880 resultados para Parallel processing (Electronic computer)
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The goal of the RAP-WAM AND-parallel Prolog abstract architecture is to provide inference speeds significantly beyond those of sequential systems, while supporting Prolog semantics and preserving sequential performance and storage efficiency. This paper presents simulation results supporting these claims with special emphasis on memory performance on a two-level sharedmemory multiprocessor organization. Several solutions to the cache coherency problem are analyzed. It is shown that RAP-WAM offers good locality and storage efficiency and that it can effectively take advantage of broadcast caches. It is argued that speeds in excess of 2 ML IPS on real applications exhibiting medium parallelism can be attained with current technology.
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This paper presents an approximation to the study of parallel systems using sequential tools. The Independent And-parallelism in Prolog is an example of parallel processing paradigm in the framework of logic programming, and implementations like
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This paper presents an approximation to the study of parallel systems using sequential tools. The Independent And-parallelism in Prolog is an example of parallel processing paradigm in the framework of logic programming, and implementations like
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This paper presents an approach to create what we have called a Unified Sentiment Lexicon (USL). This approach aims at aligning, unifying, and expanding the set of sentiment lexicons which are available on the web in order to increase their robustness of coverage. One problem related to the task of the automatic unification of different scores of sentiment lexicons is that there are multiple lexical entries for which the classification of positive, negative, or neutral {P, Z, N} depends on the unit of measurement used in the annotation methodology of the source sentiment lexicon. Our USL approach computes the unified strength of polarity of each lexical entry based on the Pearson correlation coefficient which measures how correlated lexical entries are with a value between 1 and -1, where 1 indicates that the lexical entries are perfectly correlated, 0 indicates no correlation, and -1 means they are perfectly inversely correlated and so is the UnifiedMetrics procedure for CPU and GPU, respectively. Another problem is the high processing time required for computing all the lexical entries in the unification task. Thus, the USL approach computes a subset of lexical entries in each of the 1344 GPU cores and uses parallel processing in order to unify 155802 lexical entries. The results of the analysis conducted using the USL approach show that the USL has 95.430 lexical entries, out of which there are 35.201 considered to be positive, 22.029 negative, and 38.200 neutral. Finally, the runtime was 10 minutes for 95.430 lexical entries; this allows a reduction of the time computing for the UnifiedMetrics by 3 times.
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There is a need for faster and more sensitive algorithms for sequence similarity searching in view of the rapidly increasing amounts of genomic sequence data available. Parallel processing capabilities in the form of the single instruction, multiple data (SIMD) technology are now available in common microprocessors and enable a single microprocessor to perform many operations in parallel. The ParAlign algorithm has been specifically designed to take advantage of this technology. The new algorithm initially exploits parallelism to perform a very rapid computation of the exact optimal ungapped alignment score for all diagonals in the alignment matrix. Then, a novel heuristic is employed to compute an approximate score of a gapped alignment by combining the scores of several diagonals. This approximate score is used to select the most interesting database sequences for a subsequent Smith–Waterman alignment, which is also parallelised. The resulting method represents a substantial improvement compared to existing heuristics. The sensitivity and specificity of ParAlign was found to be as good as Smith–Waterman implementations when the same method for computing the statistical significance of the matches was used. In terms of speed, only the significantly less sensitive NCBI BLAST 2 program was found to outperform the new approach. Online searches are available at http://dna.uio.no/search/
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The patterns of cortico-cortical and cortico-thalamic connections of auditory cortical areas in the rhesus monkey have led to the hypothesis that acoustic information is processed in series and in parallel in the primate auditory cortex. Recent physiological experiments in the behaving monkey indicate that the response properties of neurons in different cortical areas are both functionally distinct from each other, which is indicative of parallel processing, and functionally similar to each other, which is indicative of serial processing. Thus, auditory cortical processing may be similar to the serial and parallel “what” and “where” processing by the primate visual cortex. If “where” information is serially processed in the primate auditory cortex, neurons in cortical areas along this pathway should have progressively better spatial tuning properties. This prediction is supported by recent experiments that have shown that neurons in the caudomedial field have better spatial tuning properties than neurons in the primary auditory cortex. Neurons in the caudomedial field are also better than primary auditory cortex neurons at predicting the sound localization ability across different stimulus frequencies and bandwidths in both azimuth and elevation. These data support the hypothesis that the primate auditory cortex processes acoustic information in a serial and parallel manner and suggest that this may be a general cortical mechanism for sensory perception.
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Partial differential equation (PDE) solvers are commonly employed to study and characterize the parameter space for reaction-diffusion (RD) systems while investigating biological pattern formation. Increasingly, biologists wish to perform such studies with arbitrary surfaces representing ‘real’ 3D geometries for better insights. In this paper, we present a highly optimized CUDA-based solver for RD equations on triangulated meshes in 3D. We demonstrate our solver using a chemotactic model that can be used to study snakeskin pigmentation, for example. We employ a finite element based approach to perform explicit Euler time integrations. We compare our approach to a naive GPU implementation and provide an in-depth performance analysis, demonstrating the significant speedup afforded by our optimizations. The optimization strategies that we exploit could be generalized to other mesh based processing applications with PDE simulations.
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Includes bibliographical references.
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"UILU-ENG 77 1719."
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Vita.
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Bibliography: p. 85.
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Originally presented as the author's thesis (M.A.), University of Illinois at Urbana-Champaign.
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Originally presented as the author's thesis, University of Illinois at Urbana-Champaign.
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"February, 1969"
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Mode of access: Internet.