一种连续变焦距电视的变倍补偿机构设计

为了实现电视的焦距连续变化,设计了一种连续变焦距电视的变倍补偿机构。提出了一种提高变倍、补偿机构运动精度的方法,实测两机构直线运动精度均为15″。通过靶场试验证明连续变焦距电视的变倍补偿机构的运动精度满足电视捕获、跟踪目标的精度要求,两直线滑轨平行度调整机构设计、加工简单,可以在其它直线运动机构中得到推广应用。     

Sorting-Based Calculation of Zeroes and Extrema of Functions as Applied to Search and Recognition. I

A stable address sorting is used for approximate calculation of zeroes and extrema of functions of one variable and two variables. In particular, the paper gives a new method for localization and approximate calculation of all the roots of a polynomial with arbitrary power. The method includes poorly separated roots, and its distinctive features are the computational stability and the maximum parallelism.     

Accelerating sequential programs on commodity multi-core processors

A recently proposed pipelined multithreading (PMT) technique exhibits wide applicability in parallelizing general sequential programs on multi-core processors. However, significant inter-core communication overhead limits PMT performance and prevents its commercial utilization. A simple and effective clustered pipelined multithreading (CPMT) approach is presented to accelerate sequential programs on commodity multi-core processors. This CPMT technique adopts a clustered communication mechanism that can yield very low average communication overhead by eliminating false sharing as well as reducing communication operation and transit delays in the software-only approach. A single-producer/single-consumer concurrent lock-free clusteredQueue algorithm based on a two-level queue structure is also proposed. The accuracy of CPMT is theoretically demonstrated. The performances of the algorithm and CPMT are evaluated on a commodity AMD Phenom four-core processor. The number of enqueue and dequeue times of the algorithm are 20.8 and 23 cycles given an appropriate parameter, respectively. The speedup of CPMT ranges from 13.1% to 119.8% for typical loops extracted from the SPEC CPU 2000 benchmark suite.     

Kokkos: Enabling manycore performance portability through polymorphic memory access patterns

The manycore revolution can be characterized by increasing thread counts, decreasing memory per thread, and diversity of continually evolving manycore architectures. High performance computing (HPC) applications and libraries must exploit increasingly finer levels of parallelism within their codes to sustain scalability on these devices. A major obstacle to performance portability is the diverse and conflicting set of constraints on memory access patterns across devices. Contemporary portable programming models address manycore parallelism (e.g., OpenMP, OpenACC, OpenCL) but fail to address memory access patterns. The Kokkos C++ library enables applications and domain libraries to achieve performance portability on diverse manycore architectures by unifying abstractions for both fine-grain data parallelism and memory access patterns. In this paper we describe Kokkos’ abstractions, summarize its application programmer interface (API), present performance results for unit-test kernels and mini-applications, and outline an incremental strategy for migrating legacy C++ codes to Kokkos. The Kokkos library is under active research and development to incorporate capabilities from new generations of manycore architectures, and to address a growing list of applications and domain libraries.     

一种支持细粒度并行的SDN虚拟化编程框架

软件定义网络(software defined network,简称SDN)通过集中式的控制器提高了网络的可编程性,成为近年来网络领域非常热门的话题。以Openflow网络为代表的软件定义网络将逻辑控制与数据转发相隔离,为网络虚拟化技术提供了良好的平台。集中式的抽象与控制使得SDN虚拟化框架的处理效率成为主要瓶颈。现有的SDN虚拟化框架由于缺乏对细粒度并行的支持,为编程人员充分利用多核/众核资源、控制更大规模的网络带来了极大的挑战。为了提高SDN虚拟化框架的处理效率,提出一种新的SDN虚拟化编程框架,通过新颖的API和运行时,在框架内部支持细粒度的并行处理。该框架通过对网络中流和网络资源进行抽象,使开发人员可以直接通过划分流空间来定义不同的虚拟网络,利用无锁的编程方式对共享的网络资源和流进行操作。实验结果表明,该框架在逻辑控制的执行效率方面具有良好的可扩展性,可以创建出更大规模的虚拟网络,并对其进行更为复杂的控制。     

