monte carlo simulation with summation

[jan_t_lagen]

I'm trying to do a monte carlo simulation where I need to sum over the total data set as a last step and can't seem to make it work, let alone do it in a nice way. 

I want to simulate the variable A that is made from a number of parameters and the standard normal distribution. From this I want to sum another variable w if A fulfills a specific requirement.

My problem is firstly that i can't find a way to sum these w in the same data step as the simulation of A. Since my data set is about 10 000 rows and i want to do 500 000 simulations I can't have the table growing to 500 000 * 10 000 but rather i want the final table to have the sums of each iteration, in other words it should be 500 000  rows 

Furthermore i'm interested in if there is a more elegant way of approaching this problem in terms of the functions used etc.

I'm using SAS 9.3 if its relevant.

Thanks!

this is what i have so far, but it is not working...

data multi;
set multi_base;

do iter = 1 to 2;

L = 0;

A = a1*rand("Normal") +
a2*rand("Normal") +
a3*rand("Normal") +
a4*rand("Normal") +
a5*rand("Normal") 

if A < b then L = L + w;

output;
end;
keep iter L;
run;

[PeterClemmensen]

2 questions: 

Do you have a SAS/IML license?

What does the data set multi_base look like?

[jan_t_lagen]

I do not have a SAS/IML licence and multi_base just contains a1-a5, b and w
that are unique for each row

[Rick_SAS]

I assume that if A >= b then L remains unchanged and that value of w is discarded?

Compute the conditional cumulative sum as you go along, but put the OUTPUT statement OUTSIDE the END of the iteration loop.