Hello,
I have a Python extension written in C++ which calls the HDF library,
and I would like to use Darshan to profile an MPI-based Python
application which invokes that extension. However, compiling the
extension and running the application on Blue Waters (Cray-based
system) with Darshan 2.3 results in no profile data being generated.
Using LD_PRELOAD to load Darshan dynamically results in some kind of
socket error when (I think) the MPI process manager is launching the
Python executable. I have also tried the LD_PRELOAD mechanism with
Darshan 3.1.3 built by the HDF group, but I get the same error. I was
wondering if anyone here has done profiling with dynamically linked
Python extensions, or if anyone has any advice how to approach this.
I invoke the application with LD_PRELOAD thus:
export LD_PRELOAD=/path/to/darshan/3.1.3/lib/libdarshan.so
aprun -n 4096 python main.py ...
or
aprun -n 4096 -e LD_PRELOAD=/path/to/darshan/3.1.3/.../lib/libdarshan.so
The error I get with LD_PRELOAD is the following:
[PE_3344]:inet_listen_socket_setup:inet_setup_listen_socket: bind
failed port 1371 listen_sock = 88 Address already in use
[PE_3344]:_pmi_inet_listen_socket_setup:socket setup failed
[PE_3344]:_pmi_init:_pmi_inet_listen_socket_setup (full) returned -1
[PE_208]:inet_listen_socket_setup:inet_setup_listen_socket: bind
failed port 1371 listen_sock = 74 Address already in use
[PE_208]:_pmi_inet_listen_socket_setup:socket setup failed
[PE_208]:_pmi_init:_pmi_inet_listen_socket_setup (full) returned -1
Thanks and best regards,
