Exascale systems will require new approaches to performance observation, analysis, and
runtime decision-making to optimize for performance and efficiency. The standard" first …

The Message Passing Interface (MPI) defines the semantics of data communication
operations, while the implementing libraries provide several parameterized algorithms for …

MPI implementations are becoming increasingly complex and highly tunable, and thus
scalability limitations can come from numerous sources. The MPI Tools Interface (MPI_T) …

MPI collective operations provide a standardized interface for performing data movements
within a group of processes. The efficiency of collective communication operations depends …

New developments in HPC technology in terms of increasing computing power on
multi/many core processors, high-bandwidth memory/IO subsystems and communication …

MPI collective communication is an omnipresent communication model for high-
performance computing (HPC) systems. The performance of a collective operation depends …

The main problem when trying to optimize the parameters of libraries, such as MPI, is that
there are many parameters that users can configure. Moreover, predicting the behavior of …

A major trend in HPC is the escalation toward manycore, where systems are composed of
shared memory nodes featuring numerous processing units. Unfortunately, with scale …

Manually tuning MPI runtime parameters is a practice commonly employed to optimise MPI
application performance on a specific architecture. However, the best setting for these …

According to recent performance analyses, MPI collective operations make up a quarter of
the execution time on production systems. Machine learning (ML) autotuners use supervised …