新闻
HiCache Across Multi-Parallelism and Distributed Serving
LMSYS · 发布于 · 阅读约3分钟
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- 发生了什么
- HiCache extends KV cache reuse to host memory and external storage while maintaining consistency across context parallelism, pipeline parallelism, speculative decoding, and prefill-decode disaggregation.
- 为何重要
- Engineers deploying large language models with long-context agentic workloads where repeated request prefixes create cache reuse opportunities across distributed serving infrastructure.
- 注意
- Per-layer KV gathering adds overhead; CP sharding optimization is ongoing. Consistency across pipeline stages requires careful synchronization of asynchronous transfers to avoid tensor shape mismatches.
- serving
这条新闻背后的模式
- Speculative & Parallel Tool Execution
- Distributed Memory Architectures
- Agentic Context Engineering (Evolving Playbook)
每个模式都讲清楚技术如何运作、何时值得投入，以及在哪里会失效。
The Agent Architect
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