One of the gene expression data analysis tasks is the Gene regulatory network analysis. Gene regulatory network is concerned in the topological organization of genes interactions. Moreover, the regulatory network is i...
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ISBN:
(纸本)9783319746906;9783319746890
One of the gene expression data analysis tasks is the Gene regulatory network analysis. Gene regulatory network is concerned in the topological organization of genes interactions. Moreover, the regulatory network is important for understanding the normal cell physiology and pathological phenotypes. However, the main challenge facing gene regulatory network algorithms is the data size. Where, the algorithm runtime is proportional to the data size. This paper presents a parallel algorithm for gene regulatory network (PFastNCA) which is an improved version of FastNCA. PFastNCA enhanced the main core of FastNCA which is the connectivity matrix estimation using a distributed computing model. Where, the work is divided among N processing nodes, PFastNCA is more efficient than FastNCA. It also achieved a better performance and speedup reached 1.91.
Metadata in a paralleldistributed database contains information about table fragmentation, physical storage distribution, and access control policies. It is essential to query processing and security policy enforceme...
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State management in stream and event processingapplications is a long-standing problem. There is a conflict between individual stream processing (SP) operators as transformational units, whose purpose is to generate ...
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Advanced silicon and plasmonic nanophotonics is undergoing rapid progress due to its manifold applications in high data communication links and other applications in imaging and sensing. Our group has been at the fore...
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ISBN:
(纸本)9781450340618
Advanced silicon and plasmonic nanophotonics is undergoing rapid progress due to its manifold applications in high data communication links and other applications in imaging and sensing. Our group has been at the forefront of new devices and device physics. In this talk we will first review progress in our group in a wide variety of fundamental technologies and physics needed to extend the advances in nanophotonics. We will then illustrate these ideas with several new devices types that we have recently demonstrated at Columbia based on new simulation modalities. Our approach then to modeling and simulation is to use fully accurate methods and techniques and to achieve new capabilities based on massively parallel and high-performance computation. Much of our advances are based on new hardware strengths and testing with distributed and parallel systems.
Reference architectures predefine a common frame of reference, which can be customised to obtain architectures for specific applications in a domain. Based on a general reference model, providing a common language and...
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distributed Denial-of-Service (DDoS) attacks misuse network resource and bring serious threats to the internet. Detecting DDoS at the source-end has many advantages over defense at the victim-end and intermediate-netw...
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ISBN:
(纸本)3540297693
distributed Denial-of-Service (DDoS) attacks misuse network resource and bring serious threats to the internet. Detecting DDoS at the source-end has many advantages over defense at the victim-end and intermediate-network. However, one of the main problems for source-end methods is the performance degradation brought by these methods and no direct benefit for Internet Service Provider(ISP), which discourages ISPs to deploy the defense system. We propose an efficient detection approach, which only requires limited fixed-length memory and low computation overhead but provides satisfying detection results. Our method is also beneficial because the method can not only detect direct DDoS attack for other ISPs, but also protect the ISP itself from reflector DDoS attack. The efficient and beneficial defense is practical and expected to attract more ISPs to join the cooperation. The experiments results show our approach is efficient and feasible for defense at the source-end.
Discrete Fourier Transform(DFT) is one of the frequently used kernels in a variety of signal processingapplications. Most previous state-of-the-art work has focused on the transform size of a power of 2. And many imp...
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ISBN:
(纸本)9781467392068
Discrete Fourier Transform(DFT) is one of the frequently used kernels in a variety of signal processingapplications. Most previous state-of-the-art work has focused on the transform size of a power of 2. And many implementations of non-power-of-two sized DFT is customized for a specific application. In this paper, a parallel-processing architecture based on Field-Programmable Gate Array (FPGA) for arbitrary-sized DFT is proposed. In particular, it is attractive to use to compute DFT with arbitrary prime size. A memory efficient data mapping scheme for twiddle factors is proposed, which reduces the storage size of twiddle factors from n(2) to kn(k is a constant). We implement a design with 196 processing elements, which is available for any transform size n from 14 to 1024. For a transform size of 59, the throughput in this design can reach to 737.5 Msps. The design can be easily extended to be one with more processing elements if the hardware has enough resources. And we have built a code generator to automatically generate designs with different numbers of processing elements.
Social influence plays an essential role in spreading information within online social networks, and can be modeled or measured by analyzing various social networking data, such as published content, users' attrib...
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ISBN:
(纸本)9781538643013
Social influence plays an essential role in spreading information within online social networks, and can be modeled or measured by analyzing various social networking data, such as published content, users' attributes or interactions among them. Because of the massive social data, researchers often fail to quantify user influence in an accurate and high efficient way. Big data technique can be adopted to alleviate this problem. In this paper, we introduce a kind of classical individual influence algorithm, and implement two parallel versions of this algorithm based on different big data processing framework Experiment results on a large-scale real dataset demonstrate that the computational efficiency of influence algorithm can be improved significantly in massive data sets by virtue of big data processing framework
parallelization of sequential programs for distributed memory machines generally involves non-local modifications to the program code and automatic parallelization tools are still not available. Thus, for large applic...
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This paper describes a novel approach to dynamic distributedparallelprocessing using a mobile agent-based infrastructure. Our goal is to extend the concept of the parallel Virtual Machine architecture by using a com...
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This paper describes a novel approach to dynamic distributedparallelprocessing using a mobile agent-based infrastructure. Our goal is to extend the concept of the parallel Virtual Machine architecture by using a combination of collaborative and mobile software agents to enable automatic and dynamic configuration of distributed processes. Our approach to distributedprocessing is regulated by a two-tier management system. At the strategic level, an anchored centralized agent is responsible for managing user interaction and determining how tasks are to be distributed. Whilst the mobile agents who deliver code to remote machines, manage local processing at an operational level. We therefore developed specialized mobile agents, each performing particular roles, which co-operate as a team to achieve user defined goals. The resulting system provides users with a much simpler means of utilizing the power of distributedparallel computing.
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