streaming kv cache

**Streaming KV cache** is the **KV cache management mode optimized for continuous token streams, where state is updated and served incrementally with low-latency memory operations** - it is essential for real-time interactive generation systems. **What Is Streaming KV cache?** - **Definition**: Incremental KV update pipeline aligned with streamed token generation. - **State Flow**: New token keys and values are appended while previous states remain immediately queryable. - **Runtime Focus**: Prioritizes predictable low-latency memory writes and reads per decode step. - **Integration Scope**: Works with streaming transport, cancellation, and adaptive batching logic. **Why Streaming KV cache Matters** - **Real-Time UX**: Streaming outputs require steady per-token cache performance. - **Tail-Latency Control**: Efficient incremental updates reduce jitter in token emission rates. - **Concurrency Support**: Well-managed streaming caches handle many simultaneous sessions. - **Resource Efficiency**: Avoids expensive recomputation during long streaming responses. - **Robustness**: Stable cache streaming lowers risk of stalls and dropped sessions. **How It Is Used in Practice** - **Incremental Allocator**: Use page-based or ring-buffer allocation tuned for append-heavy access. - **Session Isolation**: Track per-request cache segments to support cancellation and cleanup. - **Throughput Monitoring**: Measure token streaming smoothness alongside memory-pressure events. Streaming KV cache is **a core runtime primitive for low-latency token streaming** - optimized streaming cache operations keep interactive generation smooth and scalable.