UK: Research Fellow in School of Computing
Closing Date: 5-09-2005
Further details:
Self-Adapting Software for Grid-Based Numerical Simulation
The post is available for a fixed term of three years to work on an EPSRC grantentitled "Self-Adapting Software for Grid-Based Numerical Simulation"recently awarded to Professor Peter Jimack as part of the EPSRC's ComputerScience for e-Science call. You will be working in the Scientific Computinggroup within the School of Computing at Leeds, a group that has a record of internationally-leadingresearch in parallel numerical algorithms. You would also be collaboratingclosely with the Informatics Architectures group in the School of Computing at Leeds who lead our research in Grid Computing.
Research IA (£19,460 - 29,128 p.a.) depending upon experience
The University is introducing a new reward framework which willfacilitate the recruitment, retention and motivation of world class staff.
Information about the School of Computing can be obtained from http://www.comp.leeds.ac.uk
Informal enquiries should be made to Prof. Peter Jimack, pkj@comp.leeds.ac.ukhttp://www.comp.leeds.ac.uk/pkjtel +44 (0) 113 343 5464.
Application packs from Irene Rudling tel 0113 343 35480 email i.rudling@leeds.ac.uk
Job ref 210554 Closing date 5 September 2005
Background
This project is concerned with the effective utilisation of Grid computingwithin one of the core components of e-Science: that of numerical simulation.In particular it focuses on developing and understanding fundamental techniquesthat will allow numerical applications to automatically adapt to their context.In order to ensure that the research remains focused we propose to consider oneparticular, but extremely important, class of numerical techniques based uponfinite difference (FD) and finite element (FE) solution of partial differentialequations (PDEs). Furthermore, we will specifically target the use of the mostmodern of sparse algebraic solution algorithms based upon multigrid and relatedmethods.
Computational Grids should enable the effective use of geographicallydistributed resources by distributed teams of researchers in a transparent andseamless manner. Their potential has already been successfully demonstratedacross a very wide range of scientific applications involving distributed dataanalysis, remote visualisation and large-scale computation. It is the latteraspect of Grid computing and e-Science that is to be addressed by this project.In particular it will focus on the development of new techniques and algorithmsto allow such e-Science applications to access the wide variety ofheterogeneous compute resources potentially available on a Grid in a mannerthat combines maximising the efficiency of their utilisation with maintainingfull transparency for the scientific users. There are many potential techniquesand parameter choices associated with the parallel implementation of numericalsoftware for PDEs and this project will focus on better understanding how suchsoftware can automatically and intelligently adapt to make the best possibleuse of available resources.
Job summary
This proposal is funded as part of the EPSRC's second call for proposals forResearch in the Computer Science Challenges to Emerge from e-Science. The keyscientific issues to be addressed by this project relate to the development oftechniques and algorithms to produce automatically adapting software forparallel and distributed computing on computational Grids. Amongst others, thiswill require the development of: dynamic load-balancing procedures that areable to respond to observed behaviour on a given computational node; differentpartitioning and parallelisation techniques that are best suited to differentarchitectural characteristics; reliable computational models, whose parametervalues may be easily established at run time, in order to predict the mostefficient execution format for the hardware encountered, and; novel algorithmsfor dealing efficiently with the high latency issues arising when simulationsare undertaken across more than one Grid resource. The specific projectobjectives are as follows.
· To understand the computation, communication and memory access patterns of arange of common parallel FD and FE software when executed across a variety ofarchitectures on a computational Grid.
· To develop techniques and algorithms that will allow such software toautomatically adapt to a given architecture so as to improve the computationalperformance on that architecture, whether it be homogeneous or heterogeneous.
· To allow such software to execute on a single problem across more than oneGrid node in a manner that automatically adapts the algorithm and itsassociated parameters to the available computational and network resources inorder to optimise performance.
· To ensure that execution models can be created in order to allow reliablepredictions to be made as to the performance of these FD and FE algorithms, soas to allow the optimal scheduling of multiple runs across different data sets,and to automatically adapt the schedules in a dynamic manner during execution.
· To develop job description metrics to allow the best resource allocation tobe achieved for a given job and to define a scheme to record details of theprovided resources, and the algorithmic and parameter choices made, in order toprovide records of provenance for data produced.
· To demonstrate the performance of the novel algorithms developed in thisproject on realistic computational Grids such as the White Rose Grid (WRG).
You will be responsible to the project investigator, and will be working toachieve the objectives set out above. You will be expected to work closely withcolleagues in the Scientific Computing and Informatics Architectures groups.
Person Specification
It is essential that you possess a PhD in a relevant subject, or have theequivalent experience. You should also possess the following skills andexperience.
