25 papers · ranked by Valyu relevance
Jeremy Li, Alex Rubinsteyn, Sergey Feldman, Timothy O’Donnell + 18 more
Scientific computing has become a central component of modern scientific discovery. Yet many computational tools are developed by small, specialized teams under incentives that encourage the release of rapidly prototyped tooling without commensurate attention to engineering concerns, including performance and…
Stefano Bianchini, Aldo Geuna, Fazliddin Shermatov
Artificial intelligence (AI) and high-performance computing (HPC) are rapidly becoming the engines of modern science. However, their joint effect on discovery has yet to be quantified at scale. Drawing on metadata from over five million scientific publications (2000–2024), we identify how AI and HPC interact to shape…
Sottile, Matthew, Tekriwal, Mohit + 2 more
Correctness in scientific computing (SC) is gaining increasing attention in the formal methods (FM) and programming languages (PL) community. Existing PL/FM verification techniques struggle with the complexities of realistic SC applications. Part of the problem is a lack of a common understanding between the SC and…
Weicheng Xue, Kai Yang, Yongxiang Liu, Baisong Xu + 4 more
The rapid rise of AI-oriented accelerators has reshaped compute systems around low-precision tensor engines, raising a practical question for the HPC community: under what conditions can such hardware support scientific workloads that demand numerical robustness, irregular memory access, and scalability? Using the…
Authors not listed
Agentic artificial intelligence (AI) is poised to redefine how science is conducted, automating not just data analysis but the entire research lifecycle, from hypothesis generation to validation. Yet most current AI agents remain domain-bound, tailored to specific applications such as materials synthesis or quantum…
Harinarayan Krishnan, Shubhabrata Mukerjee, Jeffrey Donatelli, Daniela Ushizima
The increasing complexity of modern computational environments often burdens researchers with infrastructure management, authentication protocols, and container deployments. We present Sci-Orchestra, a layered orchestration framework designed to fully automate experimental workflows, allowing scientists to prioritize…
Eric W. Bridgeford, Iain Declan Campbell, Zijiao Chen, Zhicheng Lin + 4 more
While AI coding tools have demonstrated potential to accelerate software development, their use in scientific computing raises critical questions about code quality and scientific validity. In this paper, we provide twelve practical tips for AI-assisted coding that balance the capabilities of AI with the demands of…
Authors not listed
Computational chemistry has entered a new era where machine learning (ML) models—particularly graph neural networks and machine learning force fields—routinely deliver quantum mechanical accuracy at classical speeds, scaling to millions of atoms and reshaping workflows in drug discovery, catalysis, and materials…
Authors not listed
We describe a collaborative research project spanning the disciplines of quantum hardware, quantum algorithms, conventional computational chemistry, synthetic medicinal chemistry and life sciences. Our project seeks to demonstrate an impact of quantum computing on human health. It is one of several funded by Wellcome…
William C. Regli, Rajmohan Rajaraman, Daniel Lopresti, David Jensen + 4 more
Computing is now an indispensable component of nearly all technologies and is ubiquitous for vast segments of society. It is also essential to discoveries and innovations in most disciplines. However, while past grand challenges in science have involved computing as one of the tools to address the challenge, these…
Xaver Stiensmeier, Alexander Kanitz, Jan Krüger, Santiago Insua + 11 more
- We identify the challenges of navigating a fragmented ecosystem of computing environments between research infrastructures, NRENs, and commercial clouds, and position hybrid cloud architectures as a solution to balance performance, cost, scalability, and accessibility. - We describe deployment models and workflow…
Authors not listed
The rapid growth of worldwide computing power has transformed in silico chemistry into a discipline that is integrated into the daily work of many chemists. Nowadays, researchers find it increasingly straightforward to predict a wide range of molecular properties and chemi- cal processes at reasonable computational…
A. Sina Booeshaghi, Laura Luebbert, Lior Pachter
