Re: [Matlisp-users] m.*! not native?

[Tunc S. <si...@ee...>]

Hi Ray, Jefferson;

I've played with Allegro 6.0 as follows (I asked it to explain
 the compilation of m.*!):

(defmethod m.*! ((a real-matrix) (b real-matrix))
  (let* ((nxm (number-of-elements b)))
    (declare (type fixnum nxm)
	     (optimize (speed 3) (safety 0)))

    (dotimes (k nxm b)
      (declare (type fixnum k))
      (let ((a-val (matrix-ref a k))
	    (b-val (matrix-ref b k)))
	(declare (type real-matrix-element-type a-val b-val)
		 (:explain :calls :types :boxing))
	(setf (matrix-ref b k) (* a-val b-val))))))


and here is what I get:

;;; Compiling file C:\usr\gigascale\shift\src\matlisp\src\mtimes.lisp
;Examining a (possibly unboxed) call to *_2OP with arguments:
;  symeval A-VAL type (DOUBLE-FLOAT * *)
;  symeval B-VAL type (DOUBLE-FLOAT * *)
; which returns a value of type (DOUBLE-FLOAT * *)
;Generating a DOUBLE-FLOAT box
;Examining a call to FUNCALL with arguments:
;  call to CDR type KNOWN-FUNCTION
;  symeval G16043 type (DOUBLE-FLOAT * *)
;  symeval G16044 type #<STANDARD-CLASS REAL-MATRIX>
;  symeval G16045 type (INTEGER -536870912 536870911)
; which returns a value of type T
;Examining a call to CDR with arguments:
;  constant ((EVAL-WHEN-LOADED) SETF-METHOD-LOCATIVE (QUOTE MATRIX-REF)
...) type TRUE-LIST
; which returns a value of type KNOWN-FUNCTION
;;; Writing fasl file C:\usr\gigascale\shift\src\matlisp\bin\mtimes.fasl

so my conclusion is that the MATRIX-REF used to access the variables is
waaaaay more expensive than AREF.  Insomuch that it has the overhead of 
a generic function dispatch and also a boxing of the results.
This will explain the performance figures given by Jefferson, which
I was able to duplicate (roughly on the same order) on my Windows 2000
pentium something machine.

Now I quickly tried the following change and got a performance increase
of exactly 10 fold (ie. from 1.7 seconds per call to .13 seconds)
and the compiler is still saying that there is boxing.  I don't know
the Allegro flags very well, but it seems that the matlisp sources
can be modified so that this performance problem disappears
and there is no need to do m.*! in fortran. (disclaimer:  I DIDN'T
TEST IF THE FOLLOWING MODIFICATIONS GIVE CORRECT COMPUTATIONAL
RESULTS OR ARE CONSISTENT WITH MATLISP CODING STANDARDS)

(defmethod m.*! ((a real-matrix) (b real-matrix))
  (let* ((nxm (number-of-elements b))
	 (aa (store a))
	 (bb (store b)))
    (declare (type fixnum nxm)
	     (type (real-matrix-store-type (*)) aa bb)
	     (optimize (speed 3) (safety 0)))

    (dotimes (k nxm b)
      (declare (type fixnum k))
      (let ((a-val (aref aa k))
	    (b-val (aref bb k)))
	(declare (type real-matrix-element-type a-val b-val)
		 (:explain :calls :types :boxing))
	(setf (aref bb k) (* a-val b-val))))))

Good luck and keep this list posted on your results,
I think a tested version of these changes should be checked in 
to the repository.

   -- Tunc

ps. I don't know your terminology on covariance normalization.
  But it seems to me that it should be possible using matlisp functions.

Jefferson Provost wrote:
> 
> On 2/1/02 11:34 AM, "Raymond Toy" <to...@rt...> wrote:
> 
> >>>>>> "Jefferson" == Jefferson Provost <jp...@cs...> writes:
> >
> > You are right.  A peek at the generated code on Solaris seems to show
> > that we are calling out to generic functions way too often and could
> > be vastly optimized.
> >
> > I know with CMUCL, a Lisp version of m+ was almost as fast (< 5%
> > slower?) than Fortran, so m.* should be as fast, even in Lisp.
> >
> > I'll look in to it soon.
> 
> Thanks, though I'd be happy to just write the thing in fortran myself, but
> I'm totally unfamiliar with the foreign function interfaces for Allegro and
> CMUCL.
> 
> Actually, I have another routine that I use a lot which I was hoping might
> be in MATLISP, but which I couldn't find.  I've had to write it myself (in
> lisp) and it's slower than I'd like it to be.  It's basically the
> "covariance normalization" i.e. the normalization that turns a covariance
> matrix into a correlation coefficients matrix.
> 
> J.
> 
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