In this paper, we propose a method on software performance test automation by using the virtualization. In general, most test engineers use the public performance testwares such as Load Runner and Silk Performer to validate the performance efficiency of their own systems. In case that they cannot use the performance testwares due to some technical limitations in the testwares, the testers should perform the testing in manually. As waste of computer and human resources is resulted from the situation, we need to propose the test automation scheme by using the virtualization technology to prevent the dissipation in the test environment which has limited resources. The system architecture considered efficient usage of computer resources and test automation to reduce human acts are addressed mainly in this paper. Finally, a number of experiments show that the proposed schemes allow offering the possibility for automated software performance testing by using the virtualization.

关键词：电子信息；软件；性能测试；可视化

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As the complexity of machines and architectures has increased, performance tuning has become more challenging, leading to the failure of general compilers to generate the best possible optimized code. Expert performance programmers can often hand-write code that outperforms compiler-optimized low-level code by an order of magnitude. At the same time, the complexity of programs has also increased, with modern programs built on a variety of abstraction layers to manage complexity, yet these layers hinder efforts at optimization. In fact, it is common to lose one or two additional orders of magnitude in performance when going from a low-level language such as Fortran or C to a high-level language like Python, Ruby, or Matlab. General purpose compilers are limited by the inability of program analysis to determine programmer intent, as well as the lack of detailed performance models that always determine the best executable code for a given computation and architecture. The latter problem can be mitigated through auto-tuning, which generates many code variants for a particular problem and empirically determines which performs best on a given architecture. This thesis addresses the problem of how to write programs at a high level while obtaining the performance of code written by performance experts at the low level. To do so, we build domain-specific embedded languages that generate low-level parallel code from a high-level language, and then use auto-tuning to determine the best performing low-level code. Such DSELs avoid analysis by restricting the domain while ensuring programmers specify high-level intent, and by performing empirical auto-tuning instead of modeling machine parameters. As a result, programmers write in high-level languages with portions of their code using DSELs, yet obtain performance equivalent to the best hand-optimized low-level code, across many architectures. We present a methodology for building such auto-tuned DSELs, as well as a software infrastructure and example DSELs using the infrastructure, including a DSEL for structured grid computations and two DSELs for graph algorithms. The structured grid DSEL obtains over 80% of peak performance for a variety of benchmark kernels across different architectures, while the graph algorithm DSELs mitigate all performance loss due to using a high-level language. Overall, the methodology, infrastructure, and example DSELs point to a promising new direction for obtaining high performance while programming in a high-level language.

关键词：复杂机器；编译器；DSELs；基础设施；SEJITS；Python；结构化网格计算

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This report is intended as a response to some of the questions posed by the FCC regarding the upcoming TV-band incentive auction, given in their NPRM, as they relate to the television whitespaces. In particular, we argue (1) that channel 37 should be made available for whitespace use; (2) that the channels reserved for wireless microphones should be reserved on an as-used basis only; and (3) that the guard bands which will be created via the incentive auction must be considered as database-registration-requiring whitespace if unlicensed devices are authorized to use them. These three proposals have two common themes: (1) they each work toward the goal of making otherwise-wasted spectrum available as whitespace; and (2) in each case, the key concept is that the involved parties can (and in some cases must) register their devices and use geolocation of some sort. We will sketch each of our proposals and show how together they can make whitespace available for up to 10 million more Americans with minimal overhead while ensuring that licensed users receive the quality of service that they expect. As a result, essentially no one would be left without whitespace access.

关键词：FCC；电视频带；NPRM；37频带；无线话筒；防护频带；空白电视信号频段

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What if robots and automation systems were not limited by onboard computation, memory, or programming? This is now practical with wireless networking and rapidly expanding Internet resources. In 2010, James Kuffner at Google introduced the term “Cloud Robotics" to describe a new approach to robotics that takes advantage of the Internet as a resource for massively parallel computation and real time sharing of vast data resources. The Google autonomous driving project exemplifes this approach: the system indexes maps and images that are collected and updated by satellite, Streetview, and crowdsourcing from the network to facilitate accurate localization. Another example is Kiva Systems new approach to warehouse automation and logistics using large numbers of mobile platforms to move pallets using a local network to coordinate planforms and update tracking data. These are just two new projects that build on resources from the Cloud. Steve Cousins of Willow Garage aptly summarized the idea: “No robot is an island." Cloud Robotics recognizes the wide availability of networking, incorporates elements of open-source, open-access, and crowdsourcing to greatly extend earlier concepts of “Online Robots" and “Networked Robots". Cloud Robotics has potential to improve robot performance in at least five ways: 1) Big Data: indexing a global library of images, maps, and object data, 2) Cloud Computing: parallel grid computing on demand for statistical analysis, learning, and motion planning, 3) Open-Source / Open-Access: humans sharing code, data, algorithms, and hardware designs, 4) Collective Robot Learning: robots sharing trajectories, control policies, and outcomes, and 5) Crowdsourcing and call centers: offline and on-demand human guidance for evaluation, learning, and error recovery. This article surveys related work as of Fall 2012.

