scholarly journals HDF5 as a vehicle for in transit data movement

2019 ◽  
Author(s):  
Junmin Gu ◽  
Burlen Loring ◽  
Kesheng Wu ◽  
E. Wes Bethel
Keyword(s):  
Data Movement ◽  
In Transit

Intercontinental and transcontinental mail transit times from Europe to Berkeley, 1892 to 1941

1986 ◽  
Vol 13 (2) ◽  
pp. 141-154 ◽  
Author(s):  
RUDOLF SCHMID
Keyword(s):  
Transit Times ◽  
In Transit

SUMMARY Mail transit times from Germany to Berkeley, California, are computed for issues of the current awareness journals Botanisches Centralblatt (1880–1945) and the interdisciplinary Naturae Novitates (1879–1944). Issues of the former for 1892 to 1902 averaged 29.3 days (31.2 days if abnormal times are included) in transit from Kassel to Berkeley, with many issues (92) requiring only 20 to 25 days for intercontinental and transcontinental transit. Mail transit of Naturae Novitates from Berlin to Berkeley averaged 40.7 days (42 if abnormal times are included) per issue for 1903 to 1916 and 44 days (51.1 days) per issue for 1922 to 1941 (cumulatively averaging 42 days, or 45.9 days for abnormal times), with some issues in 1906 requiring only 11-12 days for intercontinental and transcontinental transit. A smaller sampling for Nature for 1923 and 1930 gave averages of, respectively, 21.5 and 22.4 days, with a minimum of 14 days in both years. These times are consistent with known transatlantic and transcontinental, ship and rail, mail transit times for these periods, as tabulated from various sources. For perspective, early intercontinental and transcontinental air transit times and pre-1892 intercontinental ship transit times are also tabulated.

Pablo Neruda's Transnational Modernist Networks: Colombo-Madrid-London-Buenos Aires (1927–1933)

2017 ◽  
Vol 12 (2) ◽  
pp. 198-225
Author(s):  
Patricia Novillo-Corvalán
Keyword(s):  
Chamber Music ◽  
Latin American ◽  
Buenos Aires ◽  
Cultural Institutions ◽  
Complex Composition ◽  
British Colonial ◽  
The One ◽  
Composition Process ◽  
In Transit ◽  
Standing Question

This article positions Pablo Neruda's poetry collection Residence on Earth I (written between 1925–1931 and published in 1933) as a ‘text in transit’ that allows us to trace the development of transnational modernist networks through the text's protracted physical journey from British colonial Ceylon (now Sri Lanka) to Madrid, and from José Ortega y Gasset's Revista de Occidente (The Western Review) to T. S. Eliot's The Criterion. By mapping the text's diasporic movement, I seek to reinterpret its complex composition process as part of an anti-imperialist commitment that proposes a form of aesthetic solidarity with artistic modernism in Ceylon, on the one hand, and as a vehicle through which to interrogate the reception and categorisation of Latin American writers and their cultural institutions in a British periodical such as The Criterion, on the other. I conclude with an examination of Neruda's idiosyncratic Spanish translation of Joyce's Chamber Music, which was published in the Buenos Aires little magazine Poesía in 1933, positing that this translation exercise takes to further lengths his decolonising views by giving new momentum to the long-standing question of Hiberno-Latin American relations.

Summary of the SciTech 2020 Technical Panel on In Situ/In Transit Computational Environments for Visualization and Data Analytics

2021 ◽  
Author(s):  
Earl P. Duque ◽  
Steve M. Legensky ◽  
Brad J. Whitlock ◽  
David H. Rogers ◽  
Andrew C. Bauer ◽  
...  
Keyword(s):  
Data Analytics ◽  
In Transit

Big Data Security Challenges and Solution of Distributed Computing in Hadoop Environment: A Security Framework

2020 ◽  
Vol 13 (4) ◽  
pp. 790-797
Author(s):  
Gurjit Singh Bhathal ◽  
Amardeep Singh Dhiman
Keyword(s):  
Big Data ◽  
Data Security ◽  
Data Sets ◽  
Security Framework ◽  
Hadoop Distributed File System ◽  
Current Scenario ◽  
Hadoop Cluster ◽  
Ciphertext Policy ◽  
In Transit ◽  
Hadoop Framework

Background: In current scenario of internet, large amounts of data are generated and processed. Hadoop framework is widely used to store and process big data in a highly distributed manner. It is argued that Hadoop Framework is not mature enough to deal with the current cyberattacks on the data. Objective: The main objective of the proposed work is to provide a complete security approach comprising of authorisation and authentication for the user and the Hadoop cluster nodes and to secure the data at rest as well as in transit. Methods: The proposed algorithm uses Kerberos network authentication protocol for authorisation and authentication and to validate the users and the cluster nodes. The Ciphertext-Policy Attribute- Based Encryption (CP-ABE) is used for data at rest and data in transit. User encrypts the file with their own set of attributes and stores on Hadoop Distributed File System. Only intended users can decrypt that file with matching parameters. Results: The proposed algorithm was implemented with data sets of different sizes. The data was processed with and without encryption. The results show little difference in processing time. The performance was affected in range of 0.8% to 3.1%, which includes impact of other factors also, like system configuration, the number of parallel jobs running and virtual environment. Conclusion: The solutions available for handling the big data security problems faced in Hadoop framework are inefficient or incomplete. A complete security framework is proposed for Hadoop Environment. The solution is experimentally proven to have little effect on the performance of the system for datasets of different sizes.

scholarly journals Numerical algorithms for high-performance computational science

2020 ◽  
Vol 378 (2166) ◽  
pp. 20190066 ◽  
Author(s):  
Jack Dongarra ◽  
Laura Grigori ◽  
Nicholas J. Higham
Keyword(s):  
High Performance ◽  
Numerical Algorithms ◽  
Computational Science ◽  
Floating Point ◽  
Important Criterion ◽  
Data Movement ◽  
Floating Point Arithmetic ◽  
High Performance Computers ◽  
Point Arithmetic ◽  
Speed And Accuracy

A number of features of today’s high-performance computers make it challenging to exploit these machines fully for computational science. These include increasing core counts but stagnant clock frequencies; the high cost of data movement; use of accelerators (GPUs, FPGAs, coprocessors), making architectures increasingly heterogeneous; and multi- ple precisions of floating-point arithmetic, including half-precision. Moreover, as well as maximizing speed and accuracy, minimizing energy consumption is an important criterion. New generations of algorithms are needed to tackle these challenges. We discuss some approaches that we can take to develop numerical algorithms for high-performance computational science, with a view to exploiting the next generation of supercomputers. This article is part of a discussion meeting issue ‘Numerical algorithms for high-performance computational science’.

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