Seeding random number generator

Sorry if this has been covered already. I am developing a testbench
for a design and I want the behavioral models for external devices to
use random parameters within the constraints of the data sheets. I
figured out how to start up a sim with a seed variable in Modelsim,
but now I'm confused about how to use that seed. Say I have two
processes, each controlling one aspect of an ADC. Does each process
have its own random number stream or do they share some global random
number stream? In other words, does each process access a global seed
or do they each maintain their own seeds. I was thinking that a global
seed may be dangerous because it may change in a non-deterministic
fashion. Here is an example with local seeds. The first process
controls the ADC convert to busy timing, the second process controls
the prop delay through a mux. Each takes the initial value for the
seed from the generic for the testbench and then keeps a local copy of
the seed. Is this the right way to do this?

procedure rand_time(
variable seed1, seed2 : inout positive;
min, max : in integer;
result : out time
) is
variable rand : real;
begin
uniform(seed1, seed2, rand);
result := (integer(real(min) + (rand * (real(max)-real(min)) ) ))* 1
ps;
end procedure;

-- ADC busy timing
convert : process
variable s1 : integer;
variable s2 : integer;
variable t6 : time;
variable tconv : time;
variable init : std_logic;
begin
-- Init seeds from generic if not already initialized
if(init /= '1')then
s1 := gSEED;
s2 := s1/2 + 50;
init := '1';
end if;
busy_n <= '1';

wait until falling_edge(convst_n);
if(cs_n = '0')and(shtdn_n = '1')then
rand_time(s1, s2, MIN_T6, MAX_T6, t6);
rand_time(s1, s2, MIN_TCONV, MAX_TCONV, tconv);
busy_n <= '0' after t6;
wait for (tconv - t6);
busy_n <= '1';
dtemp <= din;
end if;
end process convert;

-- mux timing
mux : process (en_n, mux_sel)
variable s1: integer;
variable s2: integer;
variable p : time;
variable init : std_logic;
begin
-- Init seeds from generic if not already initialized
if(init /= '1')then
s1 := gSEED;
s2 := s1/2 + 50;
init := '1';
end if;

rand_time(s1, s2, MIN_DELAY, MAX_DELAY, p);

if(en_n = '1') then
dout <= (others => 'Z') after p;

else
dout(15 downto 12) <= mux_sel after p;
dout(11 downto 0) <= (others => '0') after p;
end if;
end process mux;

There is no Global seed. The seeds are stored in the seed variables
(s1 and s2 in each process) you have. If you monitored them you'd
notice that they change every time you call the uniform function, and
hence why they are of mode "inout".

So in effect there is no "random number stream" as you put it - just a
formula that gives you a value based on s1 and s2, and s1 and s2 are
changed after each call.

This is useful because it allows repeatability of random streams. You
can check output by seeding the expected output sequence with the same
seeds you initialised the input sequence with.

> procedure rand_time(
> variable seed1, seed2 : inout positive;
> min, max : in integer;
> result : out time
> ) is
> variable rand : real;
> begin
> uniform(seed1, seed2, rand);
> result := (integer(real(min) + (rand * (real(max)-real(min)) ) ))* 1
> ps;
> end procedure;


Another point: this function doesnt have the correct probability for
min and max occuring.
If n is the probability for any value occuring, the values of Min and
Max themselves have a probability of n/2. This is because the integer
conversion function rounds to nearest rather than truncate which means
min and max only have a 0-0.5 range each, rather than 0-1.0.

eg:

Min = 0, Max = 3.

result           Actual output
before rounding
0.0-0.5            0
0.5-1.5            1
1.5-2.5            2
2.5-3.0            3

Therefore 1 and 2 are each twice as likely to occur than 0 and 3.


I have a very similar procedure for integers, and found the solution
to the problem thus (thanks to who posted the random testing package
the other week :) ):

procedure rand_int( variable seed1, seed2 : inout positive; min, max :
in integer; result : out integer) is
  variable rand      : real;
  variable val_range : real;
begin
  assert (max >= min) report "Rand_int: Range Error" severity Failure;

  uniform(seed1, seed2, rand);
  val_range := real(Max - Min + 1);
  result := integer( trunc(rand * val_range )) + min;
end procedure;

This increases the

You can simplify this greatly by using the packages that I developed.
They layer on top of procedure uniform.

Packages and usage notes are available at:
  http://www.synthworks.com/downloads/index.htm

The presentation focuses on randomizing integers, however,
time values can be generated by multiplying by 1 ns.
To inspire you, your process would be:

Compile packages - directions are in the download

Use SynthWorks.RandomPkg.all ;  -- reference package

process
  variable RV : RandomPType ;  -- declare randomization variable
begin
  -- Initialize Seed  -- done once
  RV.SetSeed( (7, 1) ) ;  -- optional if you only are doing one thread
of randomization
  ...
  p := 1 ns * RV.RandInt(MIN_DELAY, MAX_DELAY) ;


Cheers,
Jim
SynthWorks VHDL Training

P.S.  We teach randomization plus self-checking, transaction-based
testing,
and verification data structures (linked-lists, scoreboards,
memories),
in our VHDL Testbenches and Verification classes.
See:  http://www.synthworks.com/vhdl_testbench_verification.htm