相关论文: Pixi: Unified Software Development and Distributio…
Conducting research often involves managing multiple disconnected tools for survey design, data collection, response analysis, and report generation, leading to inefficiencies, increased error risks, and challenges in ensuring…
Small to medium-scale data science experiments often rely on research software developed ad-hoc by individual scientists or small teams. Often there is no time to make the research software fast, reusable, and open access. The consequence…
In this paper, we discuss the need for an integrated software stack that unites artificial intelligence (AI) and modeling and simulation (ModSim) tools to advance scientific discovery. The authors advocate for a unified AI/ModSim software…
In an era where we can not afford to checkpoint frequently, replication is a generic way forward to construct numerical simulations that can continue to run even if hardware parts fail. Yet, replication often is not employed on larger…
Scientific knowledge increasingly depends on complex computational processes where both hardware and software layers can influence research outcomes. As computational complexity grows, classical-quantum integration provides a lens for…
Replication crises have shaken the scientific landscape during the last decade. As potential solutions, open science practices were heavily discussed and have been implemented with varying success in different disciplines. We argue that…
Computing systems rarely deliver best possible performance due to ever increasing hardware and software complexity and limitations of the current optimization technology. Additional code and architecture optimizations are often required to…
Edge and Fog computing paradigms overcome the limitations of cloud-centric execution for different latency-sensitive Internet of Things (IoT) applications by offering computing resources closer to the data sources. Small single-board…
Online artificial intelligence (AI) algorithms are an important component of digital health interventions. These online algorithms are designed to continually learn and improve their performance as streaming data is collected on…
Science depends on collaboration, result reproduction, and the development of supporting software tools. Each of these requires careful management of software versions. We present a unified model for installing, managing, and publishing…
Applications in science and engineering often require huge computational resources for solving problems within a reasonable time frame. Parallel supercomputers provide the computational infrastructure for solving such problems. A…
Performance is one of the most important qualities of software. Several techniques have thus been proposed to improve it, such as program transformations, optimisation of software parameters, or compiler flags. Many automated software…
Simulations with high accuracy are an essential part of scientific research to accelerate the innovation process. They are especially useful for finding novel approaches or optimizing existing methods. Today, powerful software tools are…
This report synthesizes findings from the November 2024 Community Workshop on Practical Reproducibility in HPC, which convened researchers, artifact authors, reviewers, and chairs of reproducibility initiatives to address the critical…
Computational analysis has become ubiquitous within the heliophysics community. However, community standards for peer-review of codes and analysis have lagged behind these developments. This absence has contributed to the reproducibility…
Cross-platform robot control remains difficult because hardware interfaces, data formats, and control paradigms vary widely, which fragments toolchains and slows deployment. To address this, we present Control Your Robot, a modular,…
Recent reproducibility case studies have raised concerns showing that much of the deposited research has not been reproducible. One of their conclusions was that the way data repositories store research data and code cannot fully facilitate…
Robot task execution when situated in real-world environments is fragile. As such, robot architectures must rely on robust error recovery, adding non-trivial complexity to highly-complex robot systems. To handle this complexity in…
Self-adaptive robotic systems operate autonomously in dynamic and uncertain environments, requiring robust real-time monitoring and adaptive behaviour. Unlike traditional robotic software with predefined logic, self-adaptive robots exploit…
Scientific workflow has become essential in software engineering because it provides a structured approach to designing, executing, and analyzing scientific experiments. Software developers and researchers have developed hundreds of…