OpenMDSP: Extending OpenMP to Program Multi-Core DSPs

Abstract Multi-core digital signal processors （DSPs） are widely used in wireless telecommunication, core network transcoding, industrial control, and audio/video processing technologies, among others. In comparison with general-purpose multi-processors, multi-core DSPs normally have a more complex memory hierarchy, such as on-chip core-local memory and non-cache-coherent shared memory. As a result, efficient multi-core DSP applications are very difficult to write. The current approach used to program multi-core DSPs is based on proprietary vendor software development kits （SDKs）, which only provide low-level, non-portable primitives. While it is acceptable to write coarse-grained task-level parallel code with these SDKs, writing fine-grained data parallel code with SDKs is a very tedious and error-prone approach. We believe that it is desirable to possess a high-level and portable parallel programming model for multi-core DSPs. In this paper, we propose OpenMDSP, an extension of OpenMP designed for multi-core DSPs. The goal of OpenMDSP is to fill the gap between the OpenMP memory model and the memory hierarchy of multi-core DSPs. We propose three classes of directives in OpenMDSP, including 1） data placement directives that allow programmers to control the placement of global variables conveniently, 2） distributed array directives that divide a whole array into sections and promote the sections into core-local memory to improve performance, and 3） stream access directives that promote big arrays into core-local memory section by section during parallel loop processing while hiding the latency of data movement by the direct memory access （DMA） of a DSP. We implement the compiler and runtime system for OpenMDSP on PreeScale MSC8156. The benchmarking results show that seven of nine benchmarks achieve a speedup of more than a factor of 5 when using six threads.     

3D fingerprint reconstruction system using feature correspondences and prior estimated finger model

The paper studies a 3D fingerprint reconstruction technique based on multi-view touchless fingerprint images. This technique offers a solution for 3D fingerprint image generation and application when only multi-view 2D images are available. However, the difficulties and stresses of 3D fingerprint reconstruction are the establishment of feature correspondences based on 2D touchless fingerprint images and the estimation of the finger shape model. In this paper, several popular used features, such as scale invariant feature transformation (SIFT) feature, ridge feature and minutiae, are employed for correspondences establishment. To extract these fingerprint features accurately, an improved fingerprint enhancement method has been proposed by polishing orientation and ridge frequency maps according to the characteristics of 2D touchless fingerprint images. Therefore, correspondences can be established by adopting hierarchical fingerprint matching approaches. Through an analysis of 440 3D point cloud finger data (220 fingers, 2 pictures each) collected by a 3D scanning technique, i.e., the structured light illumination (SLI) method, the finger shape model is estimated. It is found that the binary quadratic function is more suitable for the finger shape model than the other mixed model tested in this paper. In our experiments, the reconstruction accuracy is illustrated by constructing a cylinder. Furthermore, results obtained from different fingerprint feature correspondences are analyzed and compared to show which features are more suitable for 3D fingerprint images generation.     

量子通信网络中高斯信道的研究

从量子Fokker-Plank方程出发,在量子通信网络中构造出一种可行的量子高斯信道。变换Fokker-Plank方程的解并代入互信息公式经过一系列的复杂运算,得到相干态表象中的量子动力学互信息方程,在此基础上,提出具有可行性的量子态并行传播方案。该方案将光子加密态的系数看成信号,将传递在量子高斯信道中的信息进行编码后输入,然后通过提取和解码光子加密态的系数得到输出端信息。利用携带量子信息的谐振子编码态在量子高斯信道中进行传递,与经典高斯信道相比具有量子并行性的优点。     

A power-aware code-compression design for RISC/VLIW architecture

We studied the architecture of embedded computing systems from the viewpoint of power consumption in memory systems and used a selective-code-compression (SCC) approach to realize our design.Based on t...     

基于动态确定度传播的选择性采样

传统主动学习中采用的批量采样模式忽略了样本之间的相互关系,因而会不可避免地引入冗余。针对上述问题,提出了一种动态批量采样模式,采取"逐一标注,批量训练"的流程,综合利用当前分类模型和先前标注样本对后续采样进行动态指导;在此基础上,进一步提出了基于动态确定度传播的选择性采样算法,有效地提高了所选取样本的信息量。实验结果证明,基于动态确定度传播的选择性采样算法能够显著改进分类结果。