Experience of introducing e-infrastructure for laser performance analysis

Experience of introducing e-infrastructure for laser

performance analysis

Lakshmi Sastry, Srikanth Nagella, Richard Henwood, Victoria Marshall and Brian

Matthews

Introduction to CLF

Target Area

Users visiting CLF bring their own diagnostics.

They still need to exchange information with the CLF team:1.Request a ‘shot’ of a given power2.Discover what CLF delivered

CLF workflow

Users

CLF staff

The laser

CLF/e-Science ImpactCLF: improved workflow:

-> less effort delivering service

CLF/e-Science ImpactCLF: improved workflow:

-> less effort delivering service -> more effort to do Science -> more Nature covers!

CLF/e-Science ImpactCLF: improved workflow:

-> less effort delivering service -> more effort to do Science -> more Nature covers!

e-Science: CLF data service:-> enabling more CLF Science

CLF/e-Science ImpactCLF: improved workflow:

-> less effort delivering service -> more effort to do Science -> more Nature covers!

e-Science: CLF data service:-> enabling more CLF Science

but also...-> eSc add value to User data-> more Nature covers!

CLF workflow

Users

CLF staff

The laser

First, add value for CLFFunctional requirements• 1000 diagnostic channels• Data bursts 20 seconds apart• 3 data types: 0d, 1d, 2d• Virtual channels• NeXus data format!• Stand-alone client• Flexible addition of new channels• Analysis capabilities of the client• Offsite access• Secure data collection for target area• Generalise to Vulcan

Production system (Pipeline)

Production system (Pipeline)

The Good• Pipeline handles real data bursts• Stand-alone client provides advanced analysis

The bad• Quality of service

– No monitoring– No-one wants to Sys-admin

• Quality of protection– Host and firewall are the same machine– No access control

• Scalability– Increase burst rate?

DB Schema issues

• Adding new channels requires a new _column_ on our DB table!

• Eg Tracetable <50% useful data

DB Schema issues

• Adding new channels requires a new _column_ on our DB table

• Eg Tracetable <50% useful data

• The Ugly

Phase II – a SOA

Managing risksQ: Will HTTP be fast enough? A:

Project Scott

Instrumenting for e-Science

Beyond thumb drive Sharing

Pre-Conditions• Compelling service offering• CLF are enthusiastic• Funders data policy

?

Instrumenting for e-Science:

Sharing dataThe carrot• Governance

Instrumenting for e-Science:

Sharing dataMore carrots• Convenience• Social data• Maximising

value of your work

The carrot• Governance

Conclusions

•Unique problem domain•MVC and SOA approach in phase 2•Detailed benchmarking phase•Data governance is an important value-add•Great opportunity to do novel e-Science