Essential:
· Expertise in some aspects of scientific computing and numerical algorithms.
· Excellent programming skills.
· The ability to write and present the results of research.
· Intellectual maturity and the willingness and ability to interact withexperts across traditional domain boundaries.
· An ability to work independently but with appropriate guidance and workingtowards agreed goals.
Desirable:
· Experience with parallel numerical algorithms and programming.
· Experience with grid applications programming.
· Good knowledge of some or all of the numerical methods that underpin theproject (finite difference schemes, finite element methods, multigrid methodsand domain decomposition methods).
How to apply:
Applications should include the following:-
· Acompleted application form
· EqualOpportunities Monitoring Form . Please return the Form in a separateenvelope marked 'EOs Monitoring'.
How to Apply
Applications should include the following:-
· A completed application form
· A Curriculum Vitae/information requested on page 2 of the form
· Equal Opportunities Monitoring Form (Enclosed). Please return the Form in aseparate envelope (enclosed) marked 'EOs Monitoring'.
Replies will be treated in complete confidence.
Completed applications should be returned to Professor Peter Jimack, School of Computing, University of Leeds, Leeds, LS2 9JT quoting job ref 210554 not later than 5 September 2005
If you are selected for interview you can expect to hear from the Universitynot later than 4 weeks after the closing date. If you are not selected forinterview the University will not contact you again.
A Criminal Records Disclosure is not required for this position.
Disabled Applicants
The post is located School of Computing. Disabled applicants wishing to review access to thebuilding are invited to contact the department direct. Additional informationmay be sought from the Team Co-ordinator in Disability Services, emaildisability@leeds.ac.uk or tel 0113 343 3927
Disabled applicants are not obliged to inform employers of their disability butwill still be covered by the Disability Discrimination Act once theirdisability becomes known.
Data Protection
The information you provide in your application will be used to consider yoursuitability for the post for which you have applied. If your application is notsuccessful the information will be disposed of confidentially within 8 months.If your application is successful and you are appointed, your information andfuture data will be processed in accordance with the University's DataProtection Code of Practice. A copy of this code can be obtained from eitherthe University's Human Resources Department or by visiting http://www.leeds.ac.uk/hr/policy/index.htm
Health and Safety Responsibilities
You are required to adhere and comply to the provisions of the Health andSafety at Work Act, related Regulations and in accordance to the University'sPolicy on Health and Safety which can be accessed via http://www.leeds.ac.uk/safety/usp/uspindex.htm
In addition you are also required to cooperate with regard to theimplementation of Health and Safety arrangements and should not interfere withor misuse anything provided in the interest of Health, Safety and Welfare atWork.
Research IA (£19,460 - 29,128 p.a.) depending upon experience
The University is introducing a new reward framework which willfacilitate the recruitment, retention and motivation of world class staff.
Information about the School of Computing can be obtained from http://www.comp.leeds.ac.uk
Informal enquiries should be made to Prof. Peter Jimack, pkj@comp.leeds.ac.ukhttp://www.comp.leeds.ac.uk/pkjtel +44 (0) 113 343 5464.
Application packs from Irene Rudling tel 0113 343 35480 email i.rudling@leeds.ac.uk
Job ref 210554 Closing date 5 September 2005
Background
This project is concerned with the effective utilisation of Grid computingwithin one of the core components of e-Science: that of numerical simulation.In particular it focuses on developing and understanding fundamental techniquesthat will allow numerical applications to automatically adapt to their context.In order to ensure that the research remains focused we propose to consider oneparticular, but extremely important, class of numerical techniques based uponfinite difference (FD) and finite element (FE) solution of partial differentialequations (PDEs). Furthermore, we will specifically target the use of the mostmodern of sparse algebraic solution algorithms based upon multigrid and relatedmethods.
Computational Grids should enable the effective use of geographicallydistributed resources by distributed teams of researchers in a transparent andseamless manner. Their potential has already been successfully demonstratedacross a very wide range of scientific applications involving distributed dataanalysis, remote visualisation and large-scale computation. It is the latteraspect of Grid computing and e-Science that is to be addressed by this project.In particular it will focus on the development of new techniques and algorithmsto allow such e-Science applications to access the wide variety ofheterogeneous compute resources potentially available on a Grid in a mannerthat combines maximising the efficiency of their utilisation with maintainingfull transparency for the scientific users. There are many potential techniquesand parameter choices associated with the parallel implementation of numericalsoftware for PDEs and this project will focus on better understanding how suchsoftware can automatically and intelligently adapt to make the best possibleuse of available resources.
