Related papers: Making Ideas at Scientific Fabrication Laboratorie…
Simulations - utilizing computers to solve complicated science and engineering problems - are a key ingredient of modern science. The U.S. Department of Energy (DOE) is a world leader in the development of high-performance computing (HPC),…
The prevalence of software systems has become an integral part of modern-day living. Software usage has increased significantly, leading to its growth in both size and complexity. Consequently, software development is becoming a more…
Theories of innovation emphasize the role of social networks and teams as facilitators of breakthrough discoveries. Around the world, scientists and inventors today are more plentiful and interconnected than ever before. But while there are…
Emerging data-driven scientific workflows are seeking to leverage distributed data sources to understand end-to-end phenomena, drive experimentation, and facilitate important decision-making. Despite the exponential growth of available…
The study of the concept of "scientific excellence" and the methods for its measurement and evaluation is taking on increasing importance in the development of research policies in many nations. However, scientific excellence results as…
The Lean mathematical library mathlib is developed by a community of users with very different backgrounds and levels of experience. To lower the barrier of entry for contributors and to lessen the burden of reviewing contributions, we have…
The importance of innovation in the world's economy, now undeniable, draws great attention to the need to improve organizations' creative potential. In the last 60 years, hundreds of books have been written on the subject and hundreds of…
Most NLP tasks are modeled as supervised learning and thus require labeled training data to train effective models. However, manually producing such data at sufficient quality and quantity is known to be costly and time-intensive. Current…
A number of projects in computer science around the world have contributed to build federated experimental facilities providing access to a large set of distributed compute, storage and network resources for the research community. Several…
Experimental activities are an essential part of physics education. In addition to conveying scientific knowledge, they play a significant role in developing scientific literacy, inquiry skills, and critical thinking. In today's world,…
The reproducibility of scientific experiment is vital for the advancement of disciplines based on previous work. To achieve this goal, many researchers focus on complex methodology and self-invented tools which have difficulty in practical…
For many decades, formal methods are considered to be the way forward to help the software industry to make more reliable and trustworthy software. However, despite this strong belief and many individual success stories, no real change in…
The evolving landscape of scientific computing requires seamless transitions from experimental to production HPC environments for interactive workflows. This paper presents a structured transition pathway developed at OLCF that bridges the…
Learning to code, and more broadly, learning about computer science is a growing field of activity and research. Under the label of computational thinking, computational concepts are increasingly used as cognitive tools in many subject…
Machine learning (ML) is increasingly adopted in scientific research, yet the quality and reliability of results often depend on how experiments are designed and documented. Poor baselines, inconsistent preprocessing, or insufficient…
QC Lab is an open-source Python package for QC dynamics simulations aimed to promote the development of QC algorithms, and their application to a wide variety of relevant model problems. It follows a modular design that facilitates…
Computational Science on large high performance computing resources is hampered by the complexity of these systems. Much of this complexity is due to low-level details on these resources that are exposed to the application and the end user.…
The reproduction and replication of novel results has become a major issue for a number of scientific disciplines. In computer science and related computational disciplines such as systems biology, the issues closely revolve around the…
With the recent advancements in artificial intelligence, researchers and industries are deploying gigantic models trained on billions of samples. While training these models consumes a huge amount of energy, human brains produce similar…
Science has a data management problem, as well as a project management problem. While industrial-grade data science teams have embraced the agile mindset, and adopted or created all kind of tools to create reproducible workflows,…