Speaker
Report on the experience (or the proposed activity). It would be very important to mention key services which are essential for the success of your activity on the EGEE infrastructure.
In order for In Silico Oncology to be efficiently transferred to
the EGEE
infrastructure, certain aspects need to be addressed regarding
its adaptation
to
the grid programming model. First and foremost, suitable
workflows need to be
developed for the coordination of the grid-enabled application
components
responsible for job-simulation submission and monitoring,
resource monitoring,
data management and result retrieval, which will provide some
basic quality of
service. A first approach towards grid-enabling In Silico
Oncology is to execute
several simulations in parallel, thus reducing the overall time
that a researcher
or a doctor has to wait for different simulation results.
Jobs-simulations may be
efficiently scheduled by the gLite workload management system,
according to
system loading criteria and data locality.
Describe the added value of the Grid for the scientific/technical activity you (plan to) do on the Grid. This should include the scale of the activity and of the potential user community and the relevance for other scientific or business applications
Due to the hypercomplexity of the problem, high-performance
computing
infrastructures are necessary. In order to simulate numerous
candidate
therapeutic scenarios as fast as possible, grid technologies seem
to be
particularly effective. In addition, as tumor response to
radiotherapy is a highly
non linear phenomenon, parallel executions of the simulation code
for a large
number of sets of parameters are highly desirable, in order to
gain better
insight into the dynamics of the system.
Describe the scientific/technical community and the scientific/technical activity using (planning to use) the EGEE infrastructure. A high-level description is needed (neither a detailed specialist report nor a list of references).
In silico oncology is an emerging interdisciplinary field aiming
at mathematically
describing and computationally simulating the multiscale
biological mechanisms
that constitute the phenomenon of cancer and its response to
therapeutic
techniques. Within this framework, the In Silico Oncology Group,
National
Technical University of Athens, has already developed a
four-dimensional
simulation model of glioblastoma multiform response to radiotherapy.
With a forward look to future evolution, discuss the issues you have encountered (or that you expect) in using the EGEE infrastructure. Wherever possible, point out the experience limitations (both in terms of existing services or missing functionality)
Beyond the basic functionality described above, it is also
important that further
mechanisms for fault tolerance and quality of service are
developed and
incorporated to the application. Fault tolerance is a feature
that is not
supported inherently by the grid middleware at present and that
is highly
desirable for a grid-based application. QoS may be achieved by
taking into
consideration workload and resource capacity estimation,
resulting in more
complex scheduling patterns.
This work has been performed in the context of the research
project “Development and adaptation of an in silico oncology
application in grid environment” (GRID-APP). The project is
funded by the General Secretariat for Research and Technology,
Ministry of Development, Greece and the European Regional
Participation Fund.
