基于Spark SQL的分布式全文检索框架的设计与实现

随着信息化的深入,大数据在各个领域产生了巨大的价值,海量数据的存储和快速分析成为新的挑战。传统的关系型数据库由于性能、扩展性的不足以及价格昂贵等方面的缺点,难以满足大数据的存储和分析需求。Spark SQL是基于大数据处理框架Spark的数据分析工具,目前已支持TPC-DS基准,成为大数据背景下传统数据仓库的替代解决方案。全文检索作为一种文本搜索的有效方式,能够与一般的查询操作结合使用,提供更加丰富的查询和分析操作。目前,Spark SQL仅支持简单的查询操作,不支持全文检索。为了满足传统业务迁移和现有业务的使用需求,提出了分布式全文检索框架,涵盖了SQL文法、SQL翻译转换框架、全文检索并行化、检索优化4个模块,并在Spark SQL上进行了实现。实验结果表明相比于传统的数据库,在两种检索优化策略下,该框架的索引构建时间、查询时间分别减少到传统数据库的0.6%/0.5%和1%/10%,索引存储量减少为传统数据库的55.0%。     

液浮靶标靶板的设计与实验

为了设计光轴一致性检测中用于基准光轴空间角监测的液浮空间角靶标,确定了液浮靶板选择原则。首先,利用流体力学对靶板在浮液中的横摇固有周期进行了分析;然后,结合谐振等相关知识,分析了靶板横摇固有周期与浮液震荡周期不同比值下,靶板的稳定情况;最后,确定了靶板横摇固有周期应大于浮液震荡周期的靶板选择原则。通过对不同厚度的圆柱形靶板及半球形靶板的分析,选择横摇固有周期较大的半球形靶板,并通过实验验证了所确定的靶板选择原则的正确性。     

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。     

Avoiding Conversion and Rearrangement Overhead in SIMD Architectures

Single-Instruction Multiple-Data (SIMD) instructions provide an inexpensive way to exploit the Data-Level Parallelism in multimedia applications. However, the performance improvement obtained by employing SIMD instructions is often limited because frequently many overhead instructions are required to bring data in a form amenable to SIMD processing. In this paper, we employ two techniques to overcome this limitation. The first technique, extended subwords, uses four extra bits for every byte in a media register. This allows many SIMD operations to be performed without overflow and avoids packing/unpacking conversion overhead. The second technique, Matrix Register File (MRF), allows flexible row-wise as well as column-wise access to the register file. It is useful for many two-dimensional multimedia algorithms such as the (I) Discrete Cosine Transform, 2 × 2 Haar Transform, and pixel padding. In addition, we propose a few new media instructions. Experimental results obtained by extending the SimpleScalar toolset show that these techniques improve performance by up to a factor of 4.5 compared to a conventional SIMD instruction set extension.     

High Performance General-Purpose Microprocessors: Past and Future

It can be observed from looking backward that processor architecture is improved through spirally shifting from simple to complex and from complex to simple. Nowadays we are facing another shifting from complex to simple, and new innovative architecture will emerge to utilize the continuously increasing transistor budgets. The growing importance of wire delays, changing workloads, power consumption, and design/verification complexity will drive the forthcoming era of Chip Multiprocessors （CMPs）. Furthermore, typical CMP projects both from industries and from academics are investigated. Through going into depths for some primary theoretical and implementation problems of CMPs, the great challenges and opportunities to future CMPs are presented and discussed. Finally, the Godson series microprocessors designed in China are introduced.     

面向线程级前瞻的线程划分方法浅析

正确合理的线程划分方法是提取线程级并行性的必要前提，线程级前瞻技术是简化线程划分复杂度提高系统性能的重要手段。本文讨论了几种支持线程级前瞻的典型线程划分方法，在此基础上提出了线程级划分需要解决的关键问题，并蛄合一典型自动线程划分算法进行了具体分析，提出了线程划分需要进一步研究的问题。     

Linux平台下增强型定时器服务的研究

智能化的嵌入式产品普遍需要一定的实时性，这对定时机制提出了更高的要求。本文针对 linux 平台的用户态定时 器服务的现状，提出了增强型定时器的设计方案，主要是在多模式、并行性及时间粒度方面做了改时。     

A FPGA-Based Systolic Array Prototype Implementing the Quadrant Interlocking Factorization Method

The systolic processing offers the possibility of solving a large number of standard problems on multicellular computing devices with autonomous cells (Processing Elements—PEs). The resulting systolic arrays exploit the underlying parallelism of many computationally intensive problems and offer a vital and effective way of handling them. Advances in technology and especially in VLSI and FPGA have an ongoing contribution to the evolution of systolic arrays. Herein, a FPGA-based Systolic array prototype implementing the Factorization stage of the Quadrant Interlocking Factorization—QIF (Butterfly) method is presented and the corresponding time-complexities achieved are discussed.     

Component-Based Derivation of a Parallel Stiff ODE Solver Implemented in a Cluster of Computers

A component-based methodological approach to derive distributed implementations of parallel ODE solvers is proposed. The proposal is based on the incorporation of explicit constructs for performance polymorphism into a methodology to derive group parallel programs of numerical methods from SPMD modules. These constructs enable the structuring of the derivation process into clearly defined steps, each one associated with a different type of optimization. The approach makes possible to obtain a flexible tuning of a parallel ODE solver for several execution contexts and applications. Following this methodological approach, a relevant parallel numerical scheme for solving stiff ODES has been optimized and implemented on a PC cluster. This numerical scheme is obtained from a Radau IIA Implicit Runge–Kutta method and exhibits a high degree of potential parallelism. Several numerical experiments have been performed by using several test problems with different structural characteristics. These experiments show satisfactory speedup results.     

New Alternatives to the Estimation Problem in Hardware-Software Codesign of Complex Embedded Systems: The H.261 Video Co-dec Case Study

As Codesign problems become larger and more realistic, the required time to estimate their solutions turns into an important bottleneck. This paper presents a new approach to improve the traditional estimation techniques, in order to avoid this drawback. The presented method has been successfully tested on a large experimental benchmark, attaining quality levels close to those provided by the Synopsys Behavioral Compiler. Finally, a case study based on the standard H.261 video co-dec is described, proving the convenience of the technique on real-life situations. The obtained results show a significant improvement in the process time, while keeping the good precision and fidelity levels that the traditional estimation models usually offer.