How to split a sparse matrix into two

I have a large sparse matrix which I need to correlate which haven't been possible for me because:

1. I cant convert the sparse matrix to a dense matrix due to R's memory limitation
2. I tried using packages bigstats and bigmemory, my R froze over (using a windows 10, 8GB laptop)
3. There's no correlation function in R's Matrix package

Now:

I want to ask if it's possible to split a sparse matrix into two or three parts, convert to dense matrices then correlate each dense matrix then cbind the two or three dense matrices into one then export to a text file.

What function can I use to split a sparse matrix into two or three bearing in mind that both the i and p parts of the sparse matrix are equal sizes with the same dim

Formal class 'dgCMatrix' [package "Matrix"] with 7 slots
  ..@ i       : int [1:73075722]  ...
  ..@ p       : int [1:73075722] 0 0 1 1 1 1 1 2 2 2 ...
  ..@ Dim     : int [1:2] 500232 500232
  ..@ Dimnames:List of 2
  .. ..$ : NULL
  .. ..$ : NULL
  ..@ x       : num [1:73075722]  ...
  ..@ uplo    : chr "L"
  ..@ factors : list()

The correlation output will be in this format:

         [,1]       [,2]       [,3]        [,4]
[1,]  1.00000000 -0.8343860  0.3612926  0.09678096
[2,] -0.83438600  1.0000000 -0.8154071  0.24611830
[3,]  0.36129256 -0.8154071  1.0000000 -0.51801346
[4,]  0.09678096  0.2461183 -0.5180135  1.00000000
[5,]  0.67411584 -0.3560782 -0.1056124  0.60987601
[6,]  0.23071712 -0.4457467  0.5117711  0.21848068
[7,]  0.49200080 -0.4246502  0.2016633  0.46971736
           [,5]       [,6]       [,7]
[1,]  0.6741158  0.2307171  0.4920008
[2,] -0.3560782 -0.4457467 -0.4246502
[3,] -0.1056124  0.5117711  0.2016633
[4,]  0.6098760  0.2184807  0.4697174
[5,]  1.0000000  0.2007979  0.7198228
[6,]  0.2007979  1.0000000  0.6965899
[7,]  0.7198228  0.6965899  1.0000000