Event-driven programming has been a relatively hot topic in distributed systems development. Having worked on these systems for years, we now believe that it is not the best choice. Besides the well-known "stack ...
详细信息
This paper presents an automatic deblurring approach for motion blur images. The approach explores the prior of the intensity and gradient to estimate the motion blur kernel from single blurred image. In this way, mot...
详细信息
ISBN:
(纸本)9781479972098
This paper presents an automatic deblurring approach for motion blur images. The approach explores the prior of the intensity and gradient to estimate the motion blur kernel from single blurred image. In this way, motion blur kernel could be well estimated not only on daytime images, but also on nighttime images. Efficient optimization method was given for the prior-based approach. Besides, a cost-effective method was also proposed to remove the noise of the kernel in the iterative kernel estimation. The proposed kernel enhancement approach could also improve the performance of other blind deblurring algorithm. Experimental results showed that the performance of the proposed algorithm was superior to many state-of-the-art blind deblurring algorithms, especially for nighttime images with saturated regions.
Static data-race detection is a powerful tool by providing clues for dynamic approaches to only instrument certain memory accesses. However, static data-race analysis suffers from high false positive rate. A key reaso...
详细信息
In order to improve the efficiency of the communication networks, we used the Kruskal algorithm and the Prim algorithm through algorithm comparison and analysis methods of data structure. A dynamic framework for the c...
详细信息
As an application of large scale distributed network computing system, RAM Grid tries to solve the problem of memory resource sharing and utilization. Due to the special properties of memory, traditional resource info...
详细信息
As an application of large scale distributed network computing system, RAM Grid tries to solve the problem of memory resource sharing and utilization. Due to the special properties of memory, traditional resource information management approaches cannot be adapted easily. This paper proposes a clustering based resource aggregating scheme under the background of RAM Grid, which can reduce the scale of resource information management efficiently. With analogy to the force field and potential energy theory in physics, the basic model, the force field-potential energy model, and the corresponding distributed algorithms are proposed, respectively. The model and algorithms are also evaluated by real network topologies based simulation.
We introduce a 64-bit ANSI/IEEE Std 754-1985 floating point design of a hardware matrix multiplier optimized for FPGA implementations. A general block matrix multiplication algorithm, applicable for an arbitrary matri...
详细信息
ISBN:
(纸本)9781595930293
We introduce a 64-bit ANSI/IEEE Std 754-1985 floating point design of a hardware matrix multiplier optimized for FPGA implementations. A general block matrix multiplication algorithm, applicable for an arbitrary matrix size is proposed. The algorithm potentially enables optimum performance by exploiting the data locality and reusability incurred by the general matrix multiplication scheme and considering the limitations of the I/O bandwidth and the local storage volume. We implement a scalable linear array of processing elements (PE) supporting the proposed algorithm in the Xilinx Virtex II Pro technology. Synthesis results confirm a superior performance-area ratio compared to related recent works. Assuming the same FPGA chip, the same amount of local memory, and the same I/O bandwidth, our design outperforms related proposals by at least 1.7X and up to 18X consuming the least reconfigurable resources. A total of 39 PEs can be integrated into the xc2vp125-7 FPGA, reaching performance of, e.g., 15.6 GFLOPS with 1600 KB local memory and 400 MB/s external memory bandwidth. Copyright 2005 ACM.
Scalability is a crucial factor determining the performance of massive heterogeneous parallel CFD applications on the multi-GPUs platforms, particularly after the single-GPU implementations have achieved optimal perfo...
详细信息
The Internet based cyber-physical world has profoundly changed the information environment for the development of artificial intelligence(AI), bringing a new wave of AI research and promoting it into the new era of AI...
详细信息
The Internet based cyber-physical world has profoundly changed the information environment for the development of artificial intelligence(AI), bringing a new wave of AI research and promoting it into the new era of AI 2.0. As one of the most prominent characteristics of research in AI 2.0 era, crowd intelligence has attracted much attention from both industry and research communities. Specifically, crowd intelligence provides a novel problem-solving paradigm through gathering the intelligence of crowds to address challenges. In particular, due to the rapid development of the sharing economy, crowd intelligence not only becomes a new approach to solving scientific challenges, but has also been integrated into all kinds of application scenarios in daily life, e.g., online-tooffline(O2O) application, real-time traffic monitoring, and logistics management. In this paper, we survey existing studies of crowd intelligence. First, we describe the concept of crowd intelligence, and explain its relationship to the existing related concepts, e.g., crowdsourcing and human computation. Then, we introduce four categories of representative crowd intelligence platforms. We summarize three core research problems and the state-of-the-art techniques of crowd intelligence. Finally, we discuss promising future research directions of crowd intelligence.
The paper presents an agent-oriented programming language SLABSp. It provides caste and scenario mechanisms in a coherent way to support the caste-centric methodology of agent-oriented software development. It uses ca...
详细信息
The paper presents an agent-oriented programming language SLABSp. It provides caste and scenario mechanisms in a coherent way to support the caste-centric methodology of agent-oriented software development. It uses caste as a modular facility to organize agents into castes and to represent their structure and behavior characteristics. SLABSp also uses scenarios to define agents' behaviors in the context of environment situations. In the paper, the implementation of the language is briefly described. An example of the program is given to illustrate its programming style. Copyright 2005 ACM.
Proximity ranking according to end-to-end network distances (e.g., Round-Trip Time, RTT) can reveal detailed proximity information, which is important in network management and performance diagnosis in distributed sys...
详细信息
Proximity ranking according to end-to-end network distances (e.g., Round-Trip Time, RTT) can reveal detailed proximity information, which is important in network management and performance diagnosis in distributed systems. However, to the best of our knowledge, there has been no similar work on this subject in the P2P computing field. We present a distributed rating method iRank, that enables proximity rankings by providing discrete ratings in a distributed manner. It formulates the proximity ranking as a rating problem that faithfully captures the proximity based on noisy distance measurements scalably and practically. The primary challenge in inferring proximity rankings is enforcing distributed ratings with complex rating policies. Our solution is based on reconstructing ratings by decomposing a centralized rating method Maximum Margin Matrix Factorization (MMMF) into independent sub-problems, that can be efficiently solved in a decentralized manner. By relaxing the dependence on infrastructure nodes that are a single point of failure and limit scalability, iRank can gracefully handle network churns. Through real network latency data sets, we demonstrate that iRank can predict ratings with low distortion, which are smaller than 20 percentage worse than the centralized method, in the context of synthetic complex rating policies.
暂无评论