Two swings at guassian distribution in Postgres

I've come across 2 ways to replicate a bell curve.

This is adding 3 random numbers together.

select 
floor(random()*3)+floor(random()*3)+floor(random()*3) as y, 
count(*) 
from generate_series(1,10000000) group by y order by y;
 y |  count
---+---------
 0 |  369905
 1 | 1111997
 2 | 2222763
 3 | 2593306
 4 | 2220452
 5 | 1111506
 6 |  370071
(7 rows)

Time: 18806.885 ms

Consistent distribution, but 18 seconds for 10 million rows!

The second method has a tail end of the curve that keeps going even as it tapers to 0. This uses the normal_rand function provided by postgres with arguments of quantity, median, and standard deviation.

select  x, count(*) 
from 
(select abs(ceil(normal_rand(10000000,2,1))) as x) as y 
group by x order by count;
 x |  count
---+---------
 0 |  214152
 1 | 1373200
 2 | 3414028
 3 | 3411424
 4 | 1359447
 5 |  214194
 6 |   13234
 7 |     319
 8 |       2
(9 rows)

Time: 3221.894 ms

I want the peak of the curve around 2 and 3 but for this method of Gaussian distribution I get results below 0 unless I use abs. And its fast, 3 seconds!