Future Generation Computer

AI-Driven Scientific Computing Workflows: A Systems Review of Orchestration, Execution, Reproducibility and Provenance

Artificial intelligence (AI) is increasingly embedded within scientific computing workflows that combine simulation, data processing, optimisation, visualisation and experimental or observational components. Learned models may serve as explicit workflow components, retain persistent state and, in adaptive settings, inf...

Semantics, Workflows, and Infrastructure: Understanding Agent Serving at Production Scale

Large language model (LLM) agents execute applications through a workflow of inference requests with tool calls and user interactions. Serving these applications at production scale requires understanding how application behavior shapes inference demand and for guiding efficient execution. Recent characterization studi...

Substrate-Portable Execution for Production LLM Workflows

This work validated dozens of production agent configurations across five orchestration patterns: single-inference RAG, iterative ReAct, compositional PreAct, conditional routing, and multi-agent deep research, and found no detectable difference in output quality.

GHARuns: A Large Dataset of GitHub Actions Workflow Execution Metadata

Declare, Resolve, Reuse: A Portable Data Layer for Notebook Workflows Across HPC Systems

FAST-HEP: Compiling Declarative Analysis Workflows for High-Energy Physics and Beyond

High-energy physics analyses increasingly rely on complex software workflows whose scientific lifetime often exceeds that of the underlying software ecosystem. Maintaining reproducibility while accommodating evolving analysis software, data formats, and execution environments therefore remains a significant challenge....