Data parallel algorithm

In this article, mixed integer linear programming of python (MIP) is used to model this problem with varying input data. The result shows that with small input data the modelling code of MIP executing quickly and converging to optimal value, while large scale input data require plenty of computation time; thereby algorithm improvement as well as parallel implementation are suggested.

6p viporsche 28-10-2022 2 2   Download

Continued part 1, part 2 of book "Compilers: Principles, Techniques, and Tools (Second Edition)" provide students with knowledge about: object-code generation, construction of basic blocks, generation of code from expressions and basic blocks, and register-allocation techniques; introduces the technology of code optimization, including ow graphs, data- ow frameworks, and iterative algorithms for solving these frameworks; instruction-level optimization; talks about larger-scale parallelism detection and exploitation;...

506p britaikridanik 05-07-2022 10 3   Download

This approach is quite effective in terms of both performance and memory use in the GPU architecture. In addition, GMiner solves the workload skewness problem from which the existing parallel methods suffer; as a result, its performance increases almost linearly as the number of GPUs increases.

20p guernsey 28-12-2021 9 0   Download

High-throughput molecular profiling data has been used to improve clinical decision making by stratifying subjects based on their molecular profiles. Unsupervised clustering algorithms can be used for stratification purposes.

9p vikentucky2711 26-11-2020 6 1   Download

Mapping of short sequencing reads is a crucial step in the analysis of RNA sequencing (RNA-seq) data. ContextMap is an RNA-seq mapping algorithm that uses a context-based approach to identify the best alignment for each read and allows parallel mapping against several reference genomes.

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The sentence alignment approach proposed by Moore, 2002 (M-Align) is an effective method which gets a relatively high performance based on combination of length-based and word correspondences. Nevertheless, despite the high precision, M-Align usually gets a low recall especially when dealing with sparse data problem.

13p vixyliton2711 17-04-2019 23 0   Download

In this paper, we introduce the Retail Transaction-Weighted Utility (RTWU) structure and propose two algorithms: EAHUIMiner algorithm and PEAHUI-Miner parallel algorithm. They have been experimented and compared to the two most efficient algorithms: EFIM and FHM. Results show that our algorithm is better with sparse datasets.

7p babysexy1803 21-02-2019 26 0   Download

This study proposes a parallel algorithm for the taxonomic assignment problem, called SeMetaPL, which aims to deal with the computational challenge. The proposed algorithm is evaluated with both simulated and real datasets on a high performance computing system. Experimental results demonstrate that the algorithm is able to achieve good performance and utilize resources of the system efficiently

12p thuyliebe 05-10-2018 19 0   Download

We estimate the parameters of a phrasebased statistical machine translation system from monolingual corpora instead of a bilingual parallel corpus. We extend existing research on bilingual lexicon induction to estimate both lexical and phrasal translation probabilities for MT-scale phrasetables. We propose a novel algorithm to estimate reordering probabilities from monolingual data. We report translation results for an end-to-end translation system using these monolingual features alone.

11p bunthai_1 06-05-2013 50 3   Download

In a language generation system, a content planner embodies one or more “plans” that are usually hand–crafted, sometimes through manual analysis of target text. In this paper, we present a system that we developed to automatically learn elements of a plan and the ordering constraints among them. As training data, we use semantically annotated transcripts of domain experts performing the task our system is designed to mimic.

8p bunrieu_1 18-04-2013 34 1   Download

We present a FrameNet-based semantic role labeling system for Swedish text. As training data for the system, we used an annotated corpus that we produced by transferring FrameNet annotation from the English side to the Swedish side in a parallel corpus. In addition, we describe two frame element bracketing algorithms that are suitable when no robust constituent parsers are available. We evaluated the system on a part of the FrameNet example corpus that we translated manually, and obtained an accuracy score of 0.

8p hongvang_1 16-04-2013 49 2   Download

This paper extends previous work on extracting parallel sentence pairs from comparable data (Munteanu and Marcu, 2005). For a given source sentence S, a maximum entropy (ME) classifier is applied to a large set of candidate target translations . A beam-search algorithm is used to abandon target sentences as non-parallel early on during classification if they fall outside the beam. This way, our novel algorithm avoids any document-level prefiltering step.

4p hongphan_1 15-04-2013 61 2   Download

This paper describes the design of the Gamma database machine and the techniques employed in its imple- mentation. Gamma is a relational database machine currently operating on an Intel iPSC/2 hypercube with 32 pro- cessors and 32 disk drives. Gamma employs three key technical ideas which enable the architecture to be scaled to 100s of processors. First, all relations are horizontally partitioned across multiple disk drives enabling relations to be scanned in parallel.

60p nhacsihuytuan 13-04-2013 44 4   Download

We propose a language-independent method for the automatic extraction of transliteration pairs from parallel corpora. In contrast to previous work, our method uses no form of supervision, and does not require linguistically informed preprocessing. We conduct experiments on data sets from the NEWS 2010 shared task on transliteration mining and achieve an F-measure of up to 92%, outperforming most of the semi-supervised systems that were submitted.

10p hongdo_1 12-04-2013 48 1   Download

We describe our experiments with training algorithms for tree-to-tree synchronous tree-substitution grammar (STSG) for monolingual translation tasks such as sentence compression and paraphrasing. These translation tasks are characterized by the relative ability to commit to parallel parse trees and availability of word alignments, yet the unavailability of large-scale data, calling for a Bayesian tree-to-tree formalism.

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The Greenplum Database parallel query optimizer (Figure 6) is responsible for converting SQL or MapReduce into a physical execution plan. It does this by using a cost-based optimization algorithm to evaluate a vast number of potential plans and select the one that it believes will lead to the most efficient query execution. Unlike a traditional query optimizer, Greenplum’s optimizer takes a global view of execution across the cluster, and factors in the cost of moving data between nodes in any candidate plan.

12p yasuyidol 02-04-2013 51 3   Download

We have implemented various inner loop algorithms, and have evaluated their performance on a Pentium 4 machine. The Pentium 4 has a SIMD instruction set that supports SIMD operations using up to 128-bit registers. Other ar- chitectures have similar SIMD instruction sets that support processing of several data elements in parallel, and the tech- niques presented here are applicable to those architectures too.

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JR is a language for concurrent programming. It is an imperative language that provides explicit mechanisms for concurrency, communication, and synchronization. JR is an extension of the Java programming language with additional concurrency mechanisms based on those in the SR (Synchronizing Resources) programming language. It is suitable for writing programs for both shared- and distributed-memory applications and machines; it is, of course, also suitable for writing sequential programs.

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This book deals with the acceleration of EDA algorithms using hardware platforms such as FPGAs and GPUs. Widely applied CAD algorithms are evaluated and compared for potential acceleration on FPGAs and GPUs. Coverage includes discussion of conditions under which it is preferable to use one platform over another, e.g., when an EDA problem has a high degree of data parallelism, the GPU is typically the preferred platform, whereas when the problem has more control, an FPGA may be preferred.

207p ken333 07-06-2012 134 23   Download

The main goal of Grid programming is the study of programming models, tools, and methods that support the effective development of portable and high-performance algorithms and applications on Grid environments. Grid programming will require capabilities and properties beyond that of simple sequential programming or even parallel and distributed programming.

24p huggoo 20-08-2010 72 4   Download