The Fortran LHAPDF library has been a longterm workhorse in particle physics, providing standardised access to parton density functions for experimental and phenomenological purposes alike, following on from the venerable PDFLIB package. During Run 1 of the LHC, however, several fundamental limitations in LHAPDF's design have became deeply problematic, restricting the usability of the library for important physics-study procedures and providing dangerous avenues by which to silently obtain incorrect results. In this paper we present the LHAPDF 6 library, a ground-up re-engineering of the PDFLIB/LHAPDF paradigm for PDF access which removes all limits on use of concurrent PDF sets, massively reduces static memory requirements, offers improved CPU performance, and fixes fundamental bugs in multi-set access to PDF metadata. The new design, restricted for now to interpolated PDFs, uses centralised numerical routines and a powerful cascading metadata system to decouple software releases from provision of new PDF data and allow completely general parton content. More than 200 PDF sets have been migrated from LHAPDF 5 to the new universal data format, via a stringent quality control procedure. LHAPDF 6 is supported by many Monte Carlo generators and other physics programs, in some cases via a full set of compatibility routines, and is recommended for the demanding PDF access needs of LHC Run 2 and beyond.

Summary The Exascale Computing Project (ECP) focuses on the development of future exascale‐capable applications. Most ECP applications use the message passing interface (MPI) as their parallel programming model with mini‐apps serving as proxies. This paper explores the explicit usage of MPI in such ECP proxy applications. We empirically analyze 14 proxy applications from the ECP Proxy Apps Suite. We use the MPI profiling interface (PMPI) to collect MPI usage patterns in ECP proxy apps. Our analysis shows that a small subset of features from MPI is commonly used in the proxies of exascale‐capable applications, even when they reference third‐party libraries. This study is intended to provide a better understanding of the use of MPI in current exascale applications. The findings can help focus software investments made for exascale systems in the MPI middleware including optimization, fault‐tolerance, tuning, and hardware‐offload.

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