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Zhan C.,University of Science and Technology of China | Zhan C.,Key Laboratory on High Performance Computing | Xu Y.,University of Science and Technology of China | Xu Y.,Key Laboratory on High Performance Computing
2010 IEEE International Symposium on Network Coding, NetCod 2010 | Year: 2010

Using network coding in wireless networks can increase throughput and reduce energy consumption. Recently there are many works focusing on how to utilize network coding to increase throughput, however there are few works considering the quality of service such as delay which is important to time critical applications. This paper focuses on network coding based broadcast scheduling problem in time critical wireless networks with packet delay constraint and aims at minimizing the number of packets which miss their deadlines. Using a weighted graph model, we formulate the problem with an integer linear programming and prove that it is NP-hard. By assigning vertex weight as a decreasing function of packet deadline, we propose a packet encoding and broadcasting algorithm based on the maximum weight clique in the graph. Detailed analysis shows that some typical application requirements can be realized with different weight functions, which can be useful for Qos design. Simulation results show that our algorithm significantly reduce the deadline miss ratio in most cases, which is an important performance metric in time critical applications. © 2010 IEEE. Source

Xu Y.,Anhui University of Science and Technology | Xu Y.,Key Laboratory on High Performance Computing | Yang J.,Anhui University of Science and Technology | Yang J.,Key Laboratory on High Performance Computing | And 3 more authors.
Information Sciences | Year: 2013

The planted motif search problem is a classical problem in bioinformatics that seeks to identify meaningful patterns in biological sequences. As an NP-complete problem, current algorithms focus on improving the average time complexity and solving challenging instances within an acceptable time. In this paper, we propose a new exact algorithm CVoting that improves the state-of-the-art Voting algorithm. CVoting uses a new hash technique to reduce the space complexity to O(mn + N(l, d)) and a new pruning technique to reduce the average time complexity to Om2nN(l,d)14+3ll. Experimental results show that CVoting outperforms competing algorithms, including PMS1, RISOTTO, Voting and Pmsprune, in both space and time: up to an order of magnitude faster and using less memory in solving challenging instances. The software of the proposed algorithm is publicly available at http://staff.ustc.edu.cn/xuyun/motif. © 2013 Elsevier Inc. All rights reserved. Source

Yang J.,Key Laboratory on High Performance Computing | Yang J.,University of Science and Technology of China | Xu Y.,Key Laboratory on High Performance Computing | Xu Y.,University of Science and Technology of China | And 3 more authors.
WCE 2010 - World Congress on Engineering 2010 | Year: 2010

Sequence alignment is an important problem in computational biology and finding the longest common subsequence (LCS) of multiple biological sequences is an essential and effective technique in sequence alignment. A major computational approach for solving the LCS problem is dynamic programming. Several dynamic programming methods have been proposed to have reduced time and space complexity. As databases of biological sequences become larger, parallel algorithms become increasingly important to tackle large size problems. In the meantime, general-purpose computing on graphics processing units (GPGPU) has emerged as a promising technology for cost-effective high performance computing. In this paper, we develop an efficient parallel algorithm on GPUs for the LCS problem. We propose a new technique that changes the data dependency in the score table used by dynamic programming algorithms to enable higher degrees of parallelism. The algorithm takes advantage of the large number of processing units and the unique memory-accessing properties of GPUs to achieve high performance. The algorithm was implemented on Nvidia 9800GT GPUs and tested on randomly generated sequences of different lengths. The experiment results show that the new algorithm is about 6 times faster on GPUs than on typical CPUs and is 3 times faster than an existing efficient parallel algorithm, the diagonal parallel algorithm. Source

Cheng H.,Key Laboratory on High Performance Computing | Cheng H.,Anhui University of Science and Technology | Jiang H.,Key Laboratory on High Performance Computing | Jiang H.,Anhui University of Science and Technology | And 4 more authors.
BMC Bioinformatics | Year: 2015

Background: As the next-generation sequencing (NGS) technologies producing hundreds of millions of reads every day, a tremendous computational challenge is to map NGS reads to a given reference genome efficiently. However, existing methods of all-mappers, which aim at finding all mapping locations of each read, are very time consuming. The majority of existing all-mappers consist of 2 main parts, filtration and verification. This work significantly reduces verification time, which is the dominant part of the running time. Results: An efficient all-mapper, BitMapper, is developed based on a new vectorized bit-vector algorithm, which simultaneously calculates the edit distance of one read to multiple locations in a given reference genome. Experimental results on both simulated and real data sets show that BitMapper is from several times to an order of magnitude faster than the current state-of-the-art all-mappers, while achieving higher sensitivity, i.e., better quality solutions. Conclusions: We present BitMapper, which is designed to return all mapping locations of raw reads containing indels as well as mismatches. BitMapper is implemented in C under a GPL license. Binaries are freely available at http://home.ustc.edu.cn/%7Echhy. © 2015 Cheng et al. Source

Lin X.,University of Science and Technology of China | Lin X.,Key Laboratory on High Performance Computing | Xu Y.,University of Science and Technology of China | Xu Y.,Key Laboratory on High Performance Computing | And 4 more authors.
Journal of Information and Computational Science | Year: 2011

Recent works show that the integration of layered media multicast with network coding can significantly improve the throughput of media distribution over the networks where there are a large number of receivers with heterogeneous reception capacities. However, because of stringent bandwidth and delay requirements arising in the applications of media delivery over bandwidth limited networks, it is very important to support guaranteed bandwidth and delay requirements for the receivers. Different from all the related works on increasing the throughput, this paper firstly studies the problem of minimizing the transmission delay in layered multicast using network coding while supporting the guaranteed bandwidth requirements of the receivers. In this paper, we firstly give the mathematical formulation for the problem, and then because the problem is NP-hard, we give an effective heuristic approach, which achieves low transmission delay with high bandwidth, to solve it. The simulation results demonstrate that our heuristic approach can greatly reduce the transmission delay while supporting high bandwidth requirements in layered multicast with network coding. © 2011 Binary Information Press. Source

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