Atomic Views: Building Concurrent Data Structures with Read-Modify-Write

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Author: Denis Avetisyan

This research details how to create highly concurrent data structures using only basic read and write operations, providing a foundation for scalable shared memory systems.

The paper presents wait-free, linearizable algorithms for read-modify-writable snapshots with unbounded concurrency using only shared memory read/write operations.

While strong low-level primitives like compare&swap are typically required for constructing concurrent snapshots of shared memory, their necessity remains an open question. This paper, ‘Read-Modify-Writable Snapshots from Read/Write operations’, investigates whether read-modify-writable (RMWable) snapshots-allowing complex operations on shared data-can be realized using only fundamental read/write operations. We present two wait-free, linearizable algorithms achieving this, functioning both with a finite number of processes and in systems supporting unbounded concurrency. Could these results pave the way for more practical and efficient concurrent data structures in weakly-ordered memory models?

The Foundations of Consistent Data Access

The very foundation of modern computing relies on the ability of multiple processors to access and modify shared memory simultaneously, enabling speed and efficiency in complex tasks. However, this concurrent access introduces a critical challenge: maintaining data consistency. Without careful management, these simultaneous operations can lead to race conditions and corrupted data, requiring sophisticated mechanisms to ensure that all processors operate on accurate and up-to-date information. This isn’t merely a technical hurdle; it’s a fundamental constraint influencing the design of everything from multi-core processors to large-scale distributed systems, demanding constant innovation in synchronization primitives and memory management techniques to unlock the full potential of parallel computing.

Snapshot algorithms, while foundational in managing concurrent access to shared memory, operate by creating a static, point-in-time copy of the data. This approach, though simple to implement, presents limitations when applications require more than just a consistent read; complex transactional operations-like conditional updates or multi-step calculations-become significantly less efficient. Each transaction might necessitate a new, complete snapshot, leading to substantial overhead in both time and computational resources. Consequently, applications demanding frequent, intricate interactions with shared memory often find traditional snapshot techniques inadequate, prompting research into more dynamic and granular consistency mechanisms that can minimize redundant data copying and optimize performance for complex operations.

Extending Snapshot Functionality with Read-Modify-Write Access

RMWable Snapshots extend traditional snapshot capabilities by permitting read-modify-write operations on shared memory data within a consistent snapshot. Unlike read-only snapshots, RMWable Snapshots allow concurrent processes to not only observe a consistent state of shared memory but also to perform atomic updates to that data as seen from the perspective of the snapshot. This is achieved by isolating modifications within the snapshot’s view, ensuring that operations appear atomic even when composed of multiple read and write actions. The resulting consistent view is then made available to other processes, facilitating complex, concurrent data manipulation without requiring global locks or complex synchronization primitives.

RMWable Snapshots extend the capabilities of traditional snapshot algorithms by incorporating read-modify-write operations. Conventional snapshot algorithms typically provide consistent read-only views of data; RMWable Snapshots build upon this foundation to enable concurrent data manipulation within those views. This is achieved by ensuring that all operations within a snapshot are atomic with respect to external changes, effectively providing a mechanism for optimistic concurrency control. By allowing modifications within the snapshot’s consistent view, RMWable Snapshots offer a more powerful approach to managing concurrent access to shared memory, exceeding the limitations of read-only snapshots and enabling complex transactional operations.

RMWable Snapshots utilize atomic Read and Write operations to ensure data manipulation within a snapshot remains consistent and isolated from concurrent modifications to the underlying shared memory. These atomic operations guarantee that each Read returns a complete and accurate value, while each Write either completes entirely or has no effect, preventing partial updates. The implementation relies on these fundamental building blocks to create a consistent view of data for snapshot users, allowing for complex data modifications within the snapshot without introducing race conditions or data corruption in the live shared memory region. This approach enables the creation of snapshots that not only reflect a point-in-time image but also facilitate read-modify-write operations within that isolated context.

Performance Considerations: Optimizing Atomic Operations

RMWable Snapshot (Read-Modify-Write) performance is fundamentally constrained by the efficiency of scan and update operations performed on shared memory. These operations require direct access to the same memory locations by multiple concurrent processes or threads. The speed at which these scans and updates can be completed directly impacts the overall throughput and latency of the RMWable Snapshot system. Inefficient scans, requiring sequential access to large memory regions, or slow update mechanisms, due to contention or locking, create bottlenecks. Optimizing these core operations is therefore paramount to achieving scalable and responsive RMWable Snapshot implementations, as they form the basis for all data modification workflows.

