89,781 research outputs found
A Low Cost Two-Tier Architecture Model For High Availability Clusters Application Load Balancing
This article proposes a design and implementation of a low cost two-tier
architecture model for high availability cluster combined with load-balancing
and shared storage technology to achieve desired scale of three-tier
architecture for application load balancing e.g. web servers. The research work
proposes a design that physically omits Network File System (NFS) server nodes
and implements NFS server functionalities within the cluster nodes, through Red
Hat Cluster Suite (RHCS) with High Availability (HA) proxy load balancing
technologies. In order to achieve a low-cost implementation in terms of
investment in hardware and computing solutions, the proposed architecture will
be beneficial. This system intends to provide steady service despite any system
components fails due to uncertainly such as network system, storage and
applications.Comment: Load balancing, high availability cluster, web server cluster
MOLNs: A cloud platform for interactive, reproducible and scalable spatial stochastic computational experiments in systems biology using PyURDME
Computational experiments using spatial stochastic simulations have led to
important new biological insights, but they require specialized tools, a
complex software stack, as well as large and scalable compute and data analysis
resources due to the large computational cost associated with Monte Carlo
computational workflows. The complexity of setting up and managing a
large-scale distributed computation environment to support productive and
reproducible modeling can be prohibitive for practitioners in systems biology.
This results in a barrier to the adoption of spatial stochastic simulation
tools, effectively limiting the type of biological questions addressed by
quantitative modeling. In this paper, we present PyURDME, a new, user-friendly
spatial modeling and simulation package, and MOLNs, a cloud computing appliance
for distributed simulation of stochastic reaction-diffusion models. MOLNs is
based on IPython and provides an interactive programming platform for
development of sharable and reproducible distributed parallel computational
experiments
HP-CERTI: Towards a high performance, high availability open source RTI for composable simulations (04F-SIW-014)
Composing simulations of complex systems from already existing simulation components remains a challenging issue. Motivations for composable simulation include generation of a given federation driven by operational requirements provided "on the fly". The High Level Architecture, initially developed for designing fully distributed simulations, can be considered as an interoperability standard for composing simulations from existing components. Requirements for constructing such complex simulations are quite different from those discussed for distributed simulations. Although interoperability and reusability remain essential, both high performance and availability have also to be considered to fulfill the requirements of the end user. ONERA is currently designing a High Performance / High Availability HLA Run-time Infrastructure from its open source implementation of HLA 1.3 specifications. HP-CERTI is a software package including two main components: the first one, SHM-CERTI, provides an optimized version of CERTI based on a shared memory communication scheme; the second one, Kerrighed-CERTI, allows the deployment of CERTI through the control of the Kerrighed Single System Image operating system for clusters, currently designed by IRISA. This paper describes the design of both high performance and availability Runtime Infrastructures, focusing on the architecture of SHM-CERTI. This work is carried out in the context of the COCA (High Performance Distributed Simulation and Models Reuse) Project, sponsored by the DGA/STTC (Délégation Générale pour l'Armement/Service des Stratégies Techniques et des Technologies Communes) of the French Ministry of Defense
Libra: An Economy driven Job Scheduling System for Clusters
Clusters of computers have emerged as mainstream parallel and distributed
platforms for high-performance, high-throughput and high-availability
computing. To enable effective resource management on clusters, numerous
cluster managements systems and schedulers have been designed. However, their
focus has essentially been on maximizing CPU performance, but not on improving
the value of utility delivered to the user and quality of services. This paper
presents a new computational economy driven scheduling system called Libra,
which has been designed to support allocation of resources based on the users?
quality of service (QoS) requirements. It is intended to work as an add-on to
the existing queuing and resource management system. The first version has been
implemented as a plugin scheduler to the PBS (Portable Batch System) system.
The scheduler offers market-based economy driven service for managing batch
jobs on clusters by scheduling CPU time according to user utility as determined
by their budget and deadline rather than system performance considerations. The
Libra scheduler ensures that both these constraints are met within an O(n)
run-time. The Libra scheduler has been simulated using the GridSim toolkit to
carry out a detailed performance analysis. Results show that the deadline and
budget based proportional resource allocation strategy improves the utility of
the system and user satisfaction as compared to system-centric scheduling
strategies.Comment: 13 page
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