The model of autoencoder is one of the most typical deep learning models that have been mainly used in unsupervised feature learning for many applications like recognition, identification and mining. Autoencoder algor...
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Two-dimensional high-resolution inviscid and viscous detonations were conducted in the supersonic combustible mixture with the open-source program AMROC. The results show that as the grid resolution increases, more sm...
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It is widely believed that Shor＇s factoring algorithm provides a driving force to boost the quantum computing ***, a serious obstacle to its binary implementation is the large number of quantum gates. Non-binary quan...
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It is widely believed that Shor＇s factoring algorithm provides a driving force to boost the quantum computing ***, a serious obstacle to its binary implementation is the large number of quantum gates. Non-binary quantum computing is an efficient way to reduce the required number of elemental gates. Here, we propose optimization schemes for Shor＇s algorithm implementation and take a ternary version for factorizing 21 as an example. The optimized factorization is achieved by a two-qutrit quantum circuit, which consists of only two single qutrit gates and one ternary controlled-NOT gate. This two-qutrit quantum circuit is then encoded into the nine lower vibrational states of an ion trapped in a weakly anharmonic potential. Optimal control theory（OCT） is employed to derive the manipulation electric field for transferring the encoded states. The ternary Shor＇s algorithm can be implemented in one single step. Numerical simulation results show that the accuracy of the state transformations is about 0.9919.
Edge extraction is an indispensable task in digital image processing. With the sharp increase in the image data, real-time problem has become a limitation of the state of the art of edge extraction *** this paper, QSo...
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Edge extraction is an indispensable task in digital image processing. With the sharp increase in the image data, real-time problem has become a limitation of the state of the art of edge extraction *** this paper, QSobel, a novel quantum image edge extraction algorithm is designed based on the flexible representation of quantum image(FRQI) and the famous edge extraction algorithm Sobel. Because FRQI utilizes the superposition state of qubit sequence to store all the pixels of an image, QSobel can calculate the Sobel gradients of the image intensity of all the pixels simultaneously. It is the main reason that QSobel can extract edges quite fast. Through designing and analyzing the quantum circuit of QSobel, we demonstrate that QSobel can extract edges in the computational complexity of O(n2) for a FRQI quantum image with a size of2 n × 2n. Compared with all the classical edge extraction algorithms and the existing quantum edge extraction algorithms, QSobel can utilize quantum parallel computation to reach a significant and exponential ***, QSobel would resolve the real-time problem of image edge extraction.
A novel framework for parallel subgraph isomorphism on GPUs is proposed, named GPUSI, which consists of GPU region exploration and GPU subgraph matching. The GPUSI iteratively enumerates subgraph instances and solves ...
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A novel framework for parallel subgraph isomorphism on GPUs is proposed, named GPUSI, which consists of GPU region exploration and GPU subgraph matching. The GPUSI iteratively enumerates subgraph instances and solves the subgraph isomorphism in a divide-and-conquer fashion. The framework completely relies on the graph traversal, and avoids the explicit join operation. Moreover, in order to improve its performance, a task-queue based method and the virtual-CSR graph structure are used to balance the workload among warps, and warp-centric programming model is used to balance the workload among threads in a warp. The prototype of GPUSI is implemented, and comprehensive experiments of various graph isomorphism operations are carried on diverse large graphs. The experiments clearly demonstrate that GPUSI has good scalability and can achieve speed-up of 1.4–2.6 compared to the state-of-the-art solutions.
Interconnect network plays an important role in high performance computing systems. And its manageability directly affects the RAS (i.e., Reliability, Availability, and Serviceability) of the whole system. The Tianhe-...
