number of Faulty Nodes
A dual-cube DC(m) has m + 1 links per node where m is the degree of a cluster (m-cube), and one extra link is used for connection between clusters. The dual-cube mitigates the problem of increasing number of links in the large-scale hypercube network while keeps most of the topological properties of the hypercube network. In this paper, we propose efficient algorithms for finding a nonfaulty routing path between any two nonfaulty nodes in the dual-cube with a large number of faulty nodes. A node v ∈ DC(m) is called k-safe if v has at least k nonfaulty neighbors. The DC(m) is called k-safe if every node in DC(m) is k-safe. The first algorithm presented in this paper is an off-line algorithm that uses global information of faulty status. It finds a nonfaulty path of length at most d(s,t) + O(k2) in O(|F| + m) time for any two nonfaulty nodes s and t in the k-safe DC(m) with number of faulty nodes |F| < 2k(m + 1 – k), where 0≤ k ≤ m/2. The second algorithm is an online algorithm that uses local information only. It can find a fault-free path with high probability in an arbitrarily faulty dual-cube with unbounded number of faulty nodes.
18839021
Adaptive-Subcube Fault Tolerant Routing in Dual-Cube with Very Large Number of Faulty Nodes
The dual-cube is a newly proposed interconnection network for linking a large amount of nodes with low node degree. It uses low-dimensional hypercubes as building blocks and keeps the main desired properties of the hypercubes. In this paper, we give an efficient algorithm for fault tolerant routing in dual-cube networks with a large number of faulty nodes. Our algorithm uses the adaptive-subcube technique to select a suitable dimension to route a node. This technique not only increases the routing speed but also shortens the path and improves the successful routing rate. The experimental results show that, with high percentages of node failures, the algorithm can build routing paths with a very high probability. Our simulation results show that when a dual-cube with 32,768 nodes contains up to 20 percent faulty nodes, the success rate of constructing a faultfree path between any two nonfaulty nodes is 99.5 percent with a 4-subcube.
12535527
Fault-tolerant cycle embedding in hypercube with mixed link and node failures
1856152
Understanding the energy efficiency of simultaneous multithreading
Simultaneous multithreading (SMT) has proven to be an effective method of increasing the performance of microprocessors by extracting additional instruction-level parallelism from multiple threads. In current microprocessor designs, power-efficiency is of critical importance, and we present modeling extensions to an architectural simulator to allow us to study the power-performance efficiency of SMT. After a thorough design space exploration we find that SMT can provide a performance speedup of nearly 20% for a wide range of applications with a power overhead of roughly 24%. Thus, SMT can provide a substantial benefit for energy-efficiency metrics such as ED/sup 2/. We also explore the underlying reasons for the power uplift, analyze the impact of leakage-sensitive process technologies, and discuss our model validation strategy.
46557593
A New Stochastic PSO Technique for Neural Network Training
Recently, Particle Swarm Optimization(PSO) has been widely applied for training neural network. To improve the performance of PSO for high-dimensional solution space which always occurs in training NN, this paper introduces a new paradigm of particle swarm optimization named stochastic PSO (S-PSO). The feature of the S-PSO is its high ability for exploration. Consequently, when swarm size is relatively small, S-PSO performs much better than traditional PSO in training of NN. Hence if S-PSO is used to realize training of NN, computational cost of training can be reduced significantly.
6924123
Publicly verifiable ownership protection for relational databases
Today, watermarking techniques have been extended from the multimedia context to relational databases so as to protect the ownership of data even after the data are published or distributed. However, all existing watermarking schemes for relational databases are secret key based, thus require a secret key to be presented in proof of ownership. This means that the ownership can only be proven once to the public (e.g., to the court). After that, the secret key is known to the public and the embedded watermark can be easily destroyed by malicious users. Moreover, most of the existing techniques introduce distortions to the underlying data in the watermarking process, either by modifying least significant bits or exchanging categorical values. The distortions inevitably reduce the value of the data. In this paper, we propose a watermarking scheme by which the ownership of data can be publicly proven by anyone, as many times as necessary. The proposed scheme is distortion-free, thus suitable for watermarking any type of data without fear of error constraints. The proposed scheme is robust against typical database attacks including tuple/attribute insertion/deletion, random/selective value modification, data frame-up, and additive attacks.
29006676
A Remote Resource Monitoring Approach in Active Networks
Monitoring the resource status in active network nodes is important both for the network administrator to maintain and deploy active networks and for the normal end-users to acquire better performance. Hence, a method that can monitor the resource status at a remote node is needed. Moreover, due to the complexity of the resource usage in active networks, the corresponding method should be able to monitor the status of various resources at remote node dynamically and in a user-specified way. This paper presents the design and implementation of such a resource monitoring method. The method adopts the active application technique to obtain the desired resource status information at a remote network node and transfer them back to the user in the user-specified way. It also allows the user to control the content, the procedure and the precise of the monitoring.
121595784
Face recognition using shading-based curvature attributes
In this paper, we apply shape-from-shading to face images to extract fields of surface normals and make estimates of surface curvature attributes. The attributes studied include minimum and maximum curvature, mean and Gaussian curvature, and, curvedness and shape-index. The curvature attributes are encoded as histograms and are used to perform recognition using a number of distance and similarity measures including the Euclidean distance, the Shannon entropy, the Renyi entropy and the Tsallis entropy. We compare the results obtained using the different curvature attributes and the different entropy measures. Using precision-recall curves, we find that the best performance is delivered when the Shannon entropy is applied to histograms of shape index and curvedness.