DFA Range Slots for Cache-Efficient Regex Acceleration

The DFA graph is segmented into multiple levels or tiers, where frequently accessed transitions are placed in smaller, faster memory (cache) and less frequently accessed transitions are placed in larger, slower memory. This hierarchical segmentation allows the system to maintain fast search performance for common patterns while reducing the immediate memory footprint by storing only essential transitions in high-speed memory.

Different portions of the DFA graph are allocated different quality characteristics based on their access frequency and importance. Hot transitions (frequently executed) are stored in high-speed cache memory with fast access times, while cold transitions (rarely executed) are stored in main memory. This local differentiation of quality allows the system to optimize for speed where it matters most while accepting slower access for less critical transitions, thereby reducing overall memory footprint requirements.

The system dynamically manages the DFA graph by loading and unloading different portions of the graph into cache memory based on runtime conditions, access patterns, and available memory. This dynamic allocation allows the system to adapt to different pattern matching workloads, loading complex pattern transitions into cache when they are needed while maintaining the ability to handle a wide variety of patterns by swapping graph portions as required.

The DFA graph implementation uses a nested structure where a core set of essential transitions is permanently resident in cache memory, while additional transitions are stored in external memory and loaded into cache as needed. This nested arrangement allows the system to maintain a minimal viable DFA in fast memory while having access to the full DFA graph stored in slower memory, effectively nesting the smaller in-cache graph within the larger overall graph structure.