WeSearch

Show HN: YieldOS-Lite – A simulator for LLM inference control-plane governance

·9 min read · 0 reactions · 0 comments · 26 views
#technology#research#simulation
Show HN: YieldOS-Lite – A simulator for LLM inference control-plane governance
TL;DR · WeSearch summary

YieldOS-Lite is a Phase 1 research simulator designed to explore resource governance for heterogeneous LLM inference workloads. It aims to determine if a slow-path governance control plane can enhance service level objectives compared to traditional scheduling methods. The simulator is not intended for production use but serves as a tool for testing governance policies before integration with actual engines.

Key facts
About this source

Hacker News (AI / LLM) files mainly under ai. We currently carry 2,817 of its stories.

Original article
GitHub
Read full at GitHub →

Story provenance

Source · retrieval · rights · ranking — open for full record
inspect →

Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.

Record

Original publisherGitHub
Canonical URLhttps://github.com/nikitph/yieldos
Publication timeMon, 25 May 2026 04:34:12 +0000
Retrieval time2026-05-25T04:42:36.051Z
Last seen2026-05-25T04:42:36.051Z
Headline sourcePublisher (no WeSearch rewrite)
Excerpt sourcepublisher body
Excerpt methodFirst ~120 words (~800 chars) of extracted publisher body, fair-use limited.
SummaryWeSearch · cerebras-chat (WeSearch summarizer)
Summary source textcontentText
Citation coverageSummary is a WeSearch-generated derivative; primary citation is the original publisher URL.
Clusterhzdx-Jr_p6G2
Cluster logicGrouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison.
Ranking reasonStory pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking.
Publisher visitYes — open original
Substitutes article?No — link-out required for full text

Rights status (four layers)

Publisher-declared
No publisher-confirmed rights record for this source yet.
Machine-readable
No source-specific machine-readable restriction detected beyond the public feed.
WeSearch interpretation
WeSearch declared handling (basis: Derived from the published RSS/Atom feed). This is WeSearch policy, not a legal grant on the publisher's behalf.
Unknown
Retrieval and training permissions are not asserted unless the publisher confirms them.

WeSearch handling by dimension

Indexing May the item be indexed (stored, ranked, made findable)? Allowed
Snippet May a short excerpt of the publisher's text be shown? Allowed
AI summary May WeSearch generate its own short summary of the article? Limited
Retrieval / RAG May the content be exposed for third-party retrieval-augmented generation? Not asserted
Model training May the content be used to train AI models? Not asserted
Commercial reuse May the content be reused commercially? Not permitted

Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.

Opening excerpt (first ~120 words) tap to expand

YieldOS-Lite MVP Simulator YieldOS-Lite is a Phase 1 research artifact for asking one question: When LLM inference workloads become heterogeneous, does a slow-path resource-governance control plane improve SLO-valid work over mechanistic schedulers such as continuous batching, chunked prefill, and prefill/decode disaggregation? This repository contains the simulator, paper draft, generated figures, experiment summaries, replay traces, and tests used to explore that question. It is meant to be easy to read cold: start with this README, skim the paper, run the smoke tests, then reproduce or extend the trace-driven experiments.

Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.

Anonymous · no account needed
Share 𝕏 Facebook Reddit LinkedIn Threads WhatsApp Bluesky Mastodon Email

Discussion

0 comments

More from GitHub