PetscSF, the communication component of the Portable, Extensible Toolkit for Scientific Computation (PETSc), is designed to provide PETSc's communication infrastructure suitable for exascale computers that utilize GPUs and other accelerators. PetscSF provides a simple application programming interface (API) for managing common communication patterns in scientific computations by using a star-forest graph representation. PetscSF supports several implementations based on MPI and NVSHMEM, whose selection is based on the characteristics of the application or the target architecture. An efficient and portable model for network and intra-node communication is essential for implementing large-scale applications. The Message Passing Interface, which has been the de facto standard for distributed memory systems, has developed into a large complex API that does not yet provide high performance on the emerging heterogeneous CPU-GPU-based exascale systems. In this article, we discuss the design of PetscSF, how it can overcome some difficulties of working directly with MPI on GPUs, and we demonstrate its performance, scalability, and novel features.

Coupling separately developed codes offers an attractive method for increasing the accuracy and fidelity of the computational models. Examples include the earth sciences and fusion integrated modeling. This paper describes the Framework Application for Core-Edge Transport Simulations (FACETS).

Due to the complexity associated with developing parallel applications, scientists and engineers rely on high-level software libraries such as PETSc, ScaLAPACK and PESSL to ease this task. Such libraries assist developers by providing abstractions for mathematical operations, data representation and management of parallel layouts of the data, while internally using communication libraries such as MPI and PVM. With high-level libraries managing data layout and communication internally, it can be expected that they organize application data suitably for performing the library operations optimally. However, this places additional overhead on the underlying communication library by making the data layout noncontiguous in memory and communication volumes (data transferred by a process to each of the other processes) nonuniform. In this paper, we analyze the overheads associated with these two aspects (noncontiguous data layouts and nonuniform communication volumes) in the context of the PETSc software toolkit over the MPI communication library. We describe the issues with the current approaches used by MPICH2 (an implementation of MPI), propose different approaches to handle these issues and evaluate these approaches with micro-benchmarks as well as an application over the PETSc software library. Our experimental results demonstrate close to an order of magnitude improvement in the performance of a 3-D Laplacian multi-grid solver application when evaluated on a 128 processor cluster.