相关论文: A Serverless Tool for Platform Agnostic Computatio…
Since 2013, the PULP (Parallel Ultra-Low Power) Platform project has been one of the most active and successful initiatives in designing research IPs and releasing them as open-source. Its portfolio now ranges from processor cores to…
Recent developments in data management and imaging technologies have significantly affected diagnostic and extrapolative research in the understanding of neurodegenerative diseases. However, the impact of these new technologies is largely…
Large Eddy Simulation is a critical modelling tool for the investigation of atmospheric flows, turbulence and cloud microphysics. The models used by the UK atmospheric research community are homogeneous and the latest model, MONC, is…
The rapid growth of scientific data is surpassing advancements in computing, creating challenges in storage, transfer, and analysis, particularly at the exascale. While data reduction techniques such as lossless and lossy compression help…
For large-scale scientific simulations, it is expensive to store raw simulation results to perform post-analysis. To minimize expensive I/O, "in-situ" analysis is often used, where analysis applications are tightly coupled with scientific…
The use of edge computing can be extremely valuable in support of CPS efforts. However, few if any testbeds provide the type of resource control and provisioning required to support edge-enabled CPS experimentation. Likewise, commercial…
Scientific simulation leveraging high-performance computing (HPC) systems is crucial for modeling complex systems and phenomena in fields such as astrophysics, climate science, and fluid dynamics, generating massive datasets that often…
Abstruse learning algorithms and complex datasets increasingly characterize modern clinical decision support systems (CDSS). As a result, clinicians cannot easily or rapidly scrutinize the CDSS recommendation when facing a difficult…
We provide a user-friendly, flexible, and lightweight open-source HCI toolkit (github.com/QButterfly) that allows non-tech-savvy researchers to conduct online user interaction studies using the widespread Qualtrics and LimeSurvey platforms.…
Research in Mobile Location-Based Crowdsourcing is hindered by a marked lack of real-world data. The development of a standardized, lightweight, easily deployable, modular, composable, and most of all, scalable experimentation framework…
HTCondor has been very successful in managing globally distributed, pleasantly parallel scientific workloads, especially as part of the Open Science Grid. HTCondor system design makes it ideal for integrating compute resources provisioned…
In January 2026, the open-source agent framework OpenClaw and the agent-only social network Moltbook produced a large-scale dataset of autonomous AI-to-AI interaction, attracting six academic publications within fourteen days. This study…
Across many domains, large swaths of digital assets are being stored across distributed data repositories, e.g., the DANDI Archive [8]. The distribution and diversity of these repositories impede researchers from formally defining…
Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools, a complex software stack, as well as large and scalable compute and data analysis resources…
Adapting the cloud for high-performance computing (HPC) is a challenging task, as software for HPC applications hinges on fast network connections and is sensitive to hardware failures. Using cloud infrastructure to recreate conventional…
Recently, a number of cloud platforms and services have been developed for data intensive computing, including Hadoop, Sector, CloudStore (formerly KFS), HBase, and Thrift. In order to benchmark the performance of these systems, to…
A neural-networks predictor library has been developed to deploy machine learning (ML) models into computational fluid dynamics (CFD) codes. The pointer-to-implementation strategy is adopted to isolate the implementation details in order to…
Large-scale ad hoc analytics of genomic data is popular using the R-programming language supported by 671 software packages provided by Bioconductor. More recently, analytical jobs are benefitting from on-demand computing and storage, their…
The proliferation of sensor technologies and advancements in data collection methods have enabled the accumulation of very large amounts of data. Increasingly, these datasets are considered for scientific research. However, the design of…
Containers are an emerging technology that hold promise for improving productivity and code portability in scientific computing. We examine Linux container technology for the distribution of a non-trivial scientific computing software stack…