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Interconnect network plays an important role in high performance computing systems. And its manageability directly affects the RAS (i.e., Reliability, Availability, and Serviceability) of the whole system. The Tianhe-2 system located in NSCC-gz (i.e., National Supercomputing Center of China in Guangzhou) uses proprietary interconnect network, which includes 5,856 high-radix network router chips (i.e., NRC) and 18,304 network interface chips (i.e., NIC). For such a very large-scale interconnect network, it is a great challenge to manage (such as configure, monitor, and debug) the numerous network chips and its network ports in an efficient way. By implementing the in-band management with very few hardware resources, the interconnect network in Tianhe-2 system achieves a highly efficient network management. In this paper, we introduce the design and implementation of the in-band management for interconnect network in Tianhe-2 system, especially emphasizing on several key features, including the set of achieved management functionalities, the architecture of network management, the format of management packets, the data flow and processing of management packets, etc. In this paper, we also evaluate the performance of in-band management by mainly comparing with out-band management scheme. The preliminary results demonstrate the efficiency of the in-band management for interconnect network in Tianhe-2 system.
Audio matching automatically retrieves all excerpts that have the same content as the query audio clip from given audio recordings. The extracted feature is critical for audio matching and the Chroma Energy Normalized...
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Audio matching automatically retrieves all excerpts that have the same content as the query audio clip from given audio recordings. The extracted feature is critical for audio matching and the Chroma Energy Normalized Statistics(CENS) feature is the state-of-the-arts. However, CENS might behave unsatisfactorily on some audio because it is a handcraft feature. In this paper, we propose to utilize the features learned by Convolutional Deep Belief Network(CDBN) to enhance the performance of audio matching. Benefit from the strong generalization ability of CDBN, our method works better than CENS based methods on most audio datasets. Since the features learned by CDBN are binary-valued, we can develop a more efficient audio matching algorithm by taking the advantage of this property. Experimental results on both TIMIT dataset and a simulated music dataset confirm effectiveness of the proposed CDBN based method comparing with the traditional CENS feature based algorithm.
The advancement in the process leads to more concern about the Single Event(SE) sensitivity of the Differential Cascade Voltage Switch Logic(DCVSL) circuits. The simulation results indicate that the Single Event Trans...
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The advancement in the process leads to more concern about the Single Event(SE) sensitivity of the Differential Cascade Voltage Switch Logic(DCVSL) circuits. The simulation results indicate that the Single Event Transient(SET) generated at the DCVSL gate is much larger than that at the ordinary CMOS gate, and their SET variation is different. Based on charge collection, in this paper, the effective collection time theory is proposed to set forth the SET pulse generated at the DCVSL gate. Through 3D TCAD mixed-mode simulation in 65 nm twin-well bulk CMOS process, the effects on SET variation of device parameters such as well contact size and environment parameters such as voltage are investigated.
The traditional identifier locator split network has many issues such as inflexibility, hard to innovate and difficult to deploy. SDN (Software Defined Network) provides a new direction for designing flexible identifi...
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ISBN:
(纸本)9781467386456
The traditional identifier locator split network has many issues such as inflexibility, hard to innovate and difficult to deploy. SDN (Software Defined Network) provides a new direction for designing flexible identifier locator split network. The recent identifier locator split network based on SDN use the OpenFlow switch directly via rewritting the address, which lacks the scalability and utilizes locator address ineffectively. An OpenFlow switch named IDOpenFlow is proposed to support the communication based on identifier. IDOpenFlow switch provides the communication mechanism via encapsulating the packets, which has good scalability and utilizing locator address effectively. IDOpenFlow switch encapsulates and decapsulates packets according flow entries which are installed by SDN controller. Moreover, the prototype system shows that IDOpenFlow effectively supports the communication for both the fixed node and the mobile node. With respect to the issues of software forwarding performance, a high-performance IDOpenFlow switch based on Intel DPDK (which is named A-IDOpenFlow) is proposed. The results of Ixia test tool show that: 1) for packets more than 128 bytes, A-IDOpenFlow switch supports the communication based on identifier at rate of 10Gbit/s; 2) for small packet of 64 bytes, the rate of A-IDOpenFlow is 7.25 times faster than the rate of IDOpenFlow.
Fault resilience has became a major issue for HPC systems, particularly, in the perspective of future E-scale systems, which will consist of millions of CPU cores and other components. MPI-level fault tolerant constru...
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