The Collect Operation improves scan efficiency by retrieving multiple data elements in a single memory access, reducing the total number of read operations required during a scan. Simultaneously, the T Register serves as a dedicated tracking mechanism for update progress; it stores information regarding the current stage of an update, allowing the system to monitor completion and handle concurrent modifications. These two techniques work in concert; the T Register informs the Collect Operation of which data elements require updating, and the Collect Operation efficiently retrieves and modifies those elements, thereby minimizing contention and maximizing throughput in RMWable Snapshot implementations.

Atomic operations, specifically Compare & Swap (CAS) and Load-Link/Store-Conditional (LL/SC), are fundamental to maintaining data consistency in multi-threaded environments accessing shared memory. CAS works by conditionally swapping a value at a memory location only if the current value matches an expected value, preventing race conditions during updates. LL/SC, conversely, utilizes a two-step process: LL reserves exclusive access to a memory location, and SC conditionally stores a new value only if no other thread has intervened since the LL instruction. Both mechanisms ensure that read and write operations appear indivisible, guaranteeing that updates are completed without interference and preventing data corruption, which is particularly crucial for RMWable Snapshot implementations where concurrent access and modification of shared data are inherent.

Towards Scalability: Enhancing Efficiency with Partial Snapshots and Wait-Freedom

Traditional snapshot algorithms often capture the entire memory state, incurring significant overhead even when only a small portion of the data is relevant to a particular operation. Partial snapshots address this inefficiency by selectively capturing only the data necessary for completing the current transaction, extending the conventional Scan operation to focus on relevant memory locations. This targeted approach drastically reduces the amount of data read and written during snapshot creation, improving performance, particularly in systems with large shared memory spaces. By intelligently identifying and capturing only the actively used data, partial snapshots minimize contention and communication costs, leading to a more efficient and responsive system. This optimization is crucial for scaling concurrent applications and maintaining low latency under heavy load.

RMWable snapshots attain wait-freedom through a carefully orchestrated interplay between optimized scan and update operations, augmented by the innovative use of an H Register. This register functions as a crucial assistant during snapshot creation, effectively tracking modifications to shared memory without requiring global synchronization. By leveraging the H Register, the system avoids the pitfalls of contention that often plague traditional snapshot algorithms, ensuring that each process can complete its operation in a finite number of steps, regardless of the actions of other concurrent processes. This design ensures responsiveness and prevents indefinite postponement, even under high levels of concurrency, representing a significant advancement in shared memory synchronization techniques.

The architecture achieves a crucial property known as wait-freedom, operating effectively within an unbounded concurrency model where any process can complete its operation in a finite number of steps without relying on the progress of others – a significant advancement for system responsiveness. Algorithm 4 demonstrates this capability with a quantifiable step complexity of O(n^2 * m), where ‘n’ represents the number of concurrent processes and ‘m’ denotes the size of the shared memory being accessed. Furthermore, the implementation maintains a space complexity of O(n^2 + nm), outlining the resources required to support these concurrent operations and ensuring scalability even as the number of processes and data volume increase.

The pursuit of wait-free algorithms, as detailed in this work concerning RMWable snapshots, echoes a fundamental tenet of robust system design. If the system looks clever, it’s probably fragile-and complexity is the enemy of reliability. Tim Berners-Lee observed, “The Web is more a social creation than a technical one.” This rings true; elegant solutions, like those prioritizing linearizability with shared memory, aren’t born from intricate mechanisms but from a clear understanding of interaction and a commitment to simplicity. The paper’s focus on unbounded concurrency demands a structure that anticipates, rather than reacts, illustrating that architecture is, indeed, the art of choosing what to sacrifice-in this case, potentially sacrificing performance for guaranteed progress.

Future Directions

The pursuit of wait-free linearizability, particularly from such constrained primitives as simple read/write operations, inevitably reveals the brittleness inherent in many concurrent data structures. This work demonstrates a path forward, but it’s crucial to recognize this isn’t a demolition, but rather a careful renovation. The algorithms presented should be viewed as infrastructural components – a robust foundation upon which more complex systems can be built, allowing for incremental improvements without wholesale reconstruction.

A natural extension lies in exploring the performance characteristics of these RMWable snapshots under varying contention levels. While wait-freedom is a strong guarantee, its cost is rarely negligible. Understanding the trade-offs between contention, latency, and throughput is paramount. Furthermore, the current algorithms operate on relatively simple data models; scaling these principles to more complex, nested structures-and considering the implications for memory management-represents a significant challenge.

Ultimately, the field needs to shift from seeking universally ‘correct’ algorithms to embracing systems that evolve gracefully. A truly elegant solution acknowledges that concurrency is not a problem to be solved, but a condition to be managed. The goal should not be to eliminate conflict, but to build systems that accommodate it – that permit change and adaptation without catastrophic failure.

Original article: https://arxiv.org/pdf/2602.16903.pdf

Contact the author: https://www.linkedin.com/in/avetisyan/

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2026-02-22 16:36