Job summary
This proposal is funded as part of the EPSRC's second call for proposals forResearch in the Computer Science Challenges to Emerge from e-Science. The keyscientific issues to be addressed by this project relate to the development oftechniques and algorithms to produce automatically adapting software forparallel and distributed computing on computational Grids. Amongst others, thiswill require the development of: dynamic load-balancing procedures that areable to respond to observed behaviour on a given computational node; differentpartitioning and parallelisation techniques that are best suited to differentarchitectural characteristics; reliable computational models, whose parametervalues may be easily established at run time, in order to predict the mostefficient execution format for the hardware encountered, and; novel algorithmsfor dealing efficiently with the high latency issues arising when simulationsare undertaken across more than one Grid resource. The specific projectobjectives are as follows.
· To understand the computation, communication and memory access patterns of arange of common parallel FD and FE software when executed across a variety ofarchitectures on a computational Grid.
· To develop techniques and algorithms that will allow such software toautomatically adapt to a given architecture so as to improve the computationalperformance on that architecture, whether it be homogeneous or heterogeneous.
· To allow such software to execute on a single problem across more than oneGrid node in a manner that automatically adapts the algorithm and itsassociated parameters to the available computational and network resources inorder to optimise performance.
· To ensure that execution models can be created in order to allow reliablepredictions to be made as to the performance of these FD and FE algorithms, soas to allow the optimal scheduling of multiple runs across different data sets,and to automatically adapt the schedules in a dynamic manner during execution.
· To develop job description metrics to allow the best resource allocation tobe achieved for a given job and to define a scheme to record details of theprovided resources, and the algorithmic and parameter choices made, in order toprovide records of provenance for data produced.
· To demonstrate the performance of the novel algorithms developed in thisproject on realistic computational Grids such as the White Rose Grid (WRG).
You will be responsible to the project investigator, and will be working toachieve the objectives set out above. You will be expected to work closely withcolleagues in the Scientific Computing and Informatics Architectures groups.
Person Specification
It is essential that you possess a PhD in a relevant subject, or have theequivalent experience. You should also possess the following skills andexperience.
Essential:
· Expertise in some aspects of scientific computing and numerical algorithms.
· Excellent programming skills.
· The ability to write and present the results of research.
· Intellectual maturity and the willingness and ability to interact withexperts across traditional domain boundaries.
· An ability to work independently but with appropriate guidance and workingtowards agreed goals.
Desirable:
· Experience with parallel numerical algorithms and programming.
· Experience with grid applications programming.
· Good knowledge of some or all of the numerical methods that underpin theproject (finite difference schemes, finite element methods, multigrid methodsand domain decomposition methods).
How to apply:
Applications should include the following:-
· Acompleted application form
· EqualOpportunities Monitoring Form . Please return the Form in a separateenvelope marked 'EOs Monitoring'.
How to Apply
Applications should include the following:-
· A completed application form
· A Curriculum Vitae/information requested on page 2 of the form
· Equal Opportunities Monitoring Form (Enclosed). Please return the Form in aseparate envelope (enclosed) marked 'EOs Monitoring'.
Replies will be treated in complete confidence.
Completed applications should be returned to Professor Peter Jimack, School of Computing, University of Leeds, Leeds, LS2 9JT quoting job ref 210554 not later than 5 September 2005
If you are selected for interview you can expect to hear from the Universitynot later than 4 weeks after the closing date. If you are not selected forinterview the University will not contact you again.
A Criminal Records Disclosure is not required for this position.
Disabled Applicants
The post is located School of Computing. Disabled applicants wishing to review access to thebuilding are invited to contact the department direct. Additional informationmay be sought from the Team Co-ordinator in Disability Services, emaildisability@leeds.ac.uk or tel 0113 343 3927
Disabled applicants are not obliged to inform employers of their disability butwill still be covered by the Disability Discrimination Act once theirdisability becomes known.
Data Protection
The information you provide in your application will be used to consider yoursuitability for the post for which you have applied. If your application is notsuccessful the information will be disposed of confidentially within 8 months.If your application is successful and you are appointed, your information andfuture data will be processed in accordance with the University's DataProtection Code of Practice. A copy of this code can be obtained from eitherthe University's Human Resources Department or by visiting http://www.leeds.ac.uk/hr/policy/index.htm
Health and Safety Responsibilities
You are required to adhere and comply to the provisions of the Health andSafety at Work Act, related Regulations and in accordance to the University'sPolicy on Health and Safety which can be accessed via http://www.leeds.ac.uk/safety/usp/uspindex.htm
In addition you are also required to cooperate with regard to theimplementation of Health and Safety arrangements and should not interfere withor misuse anything provided in the interest of Health, Safety and Welfare atWork.
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