A parallel progressive radiosity algorithm based on patch data circulation

Cataloged from PDF version of article.Current research on radiosity has concentrated on increasing the accuracy and the speed of the solution. Although algorithmic and meshing techniques decrease the execution time, still excessive computational power is required for complex scenes. Hence, parallelism can be exploited for speeding up the method further. This paper aims at providing a thorough examination of parallelism in the basic progressive refinement radiosity, and investigates its parallelization on distributed-memory parallel architectures. A synchronous scheme, based on static task assignment, is proposed to achieve better coherence for shooting patch selections. An efficient global circulation scheme is proposed for the parallel light distribution computations, which reduces the total volume of concurrent communication by an asymptotical factor. The proposed parallel algorithm is implemented on an Intel's iPSC/2 hypercube multicomputer. Load balance qualities of the proposed static assignment schemes are evaluated experimentally. The effect of coherence in the parallel light distribution computations on the shooting patch selection sequence is also investigated. Theoretical and experimental evaluation is also presented to verify that the proposed parallelization scheme yields equally good performance on multicomputers implementing the simplest (e.g. ring) as well as the richest (e.g. hypercube) interconnection topologies. This paper also proposes and presents a parallel load re-balancing scheme which enhances our basic parallel radiosity algorithm to be usable in the parallelization of radiosity methods adopting adaptive subdivision and meshing techniques. (C) 1996 Elsevier Science Lt

A parallel framework for in-memory construction of term-partitioned inverted indexes

Cataloged from PDF version of article.With the advances in cloud computing and huge RAMs provided by 64-bit architectures, it is possible to tackle large problems using memory-based solutions. Construction of term-based, partitioned, parallel inverted indexes is a communication intensive task and suitable for memory-based modeling. In this paper, we provide an efficient parallel framework for in-memory construction of term-based partitioned, inverted indexes. We show that, by utilizing an efficient bucketing scheme, we can eliminate the need for the generation of a global vocabulary. We propose and investigate assignment schemes that can reduce the communication overheads while minimizing the storage and final query processing imbalance. We also present a study on how communication among processors should be carried out with limited communication memory in order to reduce the total inversion time. We present several different communication-memory organizations and discuss their advantages and shortcomings. The conducted experiments indicate promising results. © 2012 The Author. Published by Oxford University Press on behalf of The British Computer Society

Nutrient contents and in vitro digestibility of different parts of corn plant

AbstractThe objective of this study was to assess the nutrient contents and in vitro true digestibility (IVTD) of parts of the corn plant. The corn used in the study was P2088, a variety that is grown widely in Turkey. It had matured and was harvested 140 days after planting. Four replicate plants were separated into nine parts, namely lower stalk, central stalk, upper stalk, corn ear stalk, corn ear shuck, kernels, corn cob, leaf, tassel, plus the entire plant. The samples were dried and ground for analysis. Nutritional values were determined in the laboratory and in vitro digestibility was assessed. Significant differences in nutrient content were observed among parts of the corn plant. The highest crude protein (CP) content was found in the leaf (12.41%), followed by the grain (12.37%). Dry matter (DM) varied from 91.25% to 96.07%. The highest ether extract (EE) was in the grain (2.84%), and the upper stalk contained the least EE (0.29%). The parts also differed in their contents of crude cellulose (CS) and crude ash (CA) (P <0.001). Most organic matter (OM) was found in the corn cup (94.27%). The highest in vitro dry matter digestibility (IVDMD) was in the kernels (79.06%) and the lowest was in the lower stalk (38.13%). In terms of in vitro true organic matter digestibility (OMD) values of the corn plant and its 9 parts, the highest values were found in the kernels and the lowest in the lower stalk.Keywords: crude nutrients, in vitro true digestibility, parts of corn plan

Memory resident parallel inverted index construction

Advances in cloud computing, 64-bit architectures and huge RAMs enable performing many search related tasks in memory.We argue that term-based partitioned parallel inverted index construction is among such tasks, and provide an efficient parallel framework that achieves this task. We show that by utilizing an efficient bucketing scheme we can eliminate the need for the generation of a global index and reduce the communication overhead without disturbing balancing constraint. We also propose and investigate assignment schemes that can further reduce communication overheads without disturbing balancing constraints. The conducted experiments indicate promising results. © 2012 Springer-Verlag London Limited

Bimetallic Two-Dimensional Metal–Organic Frameworks for the Chemiresistive Detection of Carbon Monoxide

This paper describes the demonstration of a series of heterobimetallic, isoreticular 2D conductive metal–organic frameworks (MOFs) with metallophthalocyanine (MPc, M=Co and Ni) units interconnected by Cu nodes towards low-power chemiresistive sensing of ppm levels of carbon monoxide (CO). Devices achieve a sub-part-per-million (ppm) limit of detection (LOD) of 0.53 ppm toward CO at a low driving voltage of 0.1 V. MPc-based Cu-linked MOFs can continuously detect CO at 50 ppm, the permissible exposure limit required by the Occupational Safety and Health Administration (OSHA), for multiple exposures, and realize CO detection in air and in humid environment. Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), density functional theory (DFT) calculations, and comparison experiments suggest the contribution of Cu nodes to CO binding and the essential role of MPc units in tuning and amplifying the sensing response

