RE: [sv-ec] Clarification needed on distribution and contraint solving

 
Arturo,
Thanks for the quick answer. It was not clear to me and Chianhon (and
probably to many readers of the LRM) that all the 3 solutions you mentioned
at the end of this email are valid. Any one of the 3 solutions violates a
distribution. If all of the 3 solutions are acceptable behaviours of the
solver, then for clarity sake we should add this example to the LRM, along
with an explanation that there is no specified priority between
distributions related to same variables, even more, distributions are
statistical indications and may not be satisfied at all (solution when x = y
50 % of the time).
The first solution would give priority to distribution #1, second solution
to distribution #2 and third solution to none of the distributions.
 
Should the user get an warning message that one of the distibutions could
not be satisfied? Perhaps he did not
intend to have conflicting distributions.
 
Francoise
       '
 
 

  _____

From: owner-sv-ec@eda.org [mailto:owner-sv-ec@eda.org] On Behalf Of Arturo
Salz
Sent: Sunday, October 17, 2004 8:55 PM
To: Francoise Martinolle; sv-ec@eda.org
Cc: chien
Subject: Re: [sv-ec] Clarification needed on distribution and contraint
solving

Francoise,
 
The distribution operator specifies two pieces of information: a value set,
and a statistical
distribution of the values within that set. The set itself defines the
solution space (just like
the inside operator), not the distribution --- An obvious exception is a
distribution of 0, which
effectively excludes the value from the set.
Since it does not affect the solution space, the distribution part of the
dist operator alone
should never cause a set of constraints to fail, only an empty solution
space.
 
That is why the LRM states:
 
Absent any other constraints, the probability that the expression matches
any value in the list is
proportional to its specified weight.
 
Evidently, other constraints may change the statistical distribution or the
solution space,
and thus void the monotonic weighting property of the dist operator.
 
To illustrate, consider your example that yields the following solution
space information:
    constraint 1) x is in the range 0 to 1

    constraint 2) y is in the range 0 to 1
    constraint 3) x must equal y
 
So the solution space is the diagonal line with coordinates (0,0) - (1,1),
visualized as:
 
 x |
   |
 1 |...

   | /.
   | / .

 0 |/__.____ y

   0 1
 
As you point out, the value distribution within the solution space cannot be
satisfied simultaneously.
The actual distribution will depend on the solver algorithm and
implementation. A solver might use
the 1st distribution (x and y are 0 90% of the time), another might use the
2nd distribution (x and y
are 0 10% of the time), while others may ignore the conflicting
distributions altogether (x and y are
0 50% of the time). All of these solutions are valid.
 
    Arturo
 
----- Original Message -----
From: Francoise Martinolle <mailto:fm@cadence.com>
To: sv-ec@eda.org
Cc: chien@cadence.com
Sent: Friday, October 15, 2004 6:40 PM
Subject: [sv-ec] Clarification needed on distribution and contraint solving

I am forwarding a question from a collegue at Cadence:
If that is necessary I can enter an errata to track this issue. Please let
me know.
 
It is unclear on how distributions and constaints are solved. Can you please
specify what should occur in the following
cases:
 
1. With the lack of solve-befores, are distributions solved concurrently
with all other constraints?
 
2. When distribution constraints contradict with other constraints, what is
the expected behavior of the simulator? As an example, the following three
constraints cannot be satisfied concurrently...
 
  x dist { 0 := 90, 1 := 10 }; // x is more likely to be 0
  y dist { 0 := 10, 1 := 90 }; // y is more likely to be 1
  constraint c { x == y; }
 
How does LRM treat this situation?
 
Francoise
       '
 
Received on Mon Oct 18 11:55:05 2004