@InProceedings{Jones13,
  title =        "{A} {P}ersonal {P}erspective on the {S}tate of {HPC} in 2013",
  author=        "Jones,  Christopher C.R.",
  editor=        "Welch, Peter H. and Barnes,  Frederick R. M. and Broenink,  Jan F. and Chalmers,  Kevin and Pedersen,  Jan Bækgaard and Sampson,  Adam T.",
  pages =        "263--270",
  booktitle=     "{C}ommunicating {P}rocess {A}rchitectures 2013",
  isbn=          "978-0-9565409-7-3",
  year=          "2013",
  month=         "nov",
  abstract=      "This paper is fundamentally a personal perspective on the
     sad state of
High Performance Computing (HPC, or what was
     known once as
Supercomputing).  It arises from the author's
     current experience in
trying to find computing technology
     that will allow codes to run
faster: codes that have been
     painstakingly adapted to efficient
performance on parallel
     computing technologies since around 1990, and
have allowed
     effective 10-fold increases in computing performance at
     5
year HPC up-grade intervals, but for which the latest
     high-count
multi-core processor options fail to deliver
     improvement.  The
presently available processors may as well
     not have the majority of
their cores as to use them actually
     slows the code - hard-won budget
must be squandered on cores
     that will not contribute.  The present
situation is not
     satisfactory: there are very many reasons why we
     need
computational response, not merely throughput.  There
     are a host of
cases where we need a large, complex
     simulation to run in a very short
time.  A simplistic
     calculation based on the nominal performance of
some of the
     big machines with vast numbers of cores would lead one
     to
believe that such rapid computation would be possible. 
     The nature of
the machines and the programming paradigms,
     however, remove this
possibility.  Some of the ways in which
     the computer science community
could mitigate the hardware
     shortfalls are discussed, with a few more
off the wall ideas
     about where greater compute performance might be
found."
}