performance - Make my R code run faster (nested loops) -

imagine have 150 5 matrix. each element contains random integer 0 20.

now think each column of matrix independent; need loop through possible combination of 5 columns, yields 150^5 = 75937500000 combinations.

it critical run every single combination once. order ran combinations not matter.

i tried doing using while loops. see code below.

to run loop, based on calculation take me 54 hours on laptop.

questions

• any way make code run faster on laptop? (bootstrapping?)

• if not, there web r servers can access run code @ significant faster rate?

• if not, make significant difference run in another/faster language? (python)

  while(counter1 <= 150)  {    while(counter2 <= 150)   {     while(counter3 <= 150)      {       while(counter4 <= 150)        {         while(counter5 <= 150)        {       #other operations take additional time#       result<-c(       giant_matrix[counter1,1],        giant_matrix[counter2,2],        giant_matrix[counter3,3],        giant_matrix[counter4,4],        giant_matrix[counter5,5])        counter5=counter5+1     }     counter5=1     counter4=counter4+1   }   counter4=1   counter3=counter3+1 } counter3=1 counter2=counter2+1 } counter2=1 counter1=counter1+1 } 

here above solution 20 x 5 matrix of 100 elements. results in data frame of 3,200,000 x 5 size:

m <- matrix(sample(1:20, 100, replace = true), nrow = 20) df <- expand.grid(m[, 1], m[, 2], m[, 3], m[, 4], m[, 5]) 

example output of above df (head):

head(df)   var1 var2 var3 var4 var5 1   10   19   13    4    7 2   19   19   13    4    7 3    3   19   13    4    7 4    5   19   13    4    7 5   11   19   13    4    7 6    8   19   13    4    7  nrow(df) [1] 3200000  dim(df) [1] 3200000       5