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Influenced by the advances in data and computing, the scientific practice increasingly involves machine learning and artificial intelligence driven methods which requires specialized capabilities at the system-, science- and service-level…
Cloud computing provides a great opportunity for scientists, as it enables large-scale experiments that cannot are too long to run on local desktop machines. Cloud-based computations can be highly parallel, long running and data-intensive,…
RESTful APIs are central in developing interoperable, modular, and maintainable software systems in enterprises today. Also, it is essential to support system evolution, service interoperability, and governance across organizational…
The landscape of workflow systems for scientific applications is notoriously convoluted with hundreds of seemingly equivalent workflow systems, many isolated research claims, and a steep learning curve. To address some of these challenges…
Nowadays, invoking third party code increasingly involves calling web services via their web APIs, as opposed to the more traditional scenario of downloading a library and invoking the library's API. However, there are also new challenges…
During the application of chemical pesticides, distance requirements have to be considered. However, these have to be determined and considered by the farmer manually. To support the farmer the Pesticide Application Manager (PAM)-Projects…
High-Performance Computing (HPC) systems are among the most energy-intensive scientific facilities, with electric power consumption reaching and often exceeding 20 megawatts per installation. Unlike other major scientific infrastructures…
The rising number of IoT devices is accelerating the research on new solutions that will be able to efficiently deal with unreliable connectivity in highly dynamic computing applications. To improve the overall performance in IoT…
Progress in science is deeply bound to the effective use of high-performance computing infrastructures and to the efficient extraction of knowledge from vast amounts of data. Such data comes from different sources that follow a cycle…
Various research domains use machine learning approaches because they can solve complex tasks by learning from data. Deploying machine learning models, however, is not trivial and developers have to implement complete solutions which are…
Scientific applications in HPC environment are more com-plex and more data-intensive nowadays. Scientists usually rely on workflow system to manage the complexity: simply define multiple processing steps into a single script and let the…
Modern parallel filesystems such as Lustre are designed to provide high, scalable I/O bandwidth in response to growing I/O requirements; however, the bursty I/O characteristics of many data-intensive scientific applications make it…
In the last few years, contributions of the general public in scientific projects has increased due to the advancement of communication and computing technologies. Internet played an important role in connecting scientists and volunteers…
REST APIs enable collaboration among microservices. A single fault in a REST API can bring down the entire microservice system and cause significant financial losses, underscoring the importance of REST API testing. Effectively testing REST…
Representational State Transfer (REST) APIs are a cornerstone of modern cloud native systems. Ensuring their reliability demands automated test suites that exercise diverse and boundary level behaviors. Nevertheless, designing such test…
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…
We analyze the changes in the training and educational efforts of the SciNet HPC Consortium, a Canadian academic High Performance Computing center, in the areas of Scientific Computing and High-Performance Computing, over the last six…
We present the first open-source implementation and evaluation of Fast Raft, a hierarchical consensus protocol designed for dynamic, distributed environments. Fast Raft reduces the number of message rounds needed to commit log entries…
Water resource management is of crucial societal and economic importance, requiring a strong capacity for anticipating environmental change. Progress in physical process knowledge, numerical methods and computational power, allows us to…
Life sciences research increasingly requires identifying, accessing, and effectively processing data from an ever-evolving array of information sources on the Linked Open Data (LOD) network. This dynamic landscape places a significant…