Efficiently implementing Matlab's "Find" function in Julia

I'm trying to implement Matlab's Find function in Julia. In Matlab, the code is

find(A==0)

where A is a very, very large n by m matrix, and where I iterate and update the above over a series of about 500 steps. In Julia, I implement the above via

[findall(x->x==0, D_tot)[j][2] for j in 1:count(x->x==0,D_tot)]

This seems to work nicely, except it goes very slow as I progress with my iteration. For example, for the first step, @time yields

0.000432 seconds (33 allocations: 3.141 KiB)

Step 25:

0.546958 seconds (40.37 k allocations: 389.997 MiB, 7.40% gc time)

Step 65:

1.765892 seconds (86.73 k allocations: 1.516 GiB, 9.63% gc time)

At each step, A remains the same size but becomes more complex, and Julia seems to have trouble finding the zeroes. Is there a better way of implementing Matlab's "Find" function than what I did above?