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----------------------------------------------------------------------
---- ----
---- Rand number generator library. ----
---- ----
---- This file is part of the Random Number Generator project ----
---- http://www.opencores.org/cores/rng_lib/ ----
---- ----
---- Description ----
---- This library has function for generation random numbers with ----
---- the following distributions: ----
---- - Uniform (continous) ----
---- - Exponential (continous) ----
---- - Gaussian (continous) ----
---- ----
---- Random numbers are produced with a combination of 3 ----
---- Tausworthe generators which gives very good statistical ----
---- properties. ----
---- ----
---- NOTE! These functions will NOT synthesize. They are for test ----
---- bench use only! ----
---- ----
---- To Do: ----
---- - ----
---- ----
---- Author(s): ----
---- - Geir Drange, gedra@opencores.org ----
---- ----
----------------------------------------------------------------------
---- ----
---- Copyright (C) 2004 Authors and OPENCORES.ORG ----
---- ----
---- This source file may be used and distributed without ----
---- restriction provided that this copyright statement is not ----
---- removed from the file and that any derivative work contains ----
---- the original copyright notice and the associated disclaimer. ----
---- ----
---- This source file is free software; you can redistribute it ----
---- and/or modify it under the terms of the GNU General ----
---- Public License as published by the Free Software Foundation; ----
---- either version 2.0 of the License, or (at your option) any ----
---- later version. ----
---- ----
---- This source is distributed in the hope that it will be ----
---- useful, but WITHOUT ANY WARRANTY; without even the implied ----
---- warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR ----
---- PURPOSE. See the GNU General Public License for more details.----
---- ----
---- You should have received a copy of the GNU General ----
---- Public License along with this source; if not, download it ----
---- from http://www.gnu.org/licenses/gpl.txt ----
---- ----
----------------------------------------------------------------------
--
-- CVS Revision History
--
-- $Log: not supported by cvs2svn $
--
--
library ieee;
use ieee.std_logic_1164.all;
use ieee.numeric_std.all;
use std.textio.all;
use work.math_lib.all;
 
package rng_lib is
 
type distribution is (UNIFORM, GAUSSIAN, EXPONENTIAL);
type rand_var is record -- random variable record
rnd: real; -- random number
rnd_v: unsigned(31 downto 0); -- random number vector
dist: distribution; -- distribution type
y, z: real; -- distribution parameters
s1, s2, s3: unsigned(31 downto 0); -- seeds
mask1, mask2, mask3: unsigned(31 downto 0);
shft1, shft2, shft3: natural;
end record;
function rand (rnd: rand_var) return rand_var;
function init_uniform(constant a, b, c: natural;
constant lo, hi: real) return rand_var;
function init_gaussian(constant a, b, c: natural;
constant mean, stdev: real) return rand_var;
function init_exponential(constant a, b, c: natural;
constant mean: real) return rand_var;
 
constant q1: natural:=13;
constant q2: natural:=2;
constant q3: natural:=3;
constant p1: natural:=12;
constant p2: natural:=4;
constant p3: natural:=17;
end rng_lib;
 
package body rng_lib is
 
-- Function to convert 32bit unsigned vector to real
-- Integers only go to 2**31 (VHDL'87), so do it clever
function unsigned_2_real (constant a: unsigned(31 downto 0)) return real is
variable r: real;
begin
r := 2.0*real(to_integer(a(31 downto 1)));
if a(0) = '1' then
r := r + 1.0;
end if;
return(r);
end unsigned_2_real;
-- Generate random number using a combination of 3 tausworthe generators
-- Source: Pierre L'Ecuyer, "Maximally Equidistributed Combined Tausworthe
-- Generators". Mathematics of Computation, vol.65, no.213(1996), pp203--213.
function rng (rnd: rand_var) return rand_var is
variable new_rnd : rand_var;
variable b : unsigned(31 downto 0);
begin
new_rnd :=rnd;
b := ((new_rnd.s1 sll q1) xor new_rnd.s1) srl new_rnd.shft1;
new_rnd.s1 := ((new_rnd.s1 and new_rnd.mask1) sll p1) xor b;
b := ((new_rnd.s2 sll q2) xor new_rnd.s2) srl new_rnd.shft2;
new_rnd.s2 := ((new_rnd.s2 and new_rnd.mask2) sll p2) xor b;
b := ((new_rnd.s3 sll q3) xor new_rnd.s3) srl new_rnd.shft3;
new_rnd.s3 := ((new_rnd.s3 and new_rnd.mask3) sll p3) xor b;
new_rnd.rnd_v := new_rnd.s1 xor new_rnd.s2 xor new_rnd.s3;
-- normalize to range [0,1)
new_rnd.rnd := unsigned_2_real(new_rnd.rnd_v) / 65536.0;
new_rnd.rnd := new_rnd.rnd / 65536.0;
return (new_rnd);
end rng;
 
