Evidence map›Paper›PMID 25264418›Full record

ArticleIEEE transactions on knowledge and data engineering2014

Computing Spatial Distance Histograms for Large Scientific Datasets On-the-Fly.

Anand Kumar, Vladimir Grupcev, Yongke Yuan, Jin Huang, Yi-Cheng Tu, Gang Shen

Abstract read
In one paragraph

Article in IEEE transactions on knowledge and data engineering, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Anand KumarDepartment of Computer Science and Engineering, University of South Florida, 4202 E. Fowler Ave., ENB 118, Tampa, FL 33620, U.S.A.
Vladimir GrupcevDepartment of Computer Science and Engineering, University of South Florida, 4202 E. Fowler Ave., ENB 118, Tampa, FL 33620, U.S.A.
Yongke YuanSchool of Economics and Management, Beijing University of Technology, 100 Pingleyuan, Chaoyang District, Beijing 100124, China.
Jin HuangDepartment of Computer Science, University of Texas at Arlington, 500 UTA Boulevard, Room 640, ERB Buildings, Arlington, TX 76019, U.S.A.
Yi-Cheng TuDepartment of Computer Science and Engineering, University of South Florida, 4202 E. Fowler Ave., ENB 118, Tampa, FL 33620, U.S.A.
Gang ShenDepartment of Statistics, North Dakota State University, 201H Waldron Hall, Fargo, ND 58108, U.S.A.

Funding

Database-centric data analysis of molecular simulationsR01GM086707 · NIGMS · UNIVERSITY OF SOUTH FLORIDA · PI TU, YICHENG · 2010 to 2014
$863k
NIGMS NIH HHS R01 GM086707
6 · The paper itself

Abstract

This paper focuses on an important query in scientific simulation data analysis: the Spatial Distance Histogram (SDH). The computation time of an SDH query using brute force method is quadratic. Often, such queries are executed continuously over certain time periods, increasing the computation time. We propose highly efficient approximate algorithm to compute SDH over consecutive time periods with provable error bounds. The key idea of our algorithm is to derive statistical distribution of distances from the spatial and temporal characteristics of particles. Upon organizing the data into a Quad-tree based structure, the spatiotemporal characteristics of particles in each node of the tree are acquired to determine the particles' spatial distribution as well as their temporal locality in consecutive time periods. We report our efforts in implementing and optimizing the above algorithm in Graphics Processing Units (GPUs) as means to further improve the efficiency. The accuracy and efficiency of the proposed algorithm is backed by mathematical analysis and results of extensive experiments using data generated from real simulation studies.

Indexed as

density mapGPUquad-treeScientific databasesspatial distance histogramspatiotemporal locality

Identifiers

PMID25264418
PMCPMC4172330

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.