The increasing complexity of vehicle control requires high quality of automotive control software. The software quality is guaranteed by the quality of the development process. Today, software is mostly developed acco...
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The increasing complexity of vehicle control requires high quality of automotive control software. The software quality is guaranteed by the quality of the development process. Today, software is mostly developed according to the V model, based on formal system descriptions that are increasingly refined on every level. Development of complex dynamic control software is a special challenge in automotive software design. This paper describes the MMCD controller design process developed by AVL. This process allows mostly automated development and calibration of multivariable control algorithms, leading to high quality. The integration in the V model is illustrated. First production applications will come shortly.
We study the problem of computing the k maximum sum subsequences. Given a sequence of real numbers (x(1), x(2),..., x(n)) and an integer parameter k, 1 <= k <= 1/2n(n - 1), the problem involves finding the k lar...
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ISBN:
(纸本)9783540241317
We study the problem of computing the k maximum sum subsequences. Given a sequence of real numbers (x(1), x(2),..., x(n)) and an integer parameter k, 1 <= k <= 1/2n(n - 1), the problem involves finding the k largest values of Sigma(j)(l=t) x(l) for 1 <= 1 <= j <= n. The problem for fixed k = 1, also known as the maximum sum subsequence problem, has received much attention in the literature and is linear-time solvable. Recently, Bae and Takaoka presented a Theta (nk)-time algorithm for the k maximum sum subsequences problem. In this paper we design an efficient algorithm that solves the above problem in O(min{k + n log(2) n, n root k}) time in the worst case. Our algorithm is optimal for k = Omega(n log(2) n) and improves over the previously best known result for any value of the user-defined parameter k < 1. Moreover, our results are also extended to the multi-dimensional versions of the k maximum sum subsequences problem;resulting in fast algorithms as well.
The transmission efficiencies of combination logging data and imaging logging data are restricted under finite bandwidth. A lossless data compression method based on the characteristics of logging data is put forward,...
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The transmission efficiencies of combination logging data and imaging logging data are restricted under finite bandwidth. A lossless data compression method based on the characteristics of logging data is put forward, it can transfer the logging data to surface after they are compressed, and therefore the transmission efficiency of logging data is effectively improved. The compression plan, compression processing and algorithm are described. Different types of data are compressed using different compression methods, and the compression ratios of them are compared. It is shown that, the compression ratio of frame-related compression method is the greatest, and the compression ratios of other compression methods are smaller;the compression ratio of the first kind of data is greater, that of combination logging data is secondary, and that of imaging logging data is the least;the compression ratio slightly increases with the increase of the quantity of the data.
We propose an algorithm for designing nonuniform oversampled filterbanks with arbitray delay. The filterbank has uniform sections obtained by generalized DFT modulation;between the uniform sections, there are transiti...
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We propose an algorithm for designing nonuniform oversampled filterbanks with arbitray delay. The filterbank has uniform sections obtained by generalized DFT modulation;between the uniform sections, there are transition filters. There is no a priori constraint on the widths of transition filters channels, as in previous publications. The designalgorithm is composed of three steps, in which a bank (analysis or synthesis) is optimized by solving convex optimization problems for finding the prototypes of uniform sections and the transition filters. In the first step, an orthogonal filterbank is designed, while in the other steps a bank is given and the other is optimized. We present an example of design suitable to subband processing of wideband speech signals.
Recently, energy dissipation for computations on FPGAs has become an important performance metric. In this paper, we summarize our recent efforts in developing an algorithm-level design methodology for optimizing the ...
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Recently, energy dissipation for computations on FPGAs has become an important performance metric. In this paper, we summarize our recent efforts in developing an algorithm-level design methodology for optimizing the energy performance of FPGA based implementations. For kernels, our design methodology consists of four steps: domain selection, domain-specific energy modeling, domain-space exploration and low-level simulation. To achieve system-level energy-efficiency, we outline a design methodology that integrates the kernel-level design methodology. Both the design methodologies can be used to achieve not only energy-efficiency but also latency, area, and power efficiency. We consider signal processing kernels as illustrative examples and demonstrate energy and time efficient algorithms and implementations for these on FPGAs. Example energy performance optimization through algorithmic optimizations include the 29-51% improvement in energy performance for a matrix multiplication kernel, 57-78% improvement for a FFT kernel and the 10-60% improvement for a floating-point LU decomposition kernel over state-of-the-art implementations. Similarly, an improvement of 41 to 46% in energy performance was achieved by the system-level design approach over a greedy approach for a MVDR adaptive beamforming application. Finally we briefly describe a high-level tool for obtaining parameterized and energy-efficient designs on FPGAs.
