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scx_lavd is a BPF scheduler that implements an LAVD (Latency-criticality Aware Virtual Deadline) scheduling algorithm. While LAVD is new and still evolving, its core ideas are 1) measuring how much a task is latency critical and 2) leveraging the task's latency-criticality information in making various scheduling decisions (e.g., task's deadline, time slice, etc.). As the name implies, LAVD is based on the foundation of deadline scheduling. This scheduler consists of the BPF part and the rust part. The BPF part makes all the scheduling decisions; the rust part loads the BPF code and conducts other chores (e.g., printing sampled scheduling decisions).
32 lines
1.6 KiB
Markdown
32 lines
1.6 KiB
Markdown
# scx_lavd
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This is a single user-defined scheduler used within [sched_ext](https://github.com/sched-ext/scx/tree/main), which is a Linux kernel feature which enables implementing kernel thread schedulers in BPF and dynamically loading them. [Read more about sched_ext](https://github.com/sched-ext/scx/tree/main).
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## Overview
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scx_lavd is a BPF scheduler that implements an LAVD (Latency-criticality Aware
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Virtual Deadline) scheduling algorithm. While LAVD is new and still evolving,
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its core ideas are 1) measuring how much a task is latency critical and 2)
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leveraging the task's latency-criticality information in making various
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scheduling decisions (e.g., task's deadline, time slice, etc.). As the name
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implies, LAVD is based on the foundation of deadline scheduling. This scheduler
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consists of the BPF part and the rust part. The BPF part makes all the
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scheduling decisions; the rust part loads the BPF code and conducts other
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chores (e.g., printing sampled scheduling decisions).
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## Typical Use Case
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scx_lavd is initially motivated by gaming workloads. It aims to improve
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interactivity and reduce stuttering while playing games on Linux. Hence, this
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scheduler's typical use case involves highly interactive applications, such as
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gaming, which requires high throughput and low tail latencies.
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## Production Ready?
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This scheduler could be used in a production environment where the current code
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is optimized. The current code does not particularly consider multiple NUMA/CCX
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domains, so its scheduling decisions in such hardware would be suboptimal. This
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scheduler currently will mainly perform well on single CCX / single-socket
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hosts.
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