Open ig0xb opened 7 years ago
Several comments. 1) What operations were you hoping would be parallelized here? 2) With the C backend (the default under Julia 0.5), the functions optimized with ParallelAccelerator need to be type stable. The above function is not. You have xs first as an array and then later as "nothing." Why are you setting the variables to "nothing" when you're done with them? 3) ParallelAccelerator with the C backend doesn't handle "Any". So, if you have Array{Any,1}, it isn't going to support that. That should be supported with the native backend. 4) In general, I'd suggest creating small kernels that you believe should parallelize. So, a general idea would be to split I/O from the parallel computation.
Hi,
I am getting the following error when i use ParallelAccelerator.
OptFramework failed to optimize function ##load_pickle_data#322 in optimization pass ParallelAccelerator.Driver.toParallelIR with error typeOf Opr _8::Array{Any,1} is incompatible with its type in lambda Void
I am loading 5 different python pickle dataset using Pycall package and it is passed into the below function as Array to concatenate into one single array for further processing. When i run this function i get the above mentioned array.
Kindly let me know what am i doing wrong if i want to optimise the function using ParallelAccelerator.
Thank You