This paper describes the design for testability （DFT） challenges and techniques of Godson-3 microprocessor, which is a scalable multicore processor based on the scalable mesh of crossbar （SMOC） on-chip network and...
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This paper describes the design for testability （DFT） challenges and techniques of Godson-3 microprocessor, which is a scalable multicore processor based on the scalable mesh of crossbar （SMOC） on-chip network and targets high-end applications. Advanced techniques are adopted to make the DFT design scalable and achieve low-power and low-cost test with limited IO resources. To achieve a scalable and flexible test access, a highly elaborate test access mechanism （TAM） is implemented to support multiple test instructions and test modes. Taking advantage of multiple identical cores embedding in the processor, scan partition and on-chip comparisons are employed to reduce test power and test time. Test compression technique is also utilized to decrease test time. To further reduce test power, clock controlling logics are designed with ability to turn off clocks of non-testing partitions. In addition, scan collars of CACHEs are designed to perform functional test with low-speed ATE for speed-binning purposes, which poses low complexity and has good correlation results.
In this work, for a wireless sensor network (WSN) of n randomly placed sensors with node density \lambda \in [1,n], we study the tradeoffs between the aggregation throughput and gathering efficiency. The gathering eff...
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In this work, for a wireless sensor network (WSN) of n randomly placed sensors with node density \lambda \in [1,n], we study the tradeoffs between the aggregation throughput and gathering efficiency. The gathering efficiency refers to the ratio of the number of the sensors whose data have been gathered to the total number of sensors. Specifically, we design two efficient aggregation schemes, called single-hop-length (SHL) scheme and multiple-hop-length (MHL) scheme. By novelly integrating these two schemes, we theoretically prove that our protocol achieves the optimal tradeoffs, and derive the optimal aggregation throughput depending on a given threshold value (lower bound) on gathering efficiency. Particularly, we show that under the MHL scheme, for a practically important set of symmetric functions called divisible perfectly compressible (DPC) functions, including the mean, max, and various kinds of indicator functions, etc., the data from \Theta (n) sensors can be aggregated to the sink at the throughput of a constant order \Theta (1), implying that, our MHL scheme is indeed scalable.
A terrain data organization method was proposed in this article in order to solve large scale data realtime rendering problem, which combines wavelet transform and quadtree to organize the terrain data, to further bui...
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Knowledge acquisition is one of the most important contributions of rough set theory for machine learning, pattern recognition and data mining. The generalization of decision rule of incomplete information system is a...
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Knowledge acquisition is one of the most important contributions of rough set theory to machine learning, pattern recognition and data mining. Although many researchers have achieved a lot, the ensemble classifier bas...
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Knowledge acquisition is one of the most important contributions of rough set theory to machine learning, pattern recognition and data mining. Although many researchers have achieved a lot, the ensemble classifier based on rough set theory is seldom studied. In order to improve the generalization of rough set theory, it is urgent to study the novel approaches for knowledge acquisition with high precision. Furthermore, different attribute reduction set can be obtained by rough set theory, which is useful to construct many classifiers. In this paper, the ensemble classifier is discussed based on rough set theory and attribute order. First of all, combining with the attribute order, a value reduction method is presented, by which a unique decision rule set under given attribute order can be got. Second, an ensemble classifier for knowledge acquisition is developed. In the proposed method, different decision rule sets of decision table can be obtained, by adjusting the attribute order of decision table. After that, an ensemble classifier has been developed by integrating the different rule sets. Experimental evaluations illustrate the high precision of the proposed approach.
Group communication is essential for multi-user applications. However, due to unpredictable node departures and non-deterministic network partitions, providing reliable and scalable group communication services is cha...
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Group communication is essential for multi-user applications. However, due to unpredictable node departures and non-deterministic network partitions, providing reliable and scalable group communication services is challenging when the applications are utilized by the users with heterogeneous capacities on a large scale. To address this challenge, we propose a novel replication scheme to achieve high reliability and low-cost scalability in group communication with following three features. First, it introduces a new concept of replication based on topological similarity, which empowers each node with an ability of measuring similarity between the nodes in topology. By eliminating the topological similarity between the replicas, it intelligently mitigates service interruptions caused by node failures and network partitions. Second, instead of specifying the number of replicas, it provides a technique for nodes to dynamically adapt the replication placement schemes by exploiting functionality importance of the nodes in the group- communication session. It eliminates the bottleneck problem and improves the network resource utilization. Third, the scheme is self-converging and it can stabilize within a few adaptations even facing a high churn rate. Extensive simulations show that it yields significant improvements in reduction of replication overhead and service interruption when comparing to existing approaches.
Advances in mobile networking and information processing technologies have triggered vehicular ad hoc networks (VANETs) for traffic safety and value-added applications. Most efforts have been made to address the secur...
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Software testing is the key validation technique used by industry up to today, but remain error prone and expensive cost. Automatically generating test cases from formal models of the system under test is a promising ...
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Software testing is the key validation technique used by industry up to today, but remain error prone and expensive cost. Automatically generating test cases from formal models of the system under test is a promising improvement approach to cut down the testing cost. This paper introduces a technique that automatically generate real-time conformance test cases from timed automata specifications. First, both reactive system and its environment is modeled by restricted automata with the notion of deterministic, input enabled and output urgent. Then demonstration is given to show how to efficiently generate real-time test cases with optimal execution time from diagnostic trace. Finally, we formally specify user's single purpose or coverage criteria to convert the test case generation problem into a reachability problem. This approach is implemented using model checkers as test case generation tools and experiment results on three different coverage criteria specifications show feasibility and effectiveness of our technique.
Dawning Nebulae is a heterogeneous system composed of 9280 multi-core x86 CPUs and 4640 NVIDIA Fermi GPUs. With a Linpack performance of 1.271 petaFLOPS, it was ranked the second in the TOP500 List released in June 20...
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Dawning Nebulae is a heterogeneous system composed of 9280 multi-core x86 CPUs and 4640 NVIDIA Fermi GPUs. With a Linpack performance of 1.271 petaFLOPS, it was ranked the second in the TOP500 List released in June 2010. In this paper, key issues in the system design of Dawning Nebulae are introduced. System tuning methodologies aiming at petaFLOPS Linpack result are presented, including algorithmic optimization and communication improvement. The design of its file I/O subsystem, including HVFS and the underlying DCFS3, is also described. Performance evaluations show that the Linpack efficiency of each node reaches 69.89%, and 1024-node aggregate read and write bandwidths exceed 100 GB/s and 70 GB/s respectively. The success of Dawning Nebulae has demonstrated the viability of CPU/GPU heterogeneous structure for future designs of supercomputers.
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