Checkpoint and run-time adaptation with pluggable parallelisation

Enabling applications for computational Grids requires new approaches to develop applications that can effectively cope with resource volatility. Applications must be resilient to resource faults, adapting the behaviour to available resources. This paper describes an approach to application-level adaptation that efficiently supports application-level checkpointing. The key of this work is the concept of pluggable parallelisation, which localises parallelisation issues into multiple modules that can be (un)plugged to match resource availability. This paper shows how pluggable parallelisation can be extended to effectively support checkpointing and run-time adaptation. We present the developed pluggable mechanism that helps the programmer to include checkpointing in the base (sequential). Based on these mechanisms and on previous work on pluggable parallelisation, our approach is able to automatically add support for checkpointing in parallel execution environments. Moreover, applications can adapt from a sequential execution to a multi-cluster configuration. Adaptation can be performed by checkpointing the application and restarting on a different mode or can be performed during run-time. Pluggable parallelisation intrinsically promotes the separation of software functionality from fault-tolerance and adaptation issues facilitating their analysis and evolution. The work presented in this paper reinforces this idea by showing the feasibility of the approach and performance benefits that can be achieved.(undefined

AOmpLib: an aspect library for large-scale multi-core parallel programming

This paper introduces an aspect-oriented library aimed to support efficient execution of Java applications on multi-core systems. The library is coded in AspectJ and provides a set of parallel programming abstractions that mimics the OpenMP standard. The library supports the migration of sequential Java codes to multi-core machines with minor changes to the base code, intrinsically supports the sequential semantics of OpenMP and provides improved integration with object-oriented mechanisms. The aspect- oriented nature of library enables the encapsulation of parallelism-related code into well-defined modules. The approach makes the parallelisation and the maintenance of large-scale Java applications more manageable. Furthermore, the library can be used with plain Java annotations and can be easily extended with application- specific mechanisms in order to tune application performance. The library has a competitive performance, in comparison with traditional parallel programming in Java, and enhances programmability, since it allows an independent development of parallelism-related code.This work is funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within projects FCOMP-01-0124-FEDER- 011413 and FCOMP-01-0124-FEDER-010152

A highly scalable Met Office NERC Cloud model

Large Eddy Simulation is a critical modelling tool for scien- tists investigating atmospheric flows, turbulence and cloud microphysics. Within the UK, the principal LES model used by the atmospheric research community is the Met Office Large Eddy Model (LEM). The LEM was originally devel- oped in the late 1980s using computational techniques and assumptions of the time, which means that the it does not scale beyond 512 cores. In this paper we present the Met Office NERC Cloud model, MONC, which is a re-write of the existing LEM. We discuss the software engineering and architectural decisions made in order to develop a flexible, extensible model which the community can easily customise for their own needs. The scalability of MONC is evaluated, along with numerous additional customisations made to fur- ther improve performance at large core counts. The result of this work is a model which delivers to the community signifi- cant new scientific modelling capability that takes advantage of the current and future generation HPC machine

Aspect oriented pluggable support for parallel computing

In this paper, we present an approach to develop parallel applications based on aspect oriented programming. We propose a collection of aspects to implement group communication mechanisms on parallel applications. In our approach, parallelisation code is developed by composing the collection into the application core functionality. The approach requires fewer changes to sequential applications to parallelise the core functionality than current alternatives and yields more modular code. The paper presents the collection and shows how the aspects can be used to develop efficient parallel applicationsFundação para a Ciência e a Tecnologia (FCT) - PPC-VM (Portable Parallel Computing based on Virtual Machines) Project POSI/CHS/47158/2002; SOFTAS (POSI/EIA/60189/2004).Fundo Europeu de Desenvolvimento Regional (FEDER)

Aspect oriented parallel framework for java

This paper introduces aspect libraries, a unit of modularity in parallel programs with compositional properties. Aspects address the complexity of parallel programs by enabling the composition of (multi-ple) parallelism modules with a given (sequential) base program. This paper illustrates the introduction of parallelism using reusable parallel libraries, coded in AspectJ. These libraries provide performance comparable to traditional parallel programming techniques and enable the composition of multiple parallelism modules (e.g., shared memory with distributed memory) with a given base program.(undefined)info:eu-repo/semantics/publishedVersio

AOmpLib: An Aspect Library for Large-Scale Multi-Core Parallel Programming

Abstract-This paper introduces an aspect-oriented library aimed to support efficient execution of Java applications on multi-core systems. The library is coded in AspectJ and provides a set of parallel programming abstractions that mimics the OpenMP standard. The library supports the migration of sequential Java codes to multi-core machines with minor changes to the base code, intrinsically supports the sequential semantics of OpenMP and provides improved integration with object-oriented mechanisms. The aspectoriented nature of library enables the encapsulation of parallelism-related code into well-defined modules. The approach makes the parallelisation and the maintenance of large-scale Java applications more manageable. Furthermore, the library can be used with plain Java annotations and can be easily extended with applicationspecific mechanisms in order to tune application performance. The library has a competitive performance, in comparison with traditional parallel programming in Java, and enhances programmability, since it allows an independent development of parallelism-related code

Incrementally developing parallel applications with AspectJ

This paper presents a methodology to develop more modular parallel applications, based on aspect oriented programming. Traditional object oriented mechanisms implement application core functionality and parallelisation concerns are plugged by aspect oriented mechanisms. Parallelisation concerns are separated into four categories: functional or/and data partition, concurrency, distribution and optimisation. Modularising these categories into separate modules using aspect oriented programming enables (un)pluggability of parallelisation concerns. This approach leads to more incremental application development, easier debugging and increased reuse of core functionality and parallel code, when compared with traditional object oriented approaches. A detailed analysis of a simple parallel application - a prime number sieve - illustrates the methodology and shows how to accomplish these gains.Fundo Europeu de Desenvolvimento Regional (FEDER) - PPC-VM project POSI/CHS/47158/2002.Fundação para a Ciência e a Tecnologia (FCT) - PPC-VM project POSI/CHS/47158/2002

Architecture for Analysis of Streaming Data

While several attempts have been made to construct a scalable and flexible architecture for analysis of streaming data, no general model to tackle this task exists. Thus, our goal is to build a scalable and maintainable architecture for performing analytics on streaming data. To reach this goal, we introduce a 7-layered architecture consisting of microservices and publish-subscribe software. Our study shows that this architecture yields a good balance between scalability and maintainability due to high cohesion and low coupling of the solution, as well as asynchronous communication between the layers. This architecture can help practitioners to improve their analytic solutions. It is also of interest to academics, as it is a building block for a general architecture for processing streaming data

AspectGrid: aspect-oriented fault-tolerance in grid platforms

Migrating traditional scientific applications to computational Grids requires programming tools that can help programmers update application behaviour to this kind of platforms. Computational Grids are particularly suited for long running scientific applications, but they are also more prone to faults than desktop machines. The AspectGrid framework aims to develop methodologies and tools that can help Grid-enable scientific applications, particularly focusing on techniques based on aspect-oriented programming. In this paper we present the aspect-oriented approach taken in the AspectGrid framework to address faults in computational Grids. In the proposed approach, scientific applications are enhanced with fault-tolerance capability by plugging additional modules. The proposed technique is portable across operating systems and minimises the changes required to base applications