Creating a national lab shared storage infrastructure

2002 ◽  
Author(s):  
W. Karpoff
Keyword(s):  
Shared Storage

Enhancing the use of Object Based Contents Addressable Storage

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Simab Hasan Rizvi
Keyword(s):  
File System ◽  
Application Performance ◽  
Shared Storage ◽  
Data Intensive ◽  
Network Bandwidth ◽  
Storage Performance ◽  
Efficient Management ◽  
Object Based ◽  
Data Volume ◽  
Potential Benefits

In Today's age of Tetra Scale computing, the application has become more data intensive than ever. The increased data volume from applications, in now tackling larger and larger problems, and has fuelled the need for efficient management of this data. In this paper, a technique called Content Addressable Storage or CAS, for managing large volume of data is evaluated. This evaluation focuses on the benefits and demerits of using CAS it focuses, i) improved application performance via lockless and lightweight synchronization ofaccess to shared storage data, ii) improved cache performance, iii) increase in storage capacity and, iv) increase network bandwidth. The presented design of a CAS-Based file store significantly improves the storage performance that provides lightweight lock less user defined consistency semantics. As a result, this file system shows a 28% increase in read bandwidth and 13% increase in write bandwidth, over a popular file system in common use. In this paper the potential benefits of using CAS for a virtual machine are estimated. The study also explains mobility application for active use and public deployment.

The Origins of the Village Revisited: From Nuclear to Extended Households

2002 ◽  
Vol 67 (3) ◽  
pp. 417-433 ◽  
Author(s):  
Kent V. Flannery
Keyword(s):  
Nuclear Family ◽  
Extended Family ◽  
Near East ◽  
Shared Storage ◽  
Nuclear Families ◽  
Second Stage ◽  
Third Stage ◽  
Two Stages ◽  
Extended Households ◽  
The Village

In Mesoamerica and the Near East, the emergence of the village seems to have involved two stages. In the first stage, individuals were distributed through a series of small circular-to-oval structures, accompanied by communal or “shared” storage features. In the second stage, nuclear families occupied substantial rectangular houses with private storage rooms. Over the last 30 years a wealth of data from the Near East, Egypt, the Trans-Caucasus, India, Africa, and the Southwest U.S. have enriched our understanding of this phenomenon. And in Mesoamerica and the Near East, evidence suggests that nuclear family households eventually gave way to a third stage, one featuring extended family households whose greater labor force made possible extensive multifaceted economies.

Heterogeneous-aware cache partitioning: Improving the fairness of shared storage cache

2014 ◽  
Vol 40 (10) ◽  
pp. 710-721
Author(s):  
Yong Li ◽  
Dan Feng ◽  
Zhan Shi
Keyword(s):  
Cache Partitioning ◽  
Shared Storage

scholarly journals REANA: A System for Reusable Research Data Analyses

2019 ◽  
Vol 214 ◽  
pp. 06034 ◽  
Author(s):  
Tibor Šimko ◽  
Lukas Heinrich ◽  
Harri Hirvonsalo ◽  
Dinos Kousidis ◽  
Diego Rodríguez
Keyword(s):  
Particle Physics ◽  
Research Data ◽  
Sufficient Information ◽  
Computing Environment ◽  
Shared Storage ◽  
Data Analyses ◽  
Scientific Disciplines ◽  
Computational Workflow ◽  
Scientific Results ◽  
Cloud Infrastructures

The revalidation, reinterpretation and reuse of research data analyses requires having access to the original computing environment, the experimental datasets, the analysis software, and the computational workflow steps which were used by researchers to produce the original scientific results in the first place. REANA (Reusable Analyses) is a nascent platform enabling researchers to structure their research data analyses in view of enabling future reuse. The analysis is described by means of a YAML file that captures sufficient information about the analysis assets, parameters and processes. The REANA platform consists of a set of micro-services allowing to launch and monitor container-based computational workflow jobs on the cloud. The REANA user interface and the command-line client enables researchers to easily rerun analysis workflows with new input parameters. The REANA platform aims at supporting several container technologies (Docker), workflow engines (CWL, Yadage), shared storage systems (Ceph, EOS) and compute cloud infrastructures (Ku-bernetes/OpenStack, HTCondor) used by the community. REANA was developed with the particle physics use case in mind and profits from synergies with general reusable research data analysis patterns in other scientific disciplines, such as bioinformatics and life sciences.

scholarly journals Typed dataspace actors

2020 ◽  
Vol 30 ◽  
Author(s):  
SAM CALDWELL ◽  
TONY GARNOCK-JONES ◽  
MATTHIAS FELLEISEN
Keyword(s):  
Design Patterns ◽  
Type System ◽  
Structural Type ◽  
Storage Facility ◽  
Tuple Space ◽  
Common Goal ◽  
Actor Model ◽  
Shared Storage ◽  
Erroneous Data ◽  
Rule Out

Absatract Actors collaborate via message exchanges to reach a common goal. Experience has shown, however, that pure message-based communication is limiting and forces developers to use design patterns. The recently introduced dataspace actor model borrows ideas from the tuple space realm. It offers a tightly controlled, shared storage facility for groups of actors. In this model, actors assert facts that they wish to share and interests in such assertions. The dataspace notifies interested parties of changes to the set of assertions that they are interested in. Although it is straightforward to add the dataspace model to untyped languages, adding a typed interface is both necessary and challenging. Without restrictions on exchanged data, a faulty actor may propagate erroneous data through a malformed assertion, causing an otherwise well-behaved actor to crash—violating the key principle of failure isolation. A properly designed type system can prevent this scenario and rule out other kinds of uncooperative actors. This paper presents the first structural type system for the dataspace model of actors; it does not address the question of behavioral types for assertion-oriented protocols.

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