scholarly journals Information barrier experimental: Toward a trusted and open-source computing platform for nuclear warhead verification

Measurement ◽  
2018 ◽  
Vol 114 ◽  
pp. 185-190 ◽  
Author(s):  
Moritz Kütt ◽  
Malte Göttsche ◽  
Alexander Glaser
Author(s):  
Ashish Joglekar ◽  
Gurunath Gurrala ◽  
Puneet Kumar ◽  
Francis C Joseph ◽  
Kiran T S ◽  
...  

2016 ◽  
Author(s):  
Matei David ◽  
L.J. Dursi ◽  
Delia Yao ◽  
Paul C. Boutros ◽  
Jared T. Simpson

ABSTRACTMotivationThe highly portable Oxford Nanopore MinlON sequencer has enabled new applications of genome sequencing directly in the field. However, the MinlON currently relies on a cloud computing platform, Metrichor (metrichor.com), for translating locally generated sequencing data into basecalls.ResultsTo allow offline and private analysis of MinlON data, we created Nanocall. Nanocall is the first freely-available, open-source basecaller for Oxford Nanopore sequencing data and does not require an internet connection. On two E.coli and two human samples, with natural as well as PCR-amplified DNA, Nanocall reads have ~68% identity, directly comparable to Metrichor ”1D” data. Further, Nanocall is efficient, processing ~500Kbp of sequence per core hour, and fully parallelized. Using 8 cores, Nanocall could basecall a MinlON sequencing run in real time. Metrichor provides the ability to integrate the ”1D” sequencing of template and complement strands of a single DNA molecule, and create a ”2D” read. Nanocall does not currently integrate this technology, and addition of this capability will be an important future development. In summary, Nanocall is the first open-source, freely available, off-line basecaller for Oxford Nanopore sequencing data.AvailabilityNanocall is available at github.com/mateidavid/nanocall, released under the MIT license.Contactmatei.david at oicr.on.ca


Ubiquity ◽  
2018 ◽  
Vol 2018 (March) ◽  
pp. 1-15 ◽  
Author(s):  
Michael Kowolenko ◽  
Mladen A. Vouk

2018 ◽  
Vol 17 ◽  
pp. 03021
Author(s):  
Minglei Wu ◽  
Jingchang Pan

Monte Carlo method is also known as random simulation method. The more the number of experiments, the more accurate the results obtained. Therefore, a large number of random simulation is required in order to obtain a higher degree of accuracy, but the traditional stand-alone algorithm has been difficult to meet the needs of a large number of simulation. Hadoop platform is a distributed computing platform built on a large data background and an open source software under Apache. It is easier to write and run applications for processing massive amounts of data as an open source software platform. Therefore, this paper takes π value calculation as an example to realize the Monte Carlo algorithm based on Hadoop platform, and get the exact π value with the advantage of Hadoop platform in distributed processing.


Author(s):  
Srinivasa K. G. ◽  
Nishal Ancelette Pereira ◽  
Akshay K. Kallianpur ◽  
Subramanya E. Naligay

CloudStack is an Apache open source software that designed to install and handle large virtual machine (VM) networks, designed by Cloud.com and Citrix. This application is written in Java and was released under the terms of Apache License 2.0. This chapter discusses the easy availability and effortless scalability of CloudStack, which is an Infrastructure-as-a-service (IaaS) cloud computing platform software. We explore how CloudStack can either be used to setup public cloud services, or to provide a private cloud service.


Author(s):  
Fadi P. Deek ◽  
James A. M. McHugh
Keyword(s):  

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