db_connect: Could not connect to paper db at "wotug@dragon.kent.ac.uk"<br>
db_connect: Could not connect to paper db at "wotug@dragon.kent.ac.uk"<br>
@InProceedings{Skovhede11,
  title =        "{P}rogramming the {CELL}-{BE} using {CSP}",
db_connect: Could not connect to paper db at "wotug@dragon.kent.ac.uk"<br>
  author=        "Skovhede,  Kenneth and Larsen,  Morten N. and Vinter,  Brian",
db_connect: Could not connect to paper db at "wotug@dragon.kent.ac.uk"<br>
  editor=        "Welch, Peter H. and Sampson,  Adam T. and Pedersen,  Jan Bækgaard and Kerridge,  Jon and Broenink,  Jan F. and Barnes,  Frederick R. M.",
db_connect: Could not connect to paper db at "wotug@dragon.kent.ac.uk"<br>
  pages =        "55--70",
  booktitle=     "{C}ommunicating {P}rocess {A}rchitectures 2011",
  isbn=          "978-1-60750-773-4",
  year=          "2011",
  month=         "jun",
  abstract=      "The current trend in processor design seems to focus on
     using multiple
cores, similar to a cluster-on-a-chip model.
     These processors are
generally fast and power efficient, but
     due to their highly parallel
nature, they are notoriously
     difficult to program for most scientists.
One such processor
     is the CELL broadband engine (CELL-BE) which is known
for
     its high performance, but also for a complex programming
     model which
makes it difficult to exploit the architecture
     to its full potential. To
address this difficulty, this
     paper proposes to change the programming
model to use the
     principles of CSP design, thus making it simpler to
program
     the CELL-BE and avoid livelocks, deadlocks and race
     conditions.
The CSP model described here comprises a thread
     library for the
synergistic processing elements (SPEs) and a
     simple channel based
communication interface. To examine the
     scalability of the
implementation, experiments are performed
     with both scientific
computational cores and synthetic
     workloads. The implemented CSP model
has a simple API and is
     shown to scale well for problems with
significant
     computational requirements."
}