Parallel Hash Tables are concurrent data structures that allow multiple threads to simultaneously insert, lookup, and delete key-value pairs with minimal contention — requiring careful design to avoid the serial bottleneck of a single global lock while maintaining correctness under concurrent access, with implementations ranging from simple lock-striping to sophisticated lock-free algorithms.

Concurrency Approaches

Lock Striping (Java ConcurrentHashMap approach)

• Hash table divided into S segments (stripes), each with its own lock.
• Thread acquires only the lock for the target segment → others can proceed in parallel.
• With 16 stripes: Up to 16 threads can modify different segments simultaneously.
• Java ConcurrentHashMap (Java 8+): Actually uses per-bucket CAS + synchronized blocks.

Lock-Free Hash Tables

• Use Compare-And-Swap (CAS) atomic operations — no locks at all.
• Insert: CAS to atomically place entry in bucket. If CAS fails (another thread modified) → retry.
• Resize: Most complex operation — must atomically migrate entries from old to new table.
• Split-Ordered Lists (Shalev & Shavit): Hash table where resize doesn't move elements — elements stay in a single sorted lock-free linked list, buckets are just entry points into the list.

Cuckoo Hashing (Concurrent)

• Two hash functions h1, h2 — each key has exactly 2 possible locations.
• Lookup: Check locations h1(key) and h2(key) — always O(1).
• Insert: If both locations occupied → "cuckoo" displaces one → displaced key moves to its alternate location.
• Concurrent variant: Lock-free lookups, fine-grained locks for inserts.
• Used in: Network switches (exact-match forwarding tables), GPU hash tables.

GPU Parallel Hash Tables

• Thousands of threads inserting simultaneously → need massive parallelism.
• Open addressing (linear/quadratic probing) preferred on GPUs — better memory coalescing than chaining.
• Use atomicCAS for insertion: atomicCAS(&table[slot], EMPTY, key).
• cuCollections (NVIDIA): CUDA-optimized concurrent hash maps.

Performance Characteristics

Parallel hash tables are a fundamental building block of concurrent systems — from database indexing and network packet processing to GPU-accelerated analytics, the ability to perform millions of concurrent key-value operations per second is essential for modern parallel applications.