Section: New Results

New abstraction to manage hardware topologies in MPI applications

Since the end of year 2016, we have been working on new abstractions and mechanisms that can allow the programmer to take advantage of the underlying hardware topology in their parallel applications developed in MPI. For instance, taking into account the intricate network/memory hierarchy can lead to substantial improvements in communication performance and reduce altogether the overall execution time of the application. However, it is important to find the relevant level of abstraction, as too much details are not usable practically because the programmer is not a a hardware specialist most of the time. Also, MPI being hardware-agnostic, it is important to find means to use the hardware specifics without being tied to a particular architecture or hardware design.

With these goals in mind, we proposed the Hsplit (see Section 6.1) libray that implements a solution based on a well-known MPI concept, the communicators (that can be seen as groups of communicating processes) [7], [19]. With Hsplit , each level in the hardware hierarchy is accessible through a dedicated communicator. In this way, the programmer can leverage the underlying hierarchy in their application quite simply . The current implementation of Hsplit is based on both hwloc and netloc .

This work led to the creation of a new active working group within the MPI Forum, coordinated and led by Inria.

Also, this work has lead to the joint developement of the Hippo software with the CERFACS. Thanks to this piece of software, hybrid OpenMP/MPI applications can leverage the underlying physical hierarchy in order to better place MPI processes and OpenMP threads. This is particularly useful in a context where the application is composed of several kernels that use their own placement and mapping policy for processes and threads to achieve the best performance. Thanks to Hsplit and hwloc , CERFACS is now able to write codes in a more portable fashion without to solely rely on interactions of OpenMP and MPI runtimes for mapping and binding of processes/threads management.