Nitrate Biogeochemistry and Reactive Transport in California Groundwater: LDRD Final Report

Nitrate is the number one drinking water contaminant in the United States. It is pervasive in surface and groundwater systems,and its principal anthropogenic sources have increased dramatically in the last 50 years. In California alone, one third of the public drinking-water wells has been lost since 1988 and nitrate contamination is the most common reason for abandonment. Effective nitrate management in groundwater is complicated by uncertainties related to multiple point and non-point sources, hydrogeologic complexity, geochemical reactivity, and quantification of denitrification processes. In this paper, we review an integrated experimental and simulation-based framework being developed to study the fate of nitrate in a 25 km-long groundwater subbasin south of San Jose, California, a historically agricultural area now undergoing rapid urbanization with increasing demands for groundwater. The modeling approach is driven by a need to integrate new and archival data that support the hypothesis that nitrate fate and transport at the basin scale is intricately related to hydrostratigraphic complexity, variability of flow paths and groundwater residence times, microbial activity, and multiple geochemical reaction mechanisms. This study synthesizes these disparate and multi-scale data into a three-dimensional and highly resolved reactive transport modeling framework

Conceptualising centres of excellence: a scoping review of global evidence

Objective- Globally, interest in excellence has grown exponentially, with public and private institutions shifting their attention from meeting targets to achieving excellence. Centres of Excellence (CoEs) are standing at the forefront of healthcare, research and innovations responding to the world’s most complex problems. However, their potential is hindered by conceptual ambiguity. We conducted a global synthesis of the evidence to conceptualise CoEs. Design- Scoping review, following Arksey and O’Malley’s framework and methodological enhancement by Levac et al and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. Data sources- PubMed, Scopus, CINAHL, Google Scholar and the Google engine until 1 January 2021. Eligibility- Articles that describe CoE as the main theme. Results- The search resulted in 52 161 potential publications, with 78 articles met the eligibility criteria. The 78 articles were from 33 countries, of which 35 were from the USA, 3 each from Nigeria, South Africa, Spain and India, and 2 each from Ethiopia, Canada, Russia, Colombia, Sweden, Greece and Peru. The rest 17 were from various countries. The articles involved six thematic areas—healthcare, education, research, industry, information technology and general concepts on CoE. The analysis documented success stories of using the brand ‘CoE’—an influential brand to stimulate best practices. We identified 12 essential foundations of CoE—specialised expertise; infrastructure; innovation; high-impact research; quality service; accreditation or standards; leadership; organisational structure; strategy; collaboration and partnership; sustainable funding or financial mechanisms; and entrepreneurship. Conclusions- CoEs have significant scientific, political, economic and social impacts. However, there are inconsistent use and self-designation of the brand without approval by an independent, external process of evaluation and with high ambiguity between ‘CoEs’ and the ordinary ‘institutions’ or ‘centres’. A comprehensive framework is needed to guide and inspire an institution as a CoE and to help government and funding institutions shape and oversee CoEs

Efficient Task-Local I/O Operations of Massively Parallel Applications

Applications on current large-scale HPC systems use enormous numbers of processing elements for their computation and have access to large amounts of main memory for their data. Nevertheless, they still need file-system access to maintain program and application data persistently. Characteristic I/O patterns that produce a high load on the file system often occurduring access to checkpoint and restart files, which have to be frequently stored to allow the application to be restarted after program termination or system failure. On large-scale HPC systems with distributed memory, each application task will often perform such I/O individually by creating task-local file objects on the file system. At large scale, these I/O patterns impose substantial stress on the metadata management components of the I/O subsystem. For example, the simultaneous creation of thousands of task-local files in the same directory can cause delays of several minutes. Also at the startup of dynamically linked applications, such metadata contention occurs while searching for library files and induces a comparably high metadata load on the file system. Even mid-scale applications cause in such load scenarios startup delays of ten minutes or more. Therefore, dynamic linking and loading is nowadays not applied on large HPC systems, although dynamic linking has many advantages for managing large code bases. The reason for these limitations is that POSIX I/O and the dynamic loader are implemented as serial components of the operating system and do not take advantage of the parallel nature of the I/O operations. To avoid the above bottlenecks, this work describes two novel approaches for the integration of locality awareness (e.g., through aggregation or caching) into the serial I/O operations of parallel applications. The underlying methods are implemented in two tools, $\textit{SIONlib}$ and $\textit{Spindle}$, which exploit the knowledge of application parallelism to coordinate access to file-system objects. In addition, the applied methods also use knowledge of the underlying I/O subsystem structure, the parallel file system configuration, and the network betweenHPC-system and I/O system to optimize application I/O. Both tools add layers between the parallel application and the POSIX-based standard interfaces of the operating system for I/O and dynamic loading, eliminating the need for modifying the underlying system software. SIONlib is already applied in several applications, including PEPC, muphi, and MP2C, to implement efficient checkpointing. In addition, SIONlib is integrated in the performance-analysis tools Scalasca and Score-P to efficiently store and read trace data. Latest benchmarks on the Blue Gene/Q in Jülich demonstrate that SIONlib solves the metadata problem at large scale by running efficiently up to 1.8 million tasks while maintaining high I/O bandwidths of 60-80% of file-system peak with a negligible file-creation time. The scalability of Spindle could be demonstrated by running the Pynamic benchmark, a proxy benchmark for a real application, on a cluster of Lawrence Livermore National Laboratory at large scale. The results show that the startup of dynamically linked applications is now feasible on more than 15000 tasks, whereas the overhead of Spindle is nearly constantly low. With SIONlib and Spindle, this work demonstrates how scalability of operating system components can be improved without modifying them and without changing the I/O patterns of applications. In this way, SIONlib and Spindle represent prototype implementations of functionality needed by next-generation runtime systems