Evidence map›Paper›PMID 27655341›Full record

ArticleNeuroinformatics2017

Automating NEURON Simulation Deployment in Cloud Resources.

David B Stockton, Fidel Santamaria

Abstract read
In one paragraph

Article in Neuroinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

2 authors.

David B StocktonDepartment of Biomedical Engineering, The University of Texas at San Antonio, San Antonio, TX, 78249, USA. david.stockton@utsa.edu.
Fidel SantamariaDepartment of Biology, The University of Texas at San Antonio, San Antonio, TX, 78249, USA.

Funding

RCMI Center for Interdiscplinary Health Research CIHRG12MD007591 · NIMHD · UNIVERSITY OF TEXAS SAN ANTONIO · PI PERRY, GEORGE · 2012 to 2016
$10.4M
NIMHD NIH HHS G12 MD007591
6 · The paper itself

Abstract

Simulations in neuroscience are performed on local servers or High Performance Computing (HPC) facilities. Recently, cloud computing has emerged as a potential computational platform for neuroscience simulation. In this paper we compare and contrast HPC and cloud resources for scientific computation, then report how we deployed NEURON, a widely used simulator of neuronal activity, in three clouds: Chameleon Cloud, a hybrid private academic cloud for cloud technology research based on the OpenStack software; Rackspace, a public commercial cloud, also based on OpenStack; and Amazon Elastic Cloud Computing, based on Amazon's proprietary software. We describe the manual procedures and how to automate cloud operations. We describe extending our simulation automation software called NeuroManager (Stockton and Santamaria, Frontiers in Neuroinformatics, 2015), so that the user is capable of recruiting private cloud, public cloud, HPC, and local servers simultaneously with a simple common interface. We conclude by performing several studies in which we examine speedup, efficiency, total session time, and cost for sets of simulations of a published NEURON model.

Indexed as

Cloud ComputingComputer SimulationComputing MethodologiesSoftwareAlgorithmsHumansInternetNeuronsUser-Computer InterfaceCloud computingComputational neuroscienceComputer simulationGrid computingNeuroManagerNEURON (RRID:SCR_005393)

Identifiers

PMID27655341
PMCPMC5669366

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.