Re: Parallel nested outer for loop

[mratsim]

Nested parallel for is non-trivial, even OpenMP doesn't get it right.

Nim threadpool doesn't have the tools to deal with it.

You can use Weave for this, see this example matrix transposition from the 
README: 
[https://github.com/mratsim/weave#data-parallelism](https://github.com/mratsim/weave#data-parallelism)
    
    
    import weave
    
    func initialize(buffer: ptr UncheckedArray[float32], len: int) =
      for i in 0 ..< len:
        buffer[i] = i.float32
    
    proc transpose(M, N: int, bufIn, bufOut: ptr UncheckedArray[float32]) =
      ## Transpose a MxN matrix into a NxM matrix with nested for loops
      
      parallelFor j in 0 ..< N:
        captures: {M, N, bufIn, bufOut}
        parallelFor i in 0 ..< M:
          captures: {j, M, N, bufIn, bufOut}
          bufOut[j*M+i] = bufIn[i*N+j]
    
    proc main() =
      let M = 200
      let N = 2000
      
      let input = newSeq[float32](M*N)
      # We can't work with seq directly as it's managed by GC, take a ptr to 
the buffer.
      let bufIn = cast[ptr UncheckedArray[float32]](input[0].unsafeAddr)
      bufIn.initialize(M*N)
      
      var output = newSeq[float32](N*M)
      let bufOut = cast[ptr UncheckedArray[float32]](output[0].addr)
      
      init(Weave)
      transpose(M, N, bufIn, bufOut)
      exit(Weave)
    
    main()
    
    
    Run

Or for strided loops: 
    
    
    import weave
    
    init(Weave)
    
    # expandMacros:
    parallelForStrided i in 0 ..< 100, stride = 30:
      parallelForStrided j in 0 ..< 200, stride = 60:
        captures: {i}
        log("Matrix[%d, %d] (thread %d)\n", i, j, myID())
    
    exit(Weave)
    
    
    Run