Compiled MPI

Cost-Effective Exascale Application Development
The complexity of Petascale and Exascale machines makes it increasingly difficult to develop applications that can take advantage of them. Future systems are expected to feature billion-way parallelism, complex heterogeneous compute nodes and poor availability of memory. This new challenge for application development is motivating a significant amount of research and development on new programming models and runtime systems designed to simplify large-scale application development. Unfortunately, DoE has significant multi-decadal investment in a large family of mission-critical scientific applications. Scaling these applications to Exascale machines will require a significant investment that will dwarf the costs of hardware procurement. A key reason for the difficulty in transitioning today's applications to Exascale hardware is their reliance on explicit programming techniques, such as the Message Passing Interface (MPI) programming model to enable parallelism.

MPI provides a portable and high performance message-passing system that enables scalable performance on a wide variety of platforms. However, it also forces developers to lock the details of parallelization together with application logic, making it very difficult to adapt the application to significant changes in the underlying system.
Further, MPI's explicit interface makes it difficult to describe the application's synchronization and communication structure, reducing the amount of support that can be provided by the compiler and run-time tools. This is in contrast to recent research on more implicit parallel programming models such as X10, Chapel, OpenMP and OpenCL, which promise to provide significantly more flexibility at the cost of reimplementing significant portions of the application.
Compiled MPI (CoMPI) is a novel compiler-driven approach to enable existing MPI applications to scale to Exascale systems with minimal modifications that can be made incrementally over the application's lifetime. It includes:
  • A new set of source code annotations, inserted either manually or automatically, that will clarify the application's use of MPI to the compiler infrastructure, enabling greater accuracy where needed,
  • A compiler transformation framework that leverages these annotations to transform the original MPI source code to improve its performance and scalability,
  • Novel MPI runtime implementation techniques that will provide a rich set of functionality extensions that will be used by applications that have been transformed by our compiler,
  • A novel compiler analysis that leverages simple user annotations to automatically extract the application's communication structure and synthesize most complex code annotations.
CoMPI is based on the R&D 100 award-winning ROSE compiler and production Open MPI implementation of MPI, enabling it to target complex DoE Applications and become a practical tool.

The final deliverable of this project will be a system that will help legacy MPI applications reach Exascale performance while making only incremental changes to their source code, thus gaining most of the benefits of implicit programming models without most of the costs. By providing developers with unprecedented levels of compiler and runtime support, this system will enable them to focus on new science and to concentrate their reimplementation efforts on the few portions of their applications that require truly new numerical methods rather than new ways of expressing them.
Daniel Quinlan, Lawrence Livermore National Laboratory

Greg Bronevetsky: Lawrence Livermore National Laboratory

Andrew Lumsdaine, Indiana University and Torsten Hoefler

University of Illinois at Urbana-Champaign.

Communication Protocols

Compiler Analyses and Transformations

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