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fftw - Fast Fourier Transform library…  more info»

README.Cell

This version of FFTW contains specific support for the Cell Broadband
Engine (``Cell'') processor.

ACKNOWLEDGMENTS
---------------

The code in the cell/ directory was written and graciously donated to
the FFTW project by the IBM Austin Research Laboratory.  We are
grateful to Pat Bohrer and Lorraine Herger of IBM for this generous
contribution.


SCOPE
-----

Cell consists of one PowerPC core (``PPE'') and of a number of
Synergistic Processing Elements (``SPE'') to which the PPE can
delegate computation.  The IBM QS20 Cell blade offers 8 SPEs per Cell
chip.  The Sony Playstation 3 contains 6 useable SPEs.

This version of FFTW fully utilizes the SPEs for one- and
multi-dimensional complex FFTs of sizes that can be factored into
small primes, both in single and double precision.  Transforms of real
data use SPEs only partially at this time.  If FFTW cannot use the
SPEs, it falls back to a slower computation on the PPE.

This library is meant to use the SPEs transparently without user
intervention.  However, certain caveats apply, which are discussed
later in this document.


INSTALLATION
------------

To enable support for Cell in double precision:

   configure --enable-cell
   make
   make install

In single precision:

   configure --enable-cell --enable-single
   make
   make install

In addition, the PPE supports the Altivec (or VMX) instruction set in
single precision.  (Altivec is Apple/Freescale terminology, VMX is IBM
terminology for the same thing.)  You can enable support for Altivec
with the ``--enable-altivec'' flag (single precision only).

The software compiles with the Cell SDK 2.0, and probably with earlier
ones as well.

CAVEATS
-------

* The benchmark program allocates memory using malloc() or equivalent
  library calls, reflecting the common usage of the FFTW library.
  However, you can sometimes improve performance significantly by
  allocating memory in system-specific large TLB pages.  E.g.,
  we have seen 39 GFLOPS/s for a 256x256x256 problem using large
  pages, whereas the speed is about 25 GFLOPS/s with normal pages.
  YMMV.

* FFTW hoards all available SPEs for itself.  You can optionally
  choose a different number of SPEs by calling the undocumented
  function fftw_cell_set_nspe(n), where ``n'' is the number of desired
  SPEs.  Expect this interface to go away once we figure out how to
  make FFTW play nicely with other Cell software.

  In particular, if you try to link both the single and double precision
  of FFTW in the same program (which you can do), they will both try
  to grab all SPEs and the second one will hang.

* The SPEs demand that data be stored in contiguous arrays aligned at
  16-byte boundaries.  If you instruct FFTW to operate on
  noncontiguous or nonaligned data, the SPEs will not be used,
  resulting in slow execution.

* The FFTW_ESTIMATE mode may produce seriously suboptimal plans, and
  it becomes particularly confused if you enable both the SPEs and
  Altivec.  If you care about performance, please use FFTW_MEASURE
  until we figure out a more reliable performance model.

ACCURACY
--------

The SPEs are fully IEEE-754 compliant in double precision.  In single
precision, they only implement round-towards-zero as opposed to the
standard round-to-even mode.  (The PPE is fully IEEE-754 compliant
like all other PowerPC implementations.)  Because of the rounding
mode, FFTW is less accurate when running on the SPEs than on the PPE.
The accuracy loss is hard to quantify in general, but as a rough
guideline, the L2 norm of the relative roundoff error for random
inputs is 4-8 times larger than the corresponding calculation in
round-to-even arithmetic.  In other words, expect to lose 2 to 3 bits
of accuracy.

FFTW currently does not use any algorithm that degrades accuracy to
gain performance on the SPE.  One implication of this choice is that
large 1D transforms run slower than they would if we were willing to
sacrifice another bit or so of accuracy.
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