关键词：机器人；自动化系统；无线网络；云机器人；在线机器人；网络机器人；大数据；云计算；开源；集体机器人学习；众包

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In this paper, we present an automated technique SWATI: Synthesizing Wordlengths Automatically Using Testing and Induction, which uses a combination of Nelder-Mead optimization based testing, and induction from examples to automatically synthesize optimal fixedpoint implementation of numerical routines. The design of numerical software is commonly done using floating-point arithmetic in design-environments such as Matlab. However, these designs are often implemented using fixed-point arithmetic for speed and efficiency reasons especially in embedded systems. The fixed-point implementation reduces implementation cost, provides better performance, and reduces power consumption. The conversion from floating-point designs to fixed-point code is subject to two opposing constraints: (i) the word-width of fixed-point types must be minimized, and (ii) the outputs of the fixed-point program must be accurate. In this paper, we propose a new solution to this problem. Our technique takes the floating-point program, specified accuracy and an implementation cost model and provides the fixed-point program with specified accuracy and optimal implementation cost. We demonstrate the effectiveness of our approach on a set of examples from the domain of automated control, robotics and digital signal processing.

关键词：SWATI；自动化技术；数值计算；Matlab；定点运算；浮点程序；机器人技术

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With the arrival of the Microsoft Kinect, obtaining depth maps of interior spaces has become remarkably easy. The Kinect is equipped with an 8-bit RGB VGA resolution (640x480 pixel) video camera, and also features an IR-triangulation based depth sensor with reports of accuracy within q(z) = 2:73z2 + 0:74z 0:58[mm], with z the depth in meters. The Kinect's low cost and portability make it an attractive instrument for robotics and mapping. We have witnessed a boon of large datasets originating from such Kinect-style cameras, and an associated development in algorithms for SLAM-like tasks. While the potential for this data is vast, one immediate application is incorporating the depth data into a more robust object detector.The remainder of this report is organized as follows: Part 2 describes previous work done in the area of object recognition and depth data. Part 3 describes the dataset. Part 4 gives our approach to the problem. Part 5 gives results of our method. Part 6 provides closing remarks.

关键词：Kinect；相机；目标检测；计算机视觉；数据集

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Breadth-first search (BFS) is a fundamental graph primitive frequently used as a building block for many complex graph algorithms. In the worst case, the complexity of BFS is linear in the number of edges and vertices, and the conventional top-down approach always takes as much time as the worst case.A recently discovered bottom-up approach manages to cut down the complexity all the way to the number of vertices in the best case, which is typically at least an order of magnitude less than the number of edges. The bottom-up approach is not always advantageous, so it is combined with the top-down approach to make the direction-optimizing algorithm which adaptively switches from top-down to bottom-up as the frontier expands.We present a scalable distributed-memory parallelization of this challenging algorithm and show up to an order of magnitude speedups compared to an earlier purely top-down code. Our approach also uses a 2D decomposition of the graph that has previously been shown to be superior to a 1D decomposition.Using the default parameters of the Graph500 benchmark, our new algorithm achieves a performance rate of over 240 billion edges per second on 115 thousand cores of a Cray XE6, which makes it over 7 faster than a conventional top-down algorithm using the same set of optimizations and data distribution.

关键词：广度优先搜索；BFS；自底向上；自下而上；算法

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We consider distributed memory algorithms for the all-pairs shortest paths (APSP) problem. Scaling the APSP problem to high concurrencies requires both minimizing inter-processor communication as well as maximizing temporal data locality.The 2.5D APSP algorithm, which is based on the divide-andconquer paradigm, satisfies both of these requirements: it can utilize any extra available memory to perform asymptotically less communication, and it is rich in semiring matrix multiplications,which have high temporal locality. We start by introducing a block-cyclic 2D (minimal memory) APSP algorithm. With a careful choice of block-size, this algorithm achieves known communication lower-bounds for latency and bandwidth. We extend this 2D block-cyclic algorithm to a 2.5D algorithm, which can use c extra copies of data to reduce the bandwidth cost by a factor of c1=2, compared to its 2D counterpart. However, the 2.5D algorithm increases the latency cost by c1=2. We provide a tighter lower bound on latency, which dictates that the latency overhead is necessary to reduce bandwidth along the critical path of execution. Our implementation achieves impressive performance and scaling to 24,576 cores of a Cray XE6 supercomputer by utilizing well-tuned intra-node kernels within the distributed memory algorithm.

关键词：所有对最短路径（APSP）；分布式内存算法；关键路径

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For emerging safety-critical systems, novel design methodologies are becoming necessary to cope with early stage design validation, performance and timing prediction, and design space exploration. In this paper, we propose a tool integration technique for architectural exploration of an aircraft electric power system (EPS) controller using Ptolemy II and Metro II to satisfy requirements imposed on safety-critical system design. The functional model of a newly suggested co-simulation environment is implemented with Ptolemy II and the model for architectural exploration is realized by SystemC. To construct the co-simulation environment and combine the functional model and the architectural model, Metro II semantics is employed. We verify effectiveness and extensibility of our new approach using experiments and results with example candidates for the aircraft EPS controller.

关键词：安全系统；飞机电力系统（EPS）；Metro II；Ptolemy II；SystemC

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Software bugs are inevitable in software-defined networking (SDN) control planes, and troubleshooting is a tedious, time-consuming task. In this paper we discuss how one might improve SDN network troubleshooting by presenting a technique, retrospective causal inference, for automatically identifying a minimal sequence of inputs responsible for triggering a given bug in the control software. Retrospective causal inference works by iteratively pruning inputs from the history of the execution, and coping with divergent histories by reasoning about the functional equivalence of events. We apply retrospective causal inference to three open source SDN control platforms---Floodlight, POX, and NOX---and illustrate how our technique found minimal causal sequences for the bugs we encountered.

关键词：软件定义网络（SDN）；故障排除；软件错误；软件bug；控制平台；照明灯；POX；NOX

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