Lock-Free Shared Hash Map for Embedded Systems
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Solution Overview
Problem
Existing hash map implementations face challenges with high load factors leading to increased collisions and slower performance, and concurrent access issues due to the need for resizing and synchronization primitives like locks, which are not practical in all scenarios, especially in embedded devices with fixed memory constraints.
Innovation Solution
A lock-free shared hash map implementation that provides a linearizable programmatic interface without resizing, using a shared memory segment and atomic instructions to ensure concurrent access and correct state transitions, allowing multiple threads to operate safely and efficiently without locks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the hash map is resized to maintain low load factor, then collision probability decreases and performance improves, but memory usage increases and resizing operations require synchronization locks
Solution Approach 1:
The hash map is divided into multiple independent buckets, each capable of being operated on independently by different threads. This segmentation allows concurrent access without requiring global locks, as each thread can operate on its own bucket or probe sequence without interfering with other threads' operations.
Solution Approach 2:
The patent uses an intermediary mechanism where threads operate on local copies or snapshots of bucket data rather than directly on the shared structure. This intermediary approach allows threads to perform operations locally and then apply changes atomically, avoiding the need for complex synchronization while maintaining consistency.
2Reliability
If locks are used to ensure thread safety during hash map operations, then linearizability is achieved, but concurrency is reduced and deadlock risks increase
Solution Approach 1:
Each thread independently manages its own operation state and performs self-validation of its operations. The lock-free design allows threads to detect and handle conflicts autonomously through retry mechanisms, eliminating the need for external locking control while maintaining linearizability through careful state management and atomic operations.
Solution Approach 2:
The patent replaces the mechanical locking system with atomic memory operations and compiler/memory model guarantees. Instead of using hardware or software locks to enforce mutual exclusion, the system relies on atomic read-modify-write operations and memory ordering constraints to ensure that concurrent operations appear atomic to all threads, achieving linearizability without blocking.
3Speed
If Robin-Hood hashing is used to reduce probe distance variance, then performance at high load factors improves, but the number of cache line fetches increases
Solution Approach 1:
The patent optimizes for local cache efficiency by ensuring that probe sequences access memory locations in a localized pattern. By designing the hash function and probe sequence to access nearby memory locations sequentially, the system maximizes cache line utilization and minimizes the number of cache line fetches required, even at high load factors.
Data Source
AI summary
Shared hash map implementations provide a linearizable programmatic interface to calling threads and support lock-free hash map operations. In addition to supporting lock-free operation, the shared hash map implementations are especially useful where the hash map is stored in a fixed-sized memory location such as, for example, in a shared memory segment, or in other situations where resizing the hash map is impractical or not desired.