Hi,

I am working on a paper on resilient computing on example of POV-Ray ray tracer
rendering. We chose POV-Ray because it is popular on grid platforms of CERN
type.

In particular, our implementation is able to distribute rendering work of a
clock animation across nodes in rendering server farm, driven by a "smart"
client. Smart client is polling render nodes in such fashion that it is able to
survive crash of many nodes, restart some, and finish the job (unfortunately
with performance penalty) if just one node survives.

In case of catastrophic failure (such as power black-out to entire part of
town), we are able to reboot the cluster and restart smart client with "-C"
option, which will not restart finished frames, being able to reconstruct much
of the state from unrendered frame pool saved state on disk.

However, for ever greater resilience, an option to restart long POV-Ray job is
required. We are capable of restarting POV-Ray process in case of power failure
or other outage that preserved hard disk, yet we are not able to dive into
POV-Ray code and make modifications. IMHO that requires deep knowledge of the
code.

Our architecture offers power of our cluster through a web interface that
delivers CPU power more like a cloud, for specific tasks, rather in all-out
computing manner like CERN grid. Additionally, we were able to recover from node
failures, while at the time of participation in SEE-GRID2, it required all nodes
to finish to complete job, or restarting job for one node would require as much
time as restarting all nodes.

Thank you
iJC
MT

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