Περίληψη:
The GeantV project is focused on the R&D of new particle transport
techniques to maximize parallelism on multiple levels, profiting from
the use of both SIMD instructions and co-processors for the
CPU-intensive calculations specific to this type of applications. In our
approach, vectors of tracks belonging to multiple events and matching
different locality criteria must be gathered and dispatched to
algorithms having vector signatures. While the transport propagates
tracks and changes their individual states, data locality becomes harder
to maintain. The scheduling policy has to be changed to maintain
efficient vectors while keeping an optimal level of concurrency. The
model has complex dynamics requiring tuning the thresholds to switch
between the normal regime and special modes, i.e. prioritizing events to
allow flushing memory, adding new events in the transport pipeline to
boost locality, dynamically adjusting the particle vector size or
switching between vector to single track mode when vectorization causes
only overhead. This work requires a comprehensive study for optimizing
these parameters to make the behaviour of the scheduler self-adapting,
presenting here its initial results.
Συγγραφείς:
Apostolakis, J.
Bandieramonte, M.
Bitzes, G.
Brun, R. and
Canal, P.
Carminati, F.
Licht, J. C. De Fine
Duhem, L. and
Elvira, V. D.
Gheata, A.
Jun, S. Y.
Lima, G.
Novak, M.
and Sehgal, R.
Shadura, O.
Wenzel, S.
