93,130 research outputs found
RELEASE: A High-level Paradigm for Reliable Large-scale Server Software
Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the rst six months. The project aim is to scale the Erlang's radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the e ectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene
Storage Solutions for Big Data Systems: A Qualitative Study and Comparison
Big data systems development is full of challenges in view of the variety of
application areas and domains that this technology promises to serve.
Typically, fundamental design decisions involved in big data systems design
include choosing appropriate storage and computing infrastructures. In this age
of heterogeneous systems that integrate different technologies for optimized
solution to a specific real world problem, big data system are not an exception
to any such rule. As far as the storage aspect of any big data system is
concerned, the primary facet in this regard is a storage infrastructure and
NoSQL seems to be the right technology that fulfills its requirements. However,
every big data application has variable data characteristics and thus, the
corresponding data fits into a different data model. This paper presents
feature and use case analysis and comparison of the four main data models
namely document oriented, key value, graph and wide column. Moreover, a feature
analysis of 80 NoSQL solutions has been provided, elaborating on the criteria
and points that a developer must consider while making a possible choice.
Typically, big data storage needs to communicate with the execution engine and
other processing and visualization technologies to create a comprehensive
solution. This brings forth second facet of big data storage, big data file
formats, into picture. The second half of the research paper compares the
advantages, shortcomings and possible use cases of available big data file
formats for Hadoop, which is the foundation for most big data computing
technologies. Decentralized storage and blockchain are seen as the next
generation of big data storage and its challenges and future prospects have
also been discussed
Overview of Swallow --- A Scalable 480-core System for Investigating the Performance and Energy Efficiency of Many-core Applications and Operating Systems
We present Swallow, a scalable many-core architecture, with a current
configuration of 480 x 32-bit processors.
Swallow is an open-source architecture, designed from the ground up to
deliver scalable increases in usable computational power to allow
experimentation with many-core applications and the operating systems that
support them.
Scalability is enabled by the creation of a tile-able system with a
low-latency interconnect, featuring an attractive communication-to-computation
ratio and the use of a distributed memory configuration.
We analyse the energy and computational and communication performances of
Swallow. The system provides 240GIPS with each core consuming 71--193mW,
dependent on workload. Power consumption per instruction is lower than almost
all systems of comparable scale.
We also show how the use of a distributed operating system (nOS) allows the
easy creation of scalable software to exploit Swallow's potential. Finally, we
show two use case studies: modelling neurons and the overlay of shared memory
on a distributed memory system.Comment: An open source release of the Swallow system design and code will
follow and references to these will be added at a later dat
RELEASE: A High-level Paradigm for Reliable Large-scale Server Software
Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the first six months. The project aim is to scale the Erlang’s radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the effectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene
Taxonomy of P2P Applications
Peer-to-peer (p2p) networks have gained immense popularity in recent years and the number of services they provide continuously rises. Where p2p-networks were formerly known as file-sharing networks, p2p is now also used for services like VoIP and IPTV. With so many different p2p applications and services the need for a taxonomy framework rises. This paper describes the available p2p applications grouped by the services they provide. A taxonomy framework is proposed to classify old and recent p2p applications based on their characteristics
Scalable Reliable SD Erlang Design
This technical report presents the design of Scalable Distributed (SD) Erlang: a set of language-level changes that aims to enable Distributed Erlang to scale for server applications on commodity hardware with at most 100,000 cores. We cover a number of aspects, specifically anticipated architecture, anticipated failures, scalable data structures, and scalable computation. Other two components that guided us in the design of SD Erlang are design principles and typical Erlang applications. The design principles summarise the type of modifications we aim to allow Erlang scalability. Erlang exemplars help us to identify the main Erlang scalability issues and hypothetically validate the SD Erlang design
Provenance-based trust for grid computing: Position Paper
Current evolutions of Internet technology such as Web Services, ebXML, peer-to-peer and Grid computing all point to the development of large-scale open networks of diverse computing systems interacting with one another to perform tasks. Grid systems (and Web Services) are exemplary in this respect and are perhaps some of the first large-scale open computing systems to see widespread use - making them an important testing ground for problems in trust management which are likely to arise. From this perspective, today's grid architectures suffer from limitations, such as lack of a mechanism to trace results and lack of infrastructure to build up trust networks. These are important concerns in open grids, in which "community resources" are owned and managed by multiple stakeholders, and are dynamically organised in virtual organisations. Provenance enables users to trace how a particular result has been arrived at by identifying the individual services and the aggregation of services that produced such a particular output. Against this background, we present a research agenda to design, conceive and implement an industrial-strength open provenance architecture for grid systems. We motivate its use with three complex grid applications, namely aerospace engineering, organ transplant management and bioinformatics. Industrial-strength provenance support includes a scalable and secure architecture, an open proposal for standardising the protocols and data structures, a set of tools for configuring and using the provenance architecture, an open source reference implementation, and a deployment and validation in industrial context. The provision of such facilities will enrich grid capabilities by including new functionalities required for solving complex problems such as provenance data to provide complete audit trails of process execution and third-party analysis and auditing. As a result, we anticipate that a larger uptake of grid technology is likely to occur, since unprecedented possibilities will be offered to users and will give them a competitive edge
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