In this paper, we propose a framework to automatically map single-device OpenCL programs to heterogeneous multi-device platforms with performance concerns. Our framework is based on the independence of work groups whi...
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In this paper, we propose a framework to automatically map single-device OpenCL programs to heterogeneous multi-device platforms with performance concerns. Our framework is based on the independence of work groups which built inside the OpenCL programming model and relies heavily on the knowledge of global memory access regions of work groups. So global memory access patterns of work groups are analyzed and an abstract representation CCRwS is designed to describe the exact memory access regions of each memory access statement in the kernels. A global memory access analyzer is designed to get CCRwSs by performing static program analysis on kernel codes. Based on CCRwSs, data transfer between multiple devices and host can be fully controlled by our framework. Then a kernel code regenerator is designed to distribute the workload and perform architecture specific optimizations by code transformation. Then we tested our framework on a platform with 2 Intel E5-2650 CPUs and 4 NVIDIA Tesla C2050 GPUs. Compared with the performance on single GPU, the kernels running on all the 6 devices can achieve about 4.5x faster.
Spin-transfer torque random access memory (STT-RAM) is one of the most promising substitutes for universal main memory and cache due to its excellent scalability, high density and low leakage power. Nevertheless, the ...
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Network virtualization is recognized as an effective way to overcome the ossification of the Internet. However, the virtual network mapping problem (VNMP) is a critical challenge, focusing on how to map the virtual ne...
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Network virtualization is recognized as an effective way to overcome the ossification of the Internet. However, the virtual network mapping problem (VNMP) is a critical challenge, focusing on how to map the virtual networks to the substrate network with efficient utilization of infrastructure resources. The problem can be divided into two phases: node mapping phase and link mapping phase. In the node mapping phase, the existing algorithms usually map those virtual nodes with a complete greedy strategy, without considering the topology among these virtual nodes, resulting in too long substrate paths (with multiple hops). Addressing this problem, we propose a topology awareness mapping algorithm, which considers the topology among these virtual nodes. In the link mapping phase, the new algorithm adopts the k-shortest path algorithm. Simulation results show that the new algorithm greatly increases the long-term average revenue, the acceptance ratio, and the long-term revenue-to-cost ratio (R/C).
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...
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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...
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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.
Content-centric networks provide effective support for content services through a caching mechanism, so the caching of the placement strategy has become a hot research. In this paper, the problem of content placement ...
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Issue resolution is a central task for software development. The efficiency of issue fixing largely relies on the issue report quality. Stack Overflow, which hosts rich and real-Time posts about programming-specific p...
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The Hi-C data is the basis of three-dimensional chromosome structure reconstruction. In this paper, a method integrating U-Net and ResNET network is proposed to infer high resolution Hi-C data from existing low-resolu...
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There are two key issues for information diffusion in blogosphere: (1) blog posts are usually short, noisy and contain multiple themes, (2) information diffusion through blogosphere is primarily driven by the "wo...
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ISBN:
(纸本)9781577355120
There are two key issues for information diffusion in blogosphere: (1) blog posts are usually short, noisy and contain multiple themes, (2) information diffusion through blogosphere is primarily driven by the "word-of- mouth" effect, thus making topics evolve very fast. This paper presents a novel topic tracking approach to deal with these issues by modeling a topic as a semantic graph, in which the semantic relatedness between terms are learned from Wikipedia. For a given topic/post, the name entities, Wikipedia concepts, and the semantic relatedness are extracted to generate the graph model. Noises are filtered out through the graph clustering algorithm. To handle topic evolution, the topic model is enriched by using Wikipedia as background knowledge. Furthermore, graph edit distance is used to measure the similarity between a topic and its posts. The proposed method is tested by using the real-world blog data. Experimental results show the advantage of the proposed method on tracking the topic in short, noisy texts.
With the rapidly development of mobile cloud computing, in order to provide a better experience for mobile users, the computing and storage functions of mobile terminals are migrated to the cloud. In the application r...
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