构建分层动态架构，实现跨云边超算资源的智能发现与调度。
Hierarchical Server Architecture for Agentic Science
- 通过秘书代理并发异步协商、选择并分发任务请求。
- 在51个真实与模拟提供方上测试，谈判准确率达87.71%。
- 适合需要跨异构系统协作的自动化科研工作流场景。
代理科学正在重塑计算工作范式，延伸至科学流水线与工作负载管理。工作负载需依赖机构内及机构间的专用硬件。若调度需评估负载需求与环境匹配度，则资源的自动发现成为关键步骤。本文提出一种分层动态架构与软件，用于在多样化的云、边缘和高性能计算（HPC）系统中发现资源。该设计支持使用秘书代理对任务请求进行并发、异步的协商、选择与派发。代理探测并发现7类共51个真实与模拟资源提供方。通过19,973次协商与6,952次选择仿真，验证了决策可靠性，展现87.71%的高谈判准确率，且选择成本接近传统策略。该架构具备可扩展性，当前已支持Genesis Mission，体现了代理、发现工具与基础设施间协调的重要性。
原文摘要 · Abstract (English)
Agentic science is transforming the landscape of computational work, extending to scientific pipelines and workload managers. The workloads require specialized hardware within and across institutions. If assessing workload needs against environments is required for scheduling, automated discovery of resources is an essential step. In this paper, we present a hierarchical, dynamic architecture and software to discover resources across diverse cloud, edge, and HPC systems. The design enables concurrent, asynchronous negotiation, selection, and dispatch of requests for work using secretary agents. The agents probe and discover 51 real and simulated providers across 7 categories. We perform 19,973 negotiation and 6,952 selection simulations to assess reliability of decisions, demonstrating high (87.71\%) negotiation accuracy and selection costs comparable to more traditional strategies. Designed for extensibility and currently supporting the Genesis Mission, this architecture exemplifies the importance of careful coordination between agents, discovery tools, and infrastructure for agentic science.
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