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Read-Copy-Update (RCU) can support more than fast read-mostly lookups: its building blocks can be arranged into patterns for add-only or delete-only lists, object-existence guarantees, deferred reclamation, and reader-writer-like or versioned access. These names describe design patterns, not universal replacements for locks, reference counts, or garbage collectors. The right choice depends on the data structure, reader contract, and who is responsible for object lifetime.
What is RCU?
The 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 proceed in a way that preserves the lifetime and visibility guarantees the design requires. RCU is not one single data structure or one universal usage pattern; different applications use its mechanisms differently. See the Linux kernel documentation on RCU for the conceptual overview and implementation-specific guidance.
At a high level, RCU designs combine pointer publication and subscription with a way to wait for readers that were already active. The Linux Foundation’s companion fundamentals session identifies rcu_assign_pointer() and rcu_dereference() as the publication and subscription operations, and rcu_read_lock(), rcu_read_unlock(), and synchronize_rcu() as part of the reader/waiting relationship. This is a conceptual sketch, not a complete API safety guide: valid usage depends on the RCU flavor, object type, and surrounding synchronization.
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The Linux Foundation’s additional-use-cases session, recorded February 23, 2022, lists several patterns built around linked publish/subscribe and waiting for readers to finish. The session page says it covers as many as time permits, so the list is a set of possible use cases rather than a claim that the recording exhaustively explains every one. Its official slide deck presents the patterns in that same conceptual frame.
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Add-only lists
An add-only list is a natural fit when entries are published over time but not removed during the relevant lifetime of the structure. Readers can traverse published entries, while writers add new ones using the appropriate update protocol. The simplicity depends on the actual contract: an application still needs to handle initialization, publication ordering, and any other writer coordination the list requires.
Delete-only lists
A delete-only list starts with entries already present and removes them without adding new ones in the relevant operating phase. RCU’s grace-period mechanism can help ensure that a removed entry is not reclaimed while a pre-existing reader might still be using it. Removal from the visible structure and freeing the object’s memory are separate concerns; the reclamation design must respect the reader lifetime.
Existence guarantees
Some readers need to establish that an object exists and remains usable for the operation they are performing, rather than simply find a pointer and assume its lifetime. RCU can be part of a design that provides such an existence guarantee, but the exact guarantee must be stated precisely: what keeps the object valid, for how long, and what happens if a concurrent update removes or replaces it?
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Type-safe memory and lightweight garbage collection
The session also lists type-safe memory and a lightweight garbage collector. These labels point to memory-lifetime patterns in which RCU’s ability to wait for pre-existing readers can help defer reclamation. They should not be read as meaning that RCU automatically manages arbitrary allocations or replaces a general-purpose garbage collector. The object layout, allocation scheme, update path, and reclamation callback or waiting mechanism all matter.
Quasi reader-writer lock variants
RCU can support designs with behavior analogous to reader-writer locking, including variants named in the session. “Quasi” matters: this is an analogy, not a promise that RCU has the same locking semantics. A design must specify how writers serialize, what readers may observe during updates, and whether readers can sleep or otherwise block under the selected API contract.
Quasi multi-version consistency control
A quasi multi-version design can allow readers to work with a version while an update publishes another version, with old data retained until readers that could have seen it are finished. This can be useful when the consistency contract permits readers to observe a stable version rather than coordinate directly with every update. It does not by itself establish that all related fields form a transactionally consistent snapshot; that guarantee must come from the complete design.
Quasi reference counts
The session’s quasi-reference-count pattern uses RCU as part of reasoning about whether an object is still in use. It is not a general drop-in reference counter: reference-count semantics, acquisition races, and final reclamation must be handled according to the specific API and object-lifetime rules.
How should you choose among these patterns?
The webinar’s list does not rank the patterns or provide a universal selection rule. Use the following engineering questions to narrow the design, then confirm the details in the documentation for the kernel or userspace environment you target.
- Mutation pattern: Are entries only added, only deleted, or both added and removed?
- Reader contract: Must a reader merely find an object, guarantee it remains usable, inspect a stable version, or coordinate with writers in a lock-like way?
- Lifetime and reclamation: Which readers may still hold a reference after an update, who waits for them, and which mechanism eventually frees the old object?
- Consistency: Is it acceptable for a reader to see one coherent version while an update publishes another, or does the operation require a stronger synchronization relationship?
- API and complexity: Does the target environment provide the RCU flavor and API contract the design needs, and can the team safely maintain the added lifetime and update logic?
For implementation caveats, API usage, examples, and RCU-specific constraints, consult the official kernel RCU documentation. The additional-use-cases session is an educational overview, not a workload benchmark or a recommendation that one pattern is faster or better in every setting.
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