agent/papers/items/2026-2606-16534-generated-parallel-scalable-a-study-of-agentic-ai-generated-julia-code-on-superc.md

Paper: Generated, Parallel, Scalable? A Study of Agentic AI-Generated Julia Code on Supercomputers

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type: paper title: Generated, Parallel, Scalable? A Study of Agentic AI-Generated Julia Code on Supercomputers authors: Linus Bantel, Anna-Lena Roth, Jonas Posner, Dirk Pflüger year: 2026 venue: arXiv url: https://arxiv.org/abs/2606.16534 code_url: source: arxiv collected_at: 2026-07-08 published_at: 2026-06-15 updated_at: 2026-06-16 status: queued relevance: high topics:

• agent-evaluation
• memory
• planning
• tool-use methods:

benchmarks:

models:

datasets:

• cs.DC related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 16 collection_queries: tool-use

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: tool-use
• inferred topics: agent-evaluation, memory, planning, tool-use
• arXiv categories: cs.DC
• collection score: 16

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2606.16534