In this paper we present a new algorithm for accelerating the potential calculation which occurs in the inner loop of iterative algorithms for solving electromagnetic boundary integral equations. Such integral equations arise, for example, in the extraction of coupling capacitances in three-dimensional (3-D) geometries. We present extensive experimental comparisons with the capacitance extraction code FASTCAP [1] and demonstrate that, for a wide variety of geometries commonly encountered in integrated circuit packaging, on-chip interconnect and micro-electro-mechanical systems, the new "precorrectedFFT " algorithm is superior to the fast multipole algorithm used in FASTCAP in terms of execution time and memory use. At engineering accuracies, in terms of a speed-memory product, the new algorithm can be superior to the fast multipole based schemes by more than an order of magnitude.

Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract and label a person’s activities and significant places from traces of GPS data. In contrast to existing techniques, our approach simultaneously detects and classifies the significant locations of a person and takes the high-level context into account. Our system uses relational Markov networks to represent the hierarchical activity model that encodes the complex relations among GPS readings, activities and significant places. We apply FFT-based message passing to perform efficient summation over large numbers of nodes in the networks. We present experiments that show significant improvements over existing techniques. 1

. This paper surveys techniques for multiplying elements of various commutative rings. It covers Karatsuba multiplication, dual Karatsuba multiplication, Toom multiplication, dual Toom multiplication, the FFT trick, the twisted FFT trick, the split-radix FFT trick, Good's trick, the SchonhageStrassen trick, Schonhage's trick, Nussbaumer's trick, the cyclic SchonhageStrassen trick, and the Cantor-Kaltofen theorem. It emphasizes the underlying ring homomorphisms. 1.

Music Information Retrieval (MIR) is an interdisciplinary research area that has grown out of the need to manage burgeoning collections of music in digital form. Its diverse disciplinary communities have yet to articulate a common research agenda or agree on methodological principles and metrics of success. In order for MIR to succeed, researchers need to work with real user communities and develop research resources such as reference music collections, so that the wide variety of techniques being developed in MIR can be meaningfully compared with one another. Out of these efforts, a common MIR practice can emerge.

Rotated dispersed-dot dither is proposed as a new dither technique for digital halftoning. It is based on the discrete one-to-one rotation of a Bayer dispersed-dot dither array. Discrete rotation has the effect of rotating and splitting a significant part of the frequency impulses present in Bayer's halftone arrays into many low-amplitude distributed impulses. The halftone patterns produced by the rotated dither method therefore incorporate fewer disturbing artifacts than the horizontal and vertical components present in most of Bayer's halftone patterns. In grayscale wedges produced by rotated dither, texture changes at consecutive gray levels are much smoother than in error diffusion or in Bayer's dispersed-dot dither methods, thereby avoiding contouring effects. Due to its semi-clustering behavior at mid-tones,rotated dispersed -dot dither exhibits an improved tone reproduction behavior on printers having a significant dot gain, while maintaining the high detail rendition capabiliti...

Abstract – Large enterprise networks consist of thousands of services and applications. The performance and reliability of any particular application may depend on multiple services, spanning many hosts and network components. While the knowledge of such dependencies is invaluable for ensuring the stability and efficiency of these applications, thus far the only proven way to discover these complex dependencies is by exploiting human expert knowledge, which does not scale with the number of applications in large enterprises. Recently, researchers have proposed automated discovery of dependencies from network traffic [8, 18]. In this paper, we present a comprehensive study of the performance and limitations of this class of dependency discovery techniques (including our own prior work), by comparing with the ground truth of five dominant Microsoft applications. We introduce a new system, Orion, that discovers dependencies using packet headers and timing information in network traffic based on a novel insight of delay spike based analysis. Orion improves the state of the art significantly, but some shortcomings still remain. To take the next step forward, Orion incorporates external tests to reduce errors to a manageable level. Our results show Orion provides a solid foundation for combining automated discovery with simple testing to obtain accurate and validated dependencies. 1

The distance transform (DT) is a general operator forming the basis of many methods in computer vision and geometry, with great potential for practical applications. However, all the optimal algorithms for the computation of the exact Euclidean DT (EDT) were proposed only since the 1990s. In this work, state-of-theart sequential 2D EDT algorithms are reviewed and compared, in an effort to reach more solid conclusions regarding their differences in speed and their exactness. Six of the best algorithms were fully implemented and compared in practice.

this paper we outline additional applications of the FFT, discuss some issues involved in high-performance implementations of the FFT, and elaborate on our methodology for implementing FFTs. The paper is organized so that technical details are separate from the general discussion. Section 7, which contains a detailed discussion of our approach to implementing FFTs, can be skipped by the reader who is not interetested in the FFT. 2 Why the FFT?

This paper shows adaptive strategies to improve the reliability and performance of self-localization in robot soccer with legged robots. Adaptiveness is the common feature of the presented algorithms and has proved essential to enhance the quality of localization by a new classi cation technique, essential to increase the con dence level of internal information about the environment by extracting reliability information and by communicating them via parameterizable acoustic communication, and essential to circumvent manual implementations of walking patterns by evolving them automatically.

Energy-efficient computing is important in several systems ranging from embedded devices to large scale data centers. Several application domains offer the opportunity to tradeoff quality of service/solution (QoS) for improvements in performance and reduction in energy consumption. Programmers sometimes take advantage of such opportunities, albeit in an ad-hoc manner and often without providing any QoS guarantees. We propose a system called Green that provides a simple and flexible framework that allows programmers to take advantage of such approximation opportunities in a systematic manner while providing statistical QoS guarantees. Green enables programmers to approximate expensive functions and loops and operates in two phases. In the calibration phase, it builds a model of the QoS loss produced by the approximation. This model is used in the operational phase to make approximation decisions based on the QoS constraints specified by the programmer. The operational phase also includes an adaptation function that occasionally monitors the runtime behavior and changes the approximation decisions and QoS model to provide strong statistical QoS guarantees. To evaluate the effectiveness of Green, we implemented our system and language extensions using the Phoenix compiler framework. Our experiments using benchmarks from domains such as graphics, machine learning, signal processing, and finance, and an in-production, real-world web search engine, indicate that Green can produce significant improvements in performance and energy consumption with small and controlled QoS degradation.