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Read-Copy-Update (RCU) can support more than read-mostly lookups. Linux kernel developers use RCU’s pointer-publication and reader-waiting mechanisms as building blocks for patterns including add-only or delete-only lists, existence guarantees, deferred reclamation, and several lock- or versioning-like designs. These are patterns, not universal drop-in replacements: the right choice depends on the data structure’s mutation rules, the consistency readers need, and how old objects are reclaimed.
What is RCU?
Linux kernel documentation describes RCU as a synchronization mechanism optimized for read-mostly situations. Its central idea is to let readers access published data while updates are arranged so that readers already in progress can finish before an old object is reclaimed. The exact APIs and guarantees depend on the use case, so the kernel documentation cautions against treating RCU as one universal recipe.
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At a conceptual level, the reader subscribes to a published pointer, and an updater can wait for pre-existing readers to pass through their read-side sections. The fundamentals session introduces rcu_assign_pointer() and rcu_dereference() for pointer publication and subscription, alongside rcu_read_lock(), rcu_read_unlock(), and synchronize_rcu() for the reader/waiting relationship. This overview is not a complete API safety guide; implementation requires the contract for the specific RCU flavor and data structure.
The official Linux kernel documentation on RCU offers a conceptual overview, core API guidance, example uses, implementation material, and discussions of analogies to reader-writer locking and reference counting. The companion fundamentals session introduces the core mechanisms.
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What additional uses does the RCU session identify?
The Linux Foundation’s Additional Use Cases session, recorded February 23, 2022, lists these possibilities. Its page says the talk begins with a brief review and covers as many use cases as time allows, so the list should not be read as a claim that the recording exhaustively explains each one.
- Add-only lists and delete-only lists.
- Existence guarantees.
- Type-safe memory and lightweight garbage collection.
- Quasi reader-writer lock variants.
- Quasi multi-version consistency control.
- Quasi reference counts.
The official slide deck frames these patterns around linked publication/subscription and waiting for readers to finish. That framing helps explain how higher-level behavior can be assembled from RCU’s basic pieces; it does not establish a performance ranking or quantitative advantage.
How do the patterns differ?
Add-only and delete-only lists
These names describe mutation patterns: one design permits additions without removals, while another focuses on deletion. Restricting which changes can occur may simplify the surrounding design, but it does not by itself answer how readers find entries, how concurrent updates are serialized, or when storage can be reused. Those details must be specified for the actual list and kernel APIs.
Existence guarantees
An existence guarantee concerns whether an object remains present for a reader’s operation. It is distinct from guaranteeing that every field remains unchanged or that the reader sees the newest state. The implementation must define what “exists” means for the operation and coordinate updates and lifetime accordingly.
Type-safe memory and lightweight garbage collection
RCU’s ability to defer reclamation until relevant pre-existing readers have finished can contribute to memory-lifetime schemes, including type-safe memory handling and lightweight garbage collection. It is not a general-purpose garbage collector: a design still needs to identify retired objects, determine when reclaiming them is safe, and perform reclamation through an appropriate mechanism.
Quasi reader-writer lock variants
Some RCU designs can provide behavior analogous to reader-writer locking, with additional variants. “Quasi” matters: the analogy does not mean that RCU automatically supplies the same blocking, writer exclusion, fairness, or consistency contract as a particular lock. Establish precisely which operations readers and writers may perform and what they must observe.
Quasi multi-version consistency control
Versioned data can let readers continue using an older published view while an updater prepares or publishes a newer one. Whether that is acceptable depends on the application’s consistency contract: a reader may be allowed a coherent older version, or it may need stronger coordination with writers. RCU does not make those requirements interchangeable.
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Quasi reference counts
Reference-count-like behavior is another analogy, not a claim that RCU replaces every reference count. Reference counts and RCU address object lifetime in different ways; whether a hybrid or alternative is suitable depends on how references are acquired, released, and protected against races with removal.
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How should you choose an RCU pattern?
The webinar’s list does not establish a universal selection rule or validated head-to-head benchmark. Use the following questions to define the design problem before choosing a pattern:
- Mutation pattern: Is the structure append-only, delete-only, or subject to both additions and removals?
- Reader needs: Must a reader establish that an object exists, inspect a stable version, or coordinate with writers in a lock-like way?
- Lifetime and reclamation: Which mechanism waits for pre-existing readers, and which thread or mechanism ultimately reclaims retired objects?
- Consistency contract: Can readers use a quasi multi-version view, or do they need stronger synchronization with updates?
- API and environment: Does the specific kernel or userspace environment support the RCU flavor and API contract the design requires?
After answering these questions, check the relevant sections of the kernel RCU documentation for the implementation’s API and caveats. The additional-use-cases session is useful for recognizing design possibilities, not for deciding safety or suitability on its own.
What does the session establish?
The dated session provides an educational tour of additional RCU use-case categories, not a current benchmark or a guarantee that every pattern suits a particular workload. Its page names Paul E. McKenney as the speaker and describes his role at the time as a software engineer at Facebook; the associated slides use the Meta Platforms label. Those are source-era attributions, not claims about his present employer.
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