We develop a machine-automated approach for extracting results from papers, which we assess via a comprehensive review of the entire eLife corpus. Our method facilitates a direct comparison of machine and peer review, and sheds light on key challenges that must be overcome in order to facilitate AI-assisted science. In…
Juraj Gottweis, Wei-Hung Weng, Alexander Daryin, Tao Tu + 47 more
Title: Summary Scientific discovery is driven by scientists generating novel hypotheses for complex problems that undergo rigorous experimental validation. To augment this process, we introduce Co-Scientist, a multi-agent AI system built on Gemini for structured scientific thinking and hypothesis generation.…
VP Nagraj, Stephen D Turner, Neal Magee
Containerization enables portable, reproducible, and scalable scientific computing. However, container development, documentation, and deployment practices can vary widely, even within a single domain. Understanding patterns of how containers are implemented in real-world settings can inform community guidelines…
Peter G. Hawkins, Eli M. Swanson, Megan Feichtel
The size of individual single cell samples continues to grow with advancing technologies, as do the number of samples included in individual experiments and across organizations. This presents challenges for processing this data at scale, both in terms of computational throughput and the required size of the machines…
Federico Marotta, Oliver Stolpe, Benedikt Obermayer, January Weiner + 3 more
In many bioinformatic data analysis projects, it is convenient to visualize plots and results through an interactive web app or dashboard. These interactive reports can then be shared with customers, collaborators, or the general public. Publishing and sharing these apps is not straightforward, becoming especially…
Sumir Panji, Verena Ras, Judy Gichoya, Rolanda Julius + 6 more
Data Science can revolutionize biomedical sciences, and ultimately, health. However, this relies on core elements, including computing infrastructure, data science skills, and well-curated contextually relevant data, which are limited in low- and middle-income countries. Many big data biomedical projects that have…
Authors not listed
The increasing importance and predictive power of modern molecular modeling, driven by physics- and machine learning-based methods, necessitates a new collaborative architecture to replace the isolated, traditional model of software development. The traditional approach often led to redundant engineering effort, high…
Anna-Lena Roth, Jonas Posner
The growing importance of High-Performance Computing (HPC) requires the systematic integration of parallel programming and performance-oriented competencies into computational science curricula. Effective HPC education combines theoretical foundations with practical experience on real cluster infrastructures, enabling…
Manuel Parra-Royón, Julián Garrido-Sánchez, Susana Sánchez-Expósito, Laura Darriba-Pol + 8 more
The distributed architecture of the SKA Regional Centre Network (SRCNet) aims to provide scientific communities worldwide with efficient computational and storage resources to exploit the massive data volumes produced by the SKA Observatory (SKAO). Given the amount of SKAO data, traditional data management paradigms -…
Vaughan C Turekian
The conduct of science is entering a new phase, shaped by the convergence of AI, high-performance computing, and increasingly automated experimental systems. While discovery continues to rely on theory and experiment, it is increasingly augmented by integrated platforms that link data, models, computing, and…
Jing Li, Leyi Wei, Henry H Y Tong, Quan Zou
In early drug discovery, virtual screening based on deep learning, virtual screening based on molecular docking, and molecular dynamics are three widely used computational strategies, but they always face a trade-off between throughput, search stability, and physical fidelity. This article discusses how quantum…
Michael L. Helde, Alexander G. Dimitrov
We adapted an olfactory neuromorphic algorithm to image and sound recognition. To achieve this, we carried out specific preprocessing procedures that were tailored to each modality. For images, we used the NIST digits dataset directly. For sound, we used samples from the Google Speech Command dataset. A gammatone…
Caiseal Beardow, Pieter Jan Stappers
In recent years, the quantum computing industry has seen significant investment and growth. However, this burgeoning industry faces a persistent labour gap: individuals with computing expertise, an understanding of quantum principles, and the ability to apply these principles to computing practices, are in increasing…