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PPT : BEOWULF Cluster Seminar with Free Download


Published on April 15, 2016

Abstract

Slide 1 :

WELCOME TO THE SEMINAR

ON

BEOWULF Cluster

Slide 2 :

Introduction

==> The recent advances in high-speed networks and improved microprocessor performance are making clusters or networks of workstations an appealing vehicle for cost effective parallel computing.

==> Clusters built using commodity hardware and software components are playing a major role in redefining the concept of supercomputing’’

==> A cluster is a type of parallel or distributed processing system, which consists of a collection of interconnected stand-alone computers cooperatively working together as a single, integrated resource

==> This cluster of computers shares common network characteristics like the same namespace and it is available to other computers on the network as a single resource

Slide 3 :

Giganet

==> Giganet is the first vendor of Virtual Interface (VI) architecture cards for the Linux platform, in their cLAN cards and switches.

==> The VI architecture is a platform-neutral software and hardware system that Intel has been promoting to create clusters.

==> It uses its own network communications protocol rather than IP to exchange data directly between the servers, and it is not intended to be a WAN routable system.

==> The future of VI now lies in the ongoing work of the System I/O Group, which in itself is a merger of the Next-Generation I/O group led by Intel, and the Future I/O Group led by IBM and Compaq

Slide 4 :

Close Clusters

==> Figure

Slide 5 :

IEEE SCI

==> The IEEE standard SCI has even lower latencies (under 2.5 microseconds), and it can run at 400 MB per second (3.2 Gbps) in each direction.

==> That makes it faster to communicate between the nodes on a larger scale.

==> Even more useful is a torus topology network, with many rings between the nodes.

==> A two-dimensional torus can be pictured as a grid of n by m nodes with a ring network at every row and every column. A three-dimensional torus is similar, with a 3D cubic grid of nodes that also has rings at every level.

Slide 6 :

Security Considerations

==> Combining cluster resources on different locations, so that users from various departments would be able to take advantage of available computational nodes, however, is possible.

==> Theoretically, merging clusters is not only desirable but also advantageous, in the sense that different clusters are not localized at one place but are, rather, centralized.

==> But in order to merge clusters, all the machines would have to be on a public network instead of a private one, because every single node on every cluster needs to be directly accessible from the others

Slide 7 :

Open Clusters

==> Figure

Slide 8 :

PETSc

==> PETSc is intended for use in large-scale application projects, and several ongoing computational science projects are built around the PETSc libraries.

==> With strict attention to component interoperability, PETSc facilitates the integration of independently developed application modules, which often most naturally employ different coding styles and data structures

==> PETSc includes an expanding suite of parallel linear and nonlinear equation solvers that are easily used in application codes written in C, C++, and Fortran

Slide 9 :

PLAPACK

==> PLAPACK is an MPI-based Parallel Linear Algebra Package that provides an infrastructure for building parallel dense linear algebra libraries. PLAPACK provides 3 unique features.

==> Physically based matrix distribution

==> API to query matrices and vectors

==> Programming interface that allows object oriented programming

Slide 10 :

Conclusion

==> Beowulf systems are also muscling their way into the corporate world.

==> Major computer vendors are now selling clusters to businesses with large computational needs.

==> IBM, for instance, is building a cluster of 1,250 servers for NuTec Sciences, a biotechnology firm that plans to use the system to identify disease-causing genes.

==> An example is SETI@home, a project launched by researchers at the University of California at Berkeley who are analyzing deep-space radio signals for signs of intelligent life

Slide 11 :

References

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