25 papers · ranked by Valyu relevance
Zian Zhai, Xingyu Tan, Gaowang Zou, Xiaoyang Wang + 1 more
Large language model (LLM) agents increasingly rely on external tools to complete complex real-world tasks. However, reliable tool-use planning remains challenging due to the limitations of implicit reasoning and the evolving nature of real-world execution environments. Existing tool-use agents typically rely on LLMs…
Yi Ding, Kai Hu, Kai Wu, Zhenlong Zhao + 1 more
OpenMP, a typical shared memory programming paradigm, has been extensively applied in high performance computing community due to the popularity of multicore architectures in recent years. The most significant feature of the OpenMP 3.0 specification is the introduction of the task constructs to express parallelism at a…
V. R. Pascuzzi, Matteo Turilli, Shantenu Jha
Heterogeneous scientific workflows consist of numerous types of tasks that require executing on heterogeneous resources. Asynchronous execution of those tasks is crucial to improve resource utilization, task throughput and reduce workflows' makespan. Therefore, middleware capable of scheduling and executing different…
Ask Hjorth Larsen, Mikael J. Kuisma, Tara M. Boland, Fredrik A. Nilsson + 1 more
'Fredrik A. Nilsson' 'Kristian S. Thygesen'] We introduce Taskblaster, a generic and lightweight Python framework for composing, executing, and managing computational workflows with automated error handling. Taskblaster supports dynamic workflows including flow control using branches and iteration, making the system…
Authors not listed
This paper presents GLAS (Git-based Lab Automated Scheduler or Get Lab Automation Simplified), an open-source, robust, and highly expandable Git-based architecture designed for laboratory automation. GLAS can be deployed in both partially and fully automated experimental science laboratories, enabling the development…
Pedro Gonnet, Aidan B. G. Chalk, Matthieu Schaller
This paper describes QuickSched, a compact and efficient Open-Source C-language library for taskbased shared-memory parallel programming. QuickSched extends the standard dependency-only scheme of task-based programming with the concept of task conflicts, i.e. sets of tasks that can be executed in any order, yet not…
Paul Cardosi, Bérenger Bramas, Bilal Alatas
Parallelization is needed everywhere, from laptops and mobile phones to supercomputers. Among parallel programming models, task-based programming has demonstrated a powerful potential and is widely used in high-performance scientific computing. Not only does it allow efficient parallelization across distributed…
Ausaf A Farooqui, Tom Manly
Accounts of hierarchical cognition suggest that extended task episodes as one task entity and not individually execute their component acts. Such hierarchical execution is frequently thought to occur by first instantiating a sequence representation in working memory that then controls the identity and sequence of…
Pau Andrio, Adam Hospital, Cristian Ramon-Cortes, Javier Conejero + 4 more
The usage of workflows has led to progress in many fields of science, where the need to process large amounts of data is coupled with difficulty in accessing and efficiently using High Performance Computing platforms. On the one hand, scientists are focused on their problem and concerned with how to process their data.…
Bérenger Bramas, Gang Mei
Task-based programming models have demonstrated their efficiency in the development of scientific applications on modern high-performance platforms. They allow delegation of the management of parallelization to the runtime system (RS), which is in charge of the data coherency, the scheduling, and the assignment of the…
Ausaf A Farooqui, Tom Manly
The well-known deactivation of the Default Mode Network (DMN) during external tasks is usually thought to reflect the suppression of internally directed mental activity during external attention. In 3 experiments with human participants we organized sequences of task events identical in their attentional and control…
Nick Brown, Oliver Thomson Brown, J. Mark Bull
—Open-source matters, not just to the current cohort of HPC users but also to potential new HPC communities, such as machine learning, themselves often rooted in open-source. Many of these potential new workloads are, by their very nature, far more asynchronous and unpredictable than traditional HPC codes and…
A.J. Lázaro-Muñoz, José María González-Linares, Juan Gómez-Luna, Nicolás Guil
'Nicolás Guil'] A heterogeneous architecture composed by a host and an accelerator must frequently deal with situations where several independent tasks are available to be offloaded onto the accelerator. These tasks can be generated by concurrent applications executing in the host or, in case the host is a node of a…
Paul Cardosi, Bérenger Bramas
Parallelization is needed everywhere, from laptops and mobile phones to supercomputers. Among parallel programming models, task-based programming has demonstrated a powerful potential and is widely used in high-performance scientific computing. Not only does it allow for efficient parallelization across distributed…
Peter Kraus, Edan Bainglass, Francisco F. Ramirez, Enea Svaluto-Ferro + 7 more
Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by a full control of the data gathering process. In this work, we demonstrate tooling which bridges these two aspects, and illustrate its use in a case study of automated battery cycling. We…
D. Chitra Devi, V. Rhymend Uthariaraj
Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at 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…
Tamen Jadad-Garcia, Alejandro R. Jadad
Task Automation for the Integration of Artificial Intelligence into Existing Workflows Authors: ['Tamen Jadad-Garcia' 'Alejandro R. Jadad'] Driven by the rapid ascent of artificial intelligence (AI), organizations find themselves at the epicenter of a seismic shift, facing a crucial question: How can AI be successfully…
Samuel Lampa, Martin Dahlö, Jonathan Alvarsson, Ola Spjuth
The complex nature of biological data has driven the development of specialized software tools. Scientific workflow management systems simplify the assembly of such tools into pipelines and assist with job automation and aids reproducibility of analyses. Many contemporary workflow tools are specialized and not designed…
Yiqing Wang, Xiaoyan Liu, Hailong Yang, Xinyu Yang + 4 more
Priority in Task-based Runtime Systems Authors: ['Yiqing Wang' 'Xiaoyan Liu' 'Hailong Yang' 'Xinyu Yang' 'Peng Wang' 'Yi Liu' 'Zhongzhi Luan' 'Depei Qian'] As modern HPC computing platforms become increasingly heterogeneous, it is challenging for programmers to fully leverage the computation power of massive…
Helen Harman, Elizabeth I. Sklar
Multi-agent task allocation methods seek to distribute a set of tasks fairly amongst a set of agents. In real-world settings, such as soft fruit farms, human labourers undertake harvesting tasks. The harvesting workforce is typically organised by farm manager(s) who assign workers to the fields that are ready to be…
Authors not listed
Self-driving laboratories (SDLs) promise accelerated scientific discovery and product development by closing the loop between robotic execution and AI/ML-driven decision making. In practice, however, SDL orchestration remains fragmented; workflows are typically encoded as laboratory-specific scripts or bespoke…
Nathalie Liegel, Daniel Schneider, Edmund Wascher, Stefan Arnau
Most neuroscientific studies investigating mental effort apply unspecific effort allocation paradigms. In contrast, the present EEG study targets specific effort allocation during task prioritization. Twenty-eight participants performed a cued number classification task during the retention interval of a working memory…
Authors not listed
ElyteOS is a graphical user interface written in Python 3.8.3 which enables the automation of the processes of electrolyte preparation, measurement, data storage, and data visualization. It provides a user-friendly interface and acts as a framework for automating lab equipment with different commands as well as…
Wenyu Zhang, Mason Guy, Jerrica Yang, Lucy Hao + 5 more
Large Language Models (LLMs) have revolutionized numerous industries as well as accelerated scientific research. However, their application in planning and conducting experimental science, has been limited. In this study, we introduce an adaptable prompt-set with GPT-4, converting literature experimental procedures…