Using an interactive parallelisation toolkit to parallelise an ocean modelling code

This paper describes an interactive parallelisation toolkit that can be used to generate parallel code suitable for either a distributed memory system (using message passing) or a shared memory system (using OpenMP). This study focuses on how the toolkit is used to parallelise a complex heterogeneous ocean modelling code within a few hours for use on a shared memory parallel system. The generated parallel code is essentially the serial code with OpenMP directives added to express the parallelism. The results show that substantial gains in performance can be achieved over the single thread version with very little effort.

Generating OpenMP code using an interactive parallelization environment

Code parallelization using OpenMP for shared memory systems is relatively easier than using message passing for distributed memory systems. Despite this, it is still a challenge to use OpenMP to parallelize application codes in a way that yields effective scalable performance when executed on a shared memory parallel system. We describe an environment that will assist the programmer in the various tasks of code parallelization and this is achieved in a greatly reduced time frame and level of skill required. The parallelization environment includes a number of tools that address the main tasks of parallelism detection, OpenMP source code generation, debugging and optimization. These tools include a high quality, fully interprocedural dependence analysis with user interaction capabilities to facilitate the generation of efficient parallel code, an automatic relative debugging tool to identify erroneous user decisions in that interaction and also performance profiling to identify bottlenecks. Finally, experiences of parallelizing some NASA application codes are presented to illustrate some of the benefits of using the evolving environment.

Using an interactive software environment for the parallelization of real-world scientific applications

The parallelization of real-world compute intensive Fortran application codes is generally not a trivial task. If the time to complete the parallelization is to be significantly reduced then an environment is needed that will assist the programmer in the various tasks of code parallelization. In this paper the authors present a code parallelization environment where a number of tools that address the main tasks such as code parallelization, debugging and optimization are available. The ParaWise and CAPO parallelization tools are discussed which enable the near automatic parallelization of real-world scientific application codes for shared and distributed memory-based parallel systems. As user involvement in the parallelization process can introduce errors, a relative debugging tool (P2d2) is also available and can be used to perform nearly automatic relative debugging of a program that has been parallelized using the tools. A high quality interprocedural dependence analysis as well as user-tool interaction are also highlighted and are vital to the generation of efficient parallel code and in the optimization of the backtracking and speculation process used in relative debugging. Results of benchmark and real-world application codes parallelized are presented and show the benefits of using the environment

Numerical and experimental studies of a substructural identification strategy

For structural health monitoring it is impractical to identify a large structure with complete measurement due to limited number of sensors and difficulty in field instrumentation. Furthermore, it is not desirable to identify a large number of unknown parameters in a full system because of numerical difficulty in convergence. A novel substructural strategy was presented for identification of stiffness matrices and damage assessment with incomplete measurement. The substructural approach was employed to identify large systems in a divide-and-conquer manner. In addition, the concept of model condensation was invoked to avoid the need for complete measurement, and the recovery process to obtain the full set of parameters was formulated. The efficiency of the proposed method is demonstrated numerically through multi-storey shear buildings subjected to random force. A fairly large structural system with 50 DOFs was identified with good results, taking into consideration the effects of noisy signals and the limited number of sensors. Two variations of the method were applied, depending on whether the sensor could be repositioned. The proposed strategy was further substantiated experimentally using an eight-storey steel plane frame model subjected to shaker and impulse hammer excitations. Both numerical and experimental results have shown that the proposed substructural strategy gave reasonably accurate identification in terms of locating and quantifying structural damage.

The benefits of a health impact assessment in relation to fuel poverty: assessing Luton's affordable warmth strategy and the need for a national strategy

The links between fuel poverty and poor health are well documented, yet there is no statutory requirement on local authorities to develop fuel poverty strategies, which tend to be patchy nationally and differ substantially in quality. Fuel poverty starts from the perspective of income, even though interventions can improve health. The current public health agenda calls for more partnership-based, cost-effective strategies based on sound evidence. Fuel poverty represents a key area where there is currently little local evidence quantifying and qualifying health gain arising from strategic interventions. As a result, this initial study sought to apply the principles of a health impact assessment to Luton’s Affordable Warmth Strategy, exploring the potential to identify health impact arising – as a baseline for future research – in the context of the public health agenda. A national strategy would help ensure the promotion of targeted fuel poverty strategies.

South East London Palliative and End of Life Care Education and Training Strategy: Meeting the Education and Training Needs of the Health & Social Care Workforce Involved in the Care of Patients and Carers at the End of Life.

EXECUTIVE SUMMARY Aims 1. The aims of this strategy are • to ensure that a full range of education and training related to the adult end of life care pathway is available across South East London to meet the needs of our health and social care workforce • to enable those responsible for end of life care education and training commissioning to procure comprehensively from a full range of education providers in a systematic and strategic manner. Background 2. The work that underpins this strategy was begun by the South East London Cancer Network via its Palliative and End of Life Care Coordinating Group and then developed by way of the Marie Curie Delivering Choice Programme’s Education and Training work stream.