-
Notifications
You must be signed in to change notification settings - Fork 2.7k
fix: HiRadixCache: fix prefetch completion race #9397
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
base: main
Are you sure you want to change the base?
Conversation
Ensure can_terminate_prefetch() only considers completion when operation.hash_value is non-empty and completed_tokens == len(hash_value) * page_size, preventing premature staging under wait_complete.
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Summary of Changes
Hello @pabloiyu, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!
This pull request addresses a race condition within SGLang's hierarchical KV caching mechanism, specifically when the wait_complete
prefetch policy is active. The issue arose because the scheduler could incorrectly determine that prefetch was complete if the operation.hash_value
was empty, leading to early termination. The fix ensures that the system properly waits for the hash_value
to be populated, thereby guaranteeing that the page list is fully prepared before prefetch is considered done.
Highlights
- Fix Prefetch Completion Race Condition: Modified the
can_terminate_prefetch
method inHiRadixCache
to include a check thatoperation.hash_value
is not empty before considering the prefetch complete. This addresses a race condition where the scheduler might prematurely terminate prefetch ifhash_value
was not yet populated.
Using Gemini Code Assist
The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.
Invoking Gemini
You can request assistance from Gemini at any point in your pull request via creating an issue comment (i.e. comment on the pull request page) using either /gemini <command>
or @gemini-code-assist <command>
. Below is a summary of the supported commands.
Feature | Command | Description |
---|---|---|
Code Review | /gemini review |
Performs a code review for the current pull request in its current state. |
Pull Request Summary | /gemini summary |
Provides a summary of the current pull request in its current state. |
Comment | @gemini-code-assist | Responds in comments when explicitly tagged, both in issue comments and review comments. |
Help | /gemini help |
Displays a list of available commands. |
Customization
To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/
folder in the base of the repository. Detailed instructions can be found here.
Limitations & Feedback
Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here.
You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.
Footnotes
-
Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution. ↩
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
Code Review
This pull request addresses a race condition in HiRadixCache
's prefetch completion logic. The issue occurs when the wait_complete
policy is used, where the scheduler might check for completion before the prefetch operation's hash_value
is populated, leading to a premature completed
status. The proposed fix correctly adds a check to ensure operation.hash_value
is not empty before evaluating the completion condition. This change is concise, directly targets the described problem, and appears to be a solid fix for the race condition.
Motivation
SGLang allows for hierarchical KV caching. Under the default storage prefetch policy
best_effort
, the scheduler doesn’t have to wait for prefetch to finish: it can proceed to stage the request, which terminates the prefetch early and inserts no pages from storage. To wait for prefetch, we can usewait_complete
.However, there is a race under
wait_complete
: the scheduler can callself.tree_cache.check_prefetch_progress()
before the prefetch thread populatesoperation.hash_value
. The completion check then treats 0 completed == 0 planned as done.Fix: In
HiRadixCache.can_terminate_prefetch()
, only consider prefetch complete whenoperation.hash_value
is non-empty andoperation.completed_tokens == len(operation.hash_value) * page_size
. This ensures the scheduler waits until the page list is prepared (and withwait_complete
, until IO finishes).Modifications
Accuracy Tests
Benchmarking and Profiling
Checklist