6016075
Concept-based component libraries and optimizing compilers
This paper discusses concept lattices and some of their applications in component library development and compiler optimizations. Ongoing work on concept-based user-extensible simplification (type-based optimizer generators) and library transformations is first reviewed, then a new application--categorization of algorithms via precise descriptions of their performance characteristics--is outlined, with Standard Template Library and Boost Graph Library algorithm concept lattices as example.
44673545
Generic programming for high-performance scientific applications
We present case studies that apply generic programming to the development of high-performance parallel code for solving two archetypal partial differential equations (PDEs). We examine the overall structure of the example scientific codes and consider their generic implementation. With a generic approach it is a straightforward matter to reuse software components from different sources; implementations with components from the Iterative Template Library (ITL), the Matrix Template Library (MTL), Blitz++, A++/P++, and Fortran BLAS are presented. Our newly developed Generic Message Passing library is used for communication. We compare the generic implementations with equivalent implementations developed with alternative libraries and languages and discuss performance as well as software engineering issues. Copyright © 2005 John Wiley & Sons, Ltd.
14941056
Generic programming for high performance scientific applications
We present case studies that apply generic programming to the development of high-performance parallel code for solving two archetypal PDEs. We examine the overall structure of the example scientific codes and consider their generic implementation. With a generic approach it is a straight-forward matter to reuse software components from different sources; implementations with components from ITL, MTL, Blitz++, A++/P++, and Fortran BLAS are presented. Our newly-developed Generic Message Passing framework is used for communication. We compare the generic implementations to equivalent implementations developed with alternative libraries and languages and discuss not only performance but software engineering issues as well.
11364382
The Generic Message Passing framework
The paper presents the design and implementation of the Generic Message Passing framework (GMP). The design of the GMP is guided by two goals: programmer productivity and run-time performance, particularly for parallel systems having both shared and distributed memory (e.g., clusters of SMPs). To achieve these goals simultaneously, the GMP uses a generic programming paradigm, allowing it to integrate seamlessly with modern generic libraries such as the C++ Standard Library. In addition the GMP presents a single parallel programming model, namely message passing. The implementation of the GMP fully exploits the architectural characteristics of its execution target for maximum run-time performance. Performance results are presented that demonstrate the effectiveness of the Generic Message Passing framework.
15127206
Distributional Similarity Models: Clustering vs. Nearest Neighbors
Distributional similarity is a useful notion in estimating the probabilities of rare joint events. It has been employed both to cluster events according to their distributions, and to directly compute averages of estimates for distributional neighbors of a target event. Here, we examine the tradeoffs between model size and prediction accuracy for cluster-based and nearest neighbors distributional models of unseen events.
52861235
On bounding the delay of a critical path
312731
Mostly-Unsupervised Statistical Segmentation of Japanese: Applications to Kanji
Given the lack of word delimiters in written Japanese, word segmentation is generally considered a crucial first step in processing Japanese texts. Typical Japanese segmentation algorithms rely either on a lexicon and grammar or on pre-segmented data. In contrast, we introduce a novel statistical method utilizing unsegmented training data, with performance on kanji sequences comparable to and sometimes surpassing that of morphological analyzers over a variety of error metrics.
40898248
Using logic models to predict the detection behavior of statistical timing defects
In this paper, we study the possibility of using logic defect-level prediction models to predict the detection behavior of statistical timing defects. We compare two known logic models: the Williams-Brown (WB) model and the Mercer-Park-GrimailaDworak (MPGD) model. In the WB-model, the defect coverage is replaced by the n-detection transition fault coverage. We first demonstrate that both logic models may fail to predict the detection of statistical timing defects. Then, we propose an improved WB model based upon selection of the hard-to-detect transition faults. We show that, by selecting a proper subset of the hard-to-detect transition faults, the detection behavior of these faults can correlate well to the detection behavior of statistical timing defects. We explain our findings through statistical delay defect injection and simulation, and report results based upon various benchmark circuits.
1197
Mostly-unsupervised statistical segmentation of Japanese kanji sequences
Given the lack of word delimiters in written Japanese, word segmentation is generally considered a crucial first step in processing Japanese texts. Typical Japanese segmentation algorithms rely either on a lexicon and syntactic analysis or on pre-segmented data; but these are labor-intensive, and the lexico-syntactic techniques are vulnerable to the unknown word problem. In contrast, we introduce a novel, more robust statistical method utilizing unsegmented training data. Despite its simplicity, the algorithm yields performance on long kanji sequences comparable to and sometimes surpassing that of state-of-the-art morphological analyzers over a variety of error metrics. The algorithm also outperforms another mostly-unsupervised statistical algorithm previously proposed for Chinese. Additionally, we present a two-level annotation scheme for Japanese to incorporate multiple segmentation granularities, and introduce two novel evaluation metrics, both based on the notion of a compatible bracket, that can account for multiple granularities simultaneously.