We develop new algorithms and architectures for matrix multiplication on configurable devices. These have reduced energy dissipation and latency compared with the state-of-the-art field-programmable gate array (FPGA)-...
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We develop new algorithms and architectures for matrix multiplication on configurable devices. These have reduced energy dissipation and latency compared with the state-of-the-art field-programmable gate array (FPGA)-based designs. By profiling well-known designs, we identify "energy hot spots," which are responsible for most of the energy dissipation. Based on this, we develop algorithms and architectures that offer tradeoffs among the number of I/O ports, the number of registers, and the number of PEs. To avoid time-consuming low-level simulations for energy profiling and performance prediction of many alternate designs, we derive functions to represent the impact of algorithm design choices on the system-wide energy dissipation, area, and latency. These functions are used to either optimize the energy performance or provide tradeoffs for a family of candidate algorithms and architectures. For selected designs, we perform extensive low-level simulations using state-of-the-art tools and target FPGA devices. We show a design space for matrix multiplication on FPGAs that results in tradeoffs;among energy, area, and latency. For example, our designs improve the energy performance of state-of-the-art FPGA-based designs by 29%-51% without any increase in the area-latency product. The latency of our designs is reduced one-third to one-fifteenth while area is increased 1.9-9.4 times. In terms of comprehensive metrics such as Energy-Area-Time, our designs exhibit superior performance compared with the state-of-the-art by 50%-79%.
作者：
He, JYao, XLi, JUniv Birmingham
Sch Comp Sci Ctr Excellence Res Computat Intelligence & Applic Birmingham B15 2TT W Midlands England
This paper compares three different evolutionary algorithms for solving the node covering problem: EA-I relies on the definition of the problem only without using any domain knowledge, while EA-II and EA-III employ ex...
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This paper compares three different evolutionary algorithms for solving the node covering problem: EA-I relies on the definition of the problem only without using any domain knowledge, while EA-II and EA-III employ extra heuristic knowledge. In theory, it is proven that all three algorithms can find an optimal solution in finite generations and find a feasible solution efficiently;but none of them can find the optimal solution efficiently for all instances of the problem. Through experiments, it is observed that all three algorithms can find a feasible solution efficiently, and the algorithms with extra heuristic knowledge can find better approximation solutions, but none of them can find the optimal solution to the first instance efficiently. This paper shows that heuristic knowledge is helpful for evolutionary algorithms to find good approximation solutions, but it contributes little to search for the optimal solution in some instances.
A regular hedge grammar is a formal method to specify XML schema. An XML document can be viewed as an ordered labeled tree. Given an XML schema, finding the sequence of changes with minimum cost is not just of theoret...
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A regular hedge grammar is a formal method to specify XML schema. An XML document can be viewed as an ordered labeled tree. Given an XML schema, finding the sequence of changes with minimum cost is not just of theoretical interest. This problem can be modeled, as given, as an ordered labeled tree (forest) F and as a regular hedge grammar P . We consider the minimum edit distance required to transform the forest F into F ' so that F ' is exactly matched by P . By introducing a leaf forest, we design an algorithm for solving this problem in time O (F-2 P ( F +log P )), where F is the size of the forest and P is the size of the grammar. To our knowledge, this is the first algorithm to transform an XML document (ordered labeled tree) to conform to the schema (tree grammar).
We consider generic two-tiered Wireless Sensor Networks (WSNs) consisting of sensor clusters deployed around strategic locations, and base-stations (BSs) whose locations are relatively flexible. Within a sensor cluste...
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We consider generic two-tiered Wireless Sensor Networks (WSNs) consisting of sensor clusters deployed around strategic locations, and base-stations (BSs) whose locations are relatively flexible. Within a sensor cluster, there are many small sensor nodes (SNs) that capture, encode, and transmit relevant information from a designated area, and there is at least one application node ( AN) that receives raw data from these SNs, creates a comprehensive local-view, and forwards the composite bit-stream toward a BS. This paper focuses on the topology control process for ANs and BSs, which constitute the upper tier of two-tiered WSNs. Since heterogeneous ANs are battery-powered and energy-constrained, their node lifetime directly affects the network lifetime of WSNs. By proposing algorithmic approaches to locate BSs optimally, we can maximize the topological network lifetime of WSNs deterministically, even when the initial energy provisioning for ANs is no longer always proportional to their average bit-stream rate. The obtained optimal BS locations are under different lifetime definitions according to the mission criticality of WSNs. By studying intrinsic properties of WSNs, we establish the upper and lower bounds of maximal topological lifetime, which enable a quick assessment of energy provisioning feasibility and topology control necessity. Numerical results are given to demonstrate the efficacy and optimality of the proposed topology control approaches designed for maximizing network lifetime of WSNs.
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