Related papers: Public release of Atlas under an open source licen…
Exascale computers offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications to accelerate scientific discovery and insight. However, these software combinations and…
The need for modern data analytics to combine relational, procedural, and map-reduce-style functional processing is widely recognized. State-of-the-art systems like Spark have added SQL front-ends and relational query optimization, which…
As the Science Mission Directorate contemplates establishing an open code policy, we consider it timely to share our experiences as the developers of the open-source partial differential equation solver Dedalus. Dedalus is a flexible…
The Exascale Computing Project (ECP) was one of the largest open-source scientific software development projects ever. It supported approximately 1,000 staff from US Department of Energy laboratories, and university and industry partners.…
Pioneering data profiling systems such as Metanome and OpenClean brought public attention to science-intensive data profiling. This type of profiling aims to extract complex patterns (primitives) such as functional dependencies, data…
Interpretability is crucial for building safe, reliable, and controllable language models, yet existing interpretability pipelines remain costly and difficult to scale. Interpreting a new model typically requires training model-specific…
Nearly twenty years after the launch of AWS, it remains difficult for most developers to harness the enormous potential of the cloud. In this paper we lay out an agenda for a new generation of cloud programming research aimed at bringing…
We present the design and scalable implementation of an exascale climate emulator for addressing the escalating computational and storage requirements of high-resolution Earth System Model simulations. We utilize the spherical harmonic…
New radio interferometers such as MeerKAT, SKA, ngVLA, and DSA-2000 drive advancements in software for two key reasons. First, handling the vast data from these instruments requires subdivision and multi-node processing. Second, their…
HPC and Cloud have evolved independently, specializing their innovations into performance or productivity. Acceleration as a Service (XaaS) is a recipe to empower both fields with a shared execution platform that provides transparent access…
While widely recognized as one of the most substantial weather forecasting methodologies, Numerical Weather Prediction (NWP) usually suffers from relatively coarse resolution and inevitable bias due to tempo-spatial discretization, physical…
Recent multi-LLM agent systems have shown promising capabilities for automated problem-solving, yet they predominantly rely on frozen agents or static fine-tuning pipelines. To address this limitation, our primary contribution is ATLAS…
Derivative computation is a key component of optimization, sensitivity analysis, uncertainty quantification, and nonlinear solvers. Automatic differentiation (AD) is a powerful technique for evaluating such derivatives, and in recent years,…
Many example-guided program synthesis techniques use abstractions to prune the search space. While abstraction-based synthesis has proven to be very powerful, a domain expert needs to provide a suitable abstract domain, together with the…
The EURETILE project required the selection and coding of a set of dedicated benchmarks. The project is about the software and hardware architecture of future many-tile distributed fault-tolerant systems. We focus on dynamic workloads…
There is a continuing interest in using standard language constructs for accelerated computing in order to avoid (sometimes vendor-specific) external APIs. For Fortran codes, the {\tt do concurrent} (DC) loop has been successfully…
petitRADTRANS (pRT) is a fast radiative transfer code used for computing emission and transmission spectra of exoplanet atmospheres, combining a FORTRAN back end with a Python based user interface. It is widely used in the exoplanet…
We present a scalable, cloud-based science platform solution designed to enable next-to-the-data analyses of terabyte-scale astronomical tabular datasets. The presented platform is built on Amazon Web Services (over Kubernetes and S3…
FLASH is a publicly available high performance application code which has evolved into a modular, extensible software system from a collection of unconnected legacy codes. FLASH has been successful because its capabilities have been driven…
Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the…