Constrained Min-Cut replication for K-Way hypergraph partitioning

Cataloged from PDF version of article.Replication is a widely-used technique in information retrieval and database systems for providing fault tolerance and reducing parallelization and processing costs. Combinatorial models based on hypergraph partitioning are proposed for various problems arising in information retrieval and database systems. We consider the possibility of using vertex replication to improve the quality of hypergraph partitioning. In this study, we focus on the constrained min-cut replication (CMCR) problem, where we are initially given a maximum replication capacity and a K-way hypergraph partition with an initial imbalance ratio. The objective in the CMCR problem is finding the optimal vertex replication sets for each part of the given partition such that the initial cut size of the partition is minimized, where the initial imbalance is either preserved or reduced under the given replication capacity constraint. In this study, we present a complexity analysis of the CMCR problem and propose a model based on a unique blend of coarsening and integer linear programming (ILP) schemes. This coarsening algorithm is derived from a novel utilization of the Dulmage-Mendelsohn decomposition. Experiments show that the ILP formulation coupled with the Dulmage-Mendelsohn decomposition-based coarsening provides high quality results in practical execution times for reducing the cut size of a given K-way hypergraph partition. © 2014 INFORMS

A machine learning approach for result caching in web search engines

A commonly used technique for improving search engine performance is result caching. In result caching, precomputed results (e.g., URLs and snippets of best matching pages) of certain queries are stored in a fast-access storage. The future occurrences of a query whose results are already stored in the cache can be directly served by the result cache, eliminating the need to process the query using costly computing resources. Although other performance metrics are possible, the main performance metric for evaluating the success of a result cache is hit rate. In this work, we present a machine learning approach to improve the hit rate of a result cache by facilitating a large number of features extracted from search engine query logs. We then apply the proposed machine learning approach to static, dynamic, and static-dynamic caching. Compared to the previous methods in the literature, the proposed approach improves the hit rate of the result cache up to 0.66%, which corresponds to 9.60% of the potential room for improvement. © 2017 Elsevier Lt

SE4SEE: A grid-enabled search engine for South-East Europe

Search Engine for South-East Europe (SE4SEE) is an application project aiming to develop a grid-enabled search engine that specifically targets the countries in the South-East Europe. It is one of the two selected regional applications currently implemented in the SEE-GRID FP6 project. This paper describes the design details of SE4SEE and provides an architectural overview of the application

Analyzing and enhancing OSKI for sparse matrix-vector multiplication

Sparse matrix-vector multiplication (SpMxV) is a kernel operation widely used in iterative linear solvers. The same sparse matrix is multiplied by a dense vector repeatedly in these solvers. Matrices with irregular sparsity patterns make it difficult to utilize cache locality effectively in SpMxV computations. In this work, we investigate single- and multiple-SpMxV frameworks for exploiting cache locality in SpMxV computations. For the single-SpMxV framework, we propose two cache-size-aware top-down row/column-reordering methods based on 1D and 2D sparse matrix partitioning by utilizing the column-net and enhancing the row-column-net hypergraph models of sparse matrices. The multiple-SpMxV framework depends on splitting a given matrix into a sum of multiple nonzero-disjoint matrices so that the SpMxV operation is performed as a sequence of multiple input- and output-dependent SpMxV operations. For an effective matrix splitting required in this framework, we propose a cache-size-aware top-down approach based on 2D sparse matrix partitioning by utilizing the row-column-net hypergraph model. The primary objective in all of the three methods is to maximize the exploitation of temporal locality. We evaluate the validity of our models and methods on a wide range of sparse matrices by performing actual runs through using OSKI. Experimental results show that proposed methods and models outperform state-of-the-art schemes.Comment: arXiv admin note: substantial text overlap with arXiv:1202.385

Home ground advantage: Local Atlantic salmon have higher reproductive fitness than dispersers in the wild

A long-held, but poorly tested, assumption in natural populations is that individuals that disperse into new areas for reproduction are at a disadvantage compared to individuals that reproduce in their natal habitat, underpinning the eco-evolutionary processes of local adaptation and ecological speciation. Here, we capitalize on fine-scale population structure and natural dispersal events to compare the reproductive success of local and dispersing individuals captured on the same spawning ground in four consecutive parent-offspring cohorts of wild Atlantic salmon (Salmo salar). Parentage analysis conducted on adults and juvenile fish showed that local females and males had 9.6 and 2.9 times higher reproductive success than dispersers, respectively. Our results reveal how higher reproductive success in local spawners compared to dispersers may act in natural populations to drive population divergence and promote local adaptation over microgeographic spatial scales without clear morphological differences between populations