cuda-gdb and cudaCheckError() too many resources requested for launch

Accelerated Computing CUDA CUDA Programming and Performance
1

There must be a relation between debug built (nvcc -g -G to debug with cuda-gdb) and GPU resource consumption?

I am using Ubuntu 16.04, toolkit 8.0 on a Titan V GPU and debugging some deep learning code in Tensorflow 1.4.0 with GPU back-end C++ code. As soon as I switch to build the code with debug information, it breaks with

cudaCheckError() too many resources requested for launch

noted that with release built, it does not have this issue although my code is rather close GPU limit. How could I manage to build and debug this code?

2

yes, there is

use the -maxrregcount switch. It is documented in the nvcc manual