Distribute function computation over several cores - R - r

Question

I have a function like the following one:
FXN <- function(a, b, c, d, e, f, g){
value <- (a*b/c+d^e)-f+g
write.table(value, paste(a, b, c, d, e, f, g, ".txt", sep = "")}
(But it is a lot more computationally heavy, this just demonstrates the basic idea - does some computation on a single core; writes it to a file.)
If I want to evaluate this function in parallel on 64 cores for all combinations of
a = c(1, 2, 3, 4, 5)
b = c(5, 6, 7, 8, 9)
c = c(11, 12, 13, 14, 15)
d = c(3, 4)
e = c(5, 7, 8)
f = c(4, 5, 6)
g = c(2, 4, 6)
How can I do this? There are 6750 combinations of these values, so the function needs to be run 6750 times.
I am trying the following, but am not sure how foreach handles the function computation. Ideally for my actual function, it just runs the function on each core, writes the table, and moves onto the next combination which hasn't already been run.
library(foreach)
n_cores = 64
registerDoMC(n_cores)
foreach (a = c(1, 2, 3, 4, 5)) %dopar% {
foreach (b = c(5, 6, 7, 8, 9)) %dopar% {
foreach (c = c(11, 12, 13, 14, 15)) %dopar% {
foreach (d = c(3, 4)) %dopar% {
foreach (e = c(5, 7, 8)) %dopar% {
foreach (f = c(4, 5, 6)) %dopar% {
foreach (g = c(2, 4, 6)) %dopar% {
FXN(
a=a,
b=b,
c=c,
d=d,
e=e,
f=f,
g=g
)
}
}
}
}
}
}
}
Would this theoretically work? What other way could I distribute the 6750 combinations over 64 cores, speeding up the computations?
Thanks!