-- rand function generates a random variable with different distributions
function rand (rnd: rand_var) return rand_var is
variable rnd_out : rand_var;
variable x,y,z : real;
variable t: real := 0.0;
begin
case rnd.dist is
-- Uniform distribution
when UNIFORM =>
rnd_out := rng(rnd);
rnd_out.rnd := rnd.y + (rnd_out.rnd * (rnd.z - rnd.y));
-- Gaussian distribution
when GAUSSIAN => -- Box-Mueller method
z := 2.0;
rnd_out := rnd;
while z > 1.0 or z = 0.0 loop
-- choose x,y in uniform square (-1,-1) to (+1,+1)
rnd_out := rng(rnd_out);
x := -1.0 + 2.0 * rnd_out.rnd;
rnd_out := rng(rnd_out);
y := -1.0 + 2.0 * rnd_out.rnd;
z := (x * x) + (y * y);
end loop;
-- Box-Mueller transform
rnd_out.rnd := rnd_out.y + rnd_out.z * y * sqrt(-2.0 * log(z)/z);
-- Exponential distribution
when EXPONENTIAL =>
rnd_out := rng(rnd);
rnd_out.rnd := -rnd_out.y * log(1.0 - rnd_out.rnd);
when others =>
report "rand() function encountered an error!"
severity failure;
end case;
return (rnd_out);
end rand;
 
-- Initialize seeds, used by all init_ functions
function gen_seed (constant a, b, c: natural) return rand_var is
variable seeded : rand_var;
variable x : unsigned(31 downto 0):= "11111111111111111111111111111111";
constant k1: natural:=31;
constant k2: natural:=29;
constant k3: natural:=28;
begin
seeded.shft1 := k1-p1;
seeded.shft2 := k2-p2;
seeded.shft3 := k3-p3;
seeded.mask1 := x sll (32-k1);
seeded.mask2 := x sll (32-k2);
seeded.mask3 := x sll (32-k3);
seeded.s1 := to_unsigned(390451501, 32);
seeded.s2 := to_unsigned(613566701, 32);
seeded.s3 := to_unsigned(858993401, 32);
if to_unsigned(a, 32) > (to_unsigned(1,32) sll (32-k1)) then
seeded.s1 := to_unsigned(a, 32);
end if;
if to_unsigned(b, 32) > (to_unsigned(1,32) sll (32-k2)) then
seeded.s2 := to_unsigned(b, 32);
end if;
if to_unsigned(c, 32) > (to_unsigned(1,32) sll (32-k3)) then
seeded.s3 := to_unsigned(c, 32);
end if;
return(seeded);
end gen_seed;
-- Uniform distribution random variable initialization
-- a,b,c are seeds
-- lo,hi is the range for the uniform distribution
function init_uniform(constant a, b, c: natural;
constant lo, hi: real) return rand_var is
variable rnd, rout : rand_var;
begin
if lo >= hi then
report "Uniform parameter error: 'hi' must be > 'lo'!"
severity failure;
end if;
rnd := gen_seed(a, b, c);
rnd.dist := UNIFORM;
rnd.y := lo;
rnd.z := hi;
rout := rand(rnd);
return(rout);
end init_uniform;
 
-- Gaussian distribution random variable initialization
-- a,b,c are seeds
-- mean,stdev is mean and standard deviation
function init_gaussian(constant a, b, c: natural;
constant mean, stdev: real) return rand_var is
variable rnd, rout : rand_var;
begin
if stdev = 0.0 then
report "Gaussian parameter error: 'stdev' must be non-zero!"
severity failure;
end if;
rnd := gen_seed(a, b, c);
rnd.dist := GAUSSIAN;
rnd.y := mean;
rnd.z := stdev;
rout := rand(rnd);
return(rout);
end init_gaussian;
 
-- Exponential distribution random variable initialization
-- a,b,c are seeds
-- mean: mean value
function init_exponential(constant a, b, c: natural;
constant mean: real) return rand_var is
variable rnd, rout : rand_var;
begin
if mean <= 0.0 then
report "Exponential parameter error: 'mean' must be > 0!"
severity failure;
end if;
rnd := gen_seed(a, b, c);
rnd.dist := EXPONENTIAL;
rnd.y := mean;
rout := rand(rnd);
return(rout);
end init_exponential;
end rng_lib;

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