https://answer.freetools.me/tags/%E5%86%85%E5%AD%98%E4%BC%98%E5%8C%96/ Recent content in 内存优化 on Answer Hugo -- 0.152.2 zh-cn Thu, 12 Mar 2026 00:32:19 +0800 https://answer.freetools.me/kv-cache%E4%B8%BA%E4%BB%80%E4%B9%88%E8%BF%99%E4%B8%AA%E7%BC%93%E5%AD%98%E5%86%B3%E5%AE%9A%E4%BA%86%E5%A4%A7%E6%A8%A1%E5%9E%8B%E6%8E%A8%E7%90%86%E7%9A%84%E9%80%9F%E5%BA%A6%E5%92%8C%E6%88%90%E6%9C%AC/ Thu, 12 Mar 2026 00:32:19 +0800 https://answer.freetools.me/kv-cache%E4%B8%BA%E4%BB%80%E4%B9%88%E8%BF%99%E4%B8%AA%E7%BC%93%E5%AD%98%E5%86%B3%E5%AE%9A%E4%BA%86%E5%A4%A7%E6%A8%A1%E5%9E%8B%E6%8E%A8%E7%90%86%E7%9A%84%E9%80%9F%E5%BA%A6%E5%92%8C%E6%88%90%E6%9C%AC/ 深入解析大模型推理中KV Cache的工作原理、内存消耗计算、PagedAttention优化、GQA架构演进，以及如何在实际部署中进行容量规划。 https://answer.freetools.me/kv-cache%E5%8E%8B%E7%BC%A9%E5%A6%82%E4%BD%95%E8%AE%A9%E5%A4%A7%E6%A8%A1%E5%9E%8B%E7%AA%81%E7%A0%B4%E7%99%BE%E4%B8%87token%E4%B8%8A%E4%B8%8B%E6%96%87%E4%BB%8Eattention-sink%E5%88%B0heavy-hitter%E7%9A%84%E6%8A%80%E6%9C%AF%E7%AA%81%E5%9B%B4/ Mon, 09 Mar 2026 07:49:36 +0800 https://answer.freetools.me/kv-cache%E5%8E%8B%E7%BC%A9%E5%A6%82%E4%BD%95%E8%AE%A9%E5%A4%A7%E6%A8%A1%E5%9E%8B%E7%AA%81%E7%A0%B4%E7%99%BE%E4%B8%87token%E4%B8%8A%E4%B8%8B%E6%96%87%E4%BB%8Eattention-sink%E5%88%B0heavy-hitter%E7%9A%84%E6%8A%80%E6%9C%AF%E7%AA%81%E5%9B%B4/ 深入解析KV Cache压缩技术如何突破大模型推理的内存瓶颈。从StreamingLLM的Attention Sink到H2O的Heavy Hitter，从KIVI的非对称量化到KVQuant的超低比特压缩，全面揭示这项决定大模型上下文长度的核心技术。 https://answer.freetools.me/%E5%8D%83%E4%BA%BF%E5%8F%82%E6%95%B0%E6%A8%A1%E5%9E%8B%E5%A6%82%E4%BD%95%E5%A1%9E%E8%BF%9B%E6%9C%89%E9%99%90%E6%98%BE%E5%8D%A1zero%E5%A6%82%E4%BD%95%E7%94%A8%E5%88%86%E7%89%87%E6%B6%88%E9%99%A4%E6%95%B0%E6%8D%AE%E5%B9%B6%E8%A1%8C%E7%9A%84%E5%86%85%E5%AD%98%E5%86%97%E4%BD%99/ Mon, 09 Mar 2026 05:54:35 +0800 https://answer.freetools.me/%E5%8D%83%E4%BA%BF%E5%8F%82%E6%95%B0%E6%A8%A1%E5%9E%8B%E5%A6%82%E4%BD%95%E5%A1%9E%E8%BF%9B%E6%9C%89%E9%99%90%E6%98%BE%E5%8D%A1zero%E5%A6%82%E4%BD%95%E7%94%A8%E5%88%86%E7%89%87%E6%B6%88%E9%99%A4%E6%95%B0%E6%8D%AE%E5%B9%B6%E8%A1%8C%E7%9A%84%E5%86%85%E5%AD%98%E5%86%97%E4%BD%99/ 深入解析ZeRO（零冗余优化器）如何通过三阶段分片技术消除数据并行的内存冗余。从混合精度训练的内存消耗分析入手，详细阐述优化器状态、梯度、参数分片的数学原理，对比ZeRO与模型并行、流水线并行的通信开销，并介绍ZeRO-Offload和ZeRO-Infinity如何突破GPU内存墙。 https://answer.freetools.me/%E4%B8%BA%E4%BB%80%E4%B9%88flash-attention%E8%83%BD%E5%B0%86%E6%B3%A8%E6%84%8F%E5%8A%9B%E8%AE%A1%E7%AE%97%E6%8F%90%E9%80%9F%E6%95%B0%E5%80%8D%E8%80%8C%E4%B8%8D%E6%8D%9F%E5%A4%B1%E7%B2%BE%E5%BA%A6%E4%BB%8Egpu%E5%86%85%E5%AD%98%E5%A2%99%E5%88%B0io%E6%84%9F%E7%9F%A5%E7%AE%97%E6%B3%95%E7%9A%84%E6%8A%80%E6%9C%AF%E7%AA%81%E5%9B%B4/ Mon, 09 Mar 2026 03:57:50 +0800 https://answer.freetools.me/%E4%B8%BA%E4%BB%80%E4%B9%88flash-attention%E8%83%BD%E5%B0%86%E6%B3%A8%E6%84%8F%E5%8A%9B%E8%AE%A1%E7%AE%97%E6%8F%90%E9%80%9F%E6%95%B0%E5%80%8D%E8%80%8C%E4%B8%8D%E6%8D%9F%E5%A4%B1%E7%B2%BE%E5%BA%A6%E4%BB%8Egpu%E5%86%85%E5%AD%98%E5%A2%99%E5%88%B0io%E6%84%9F%E7%9F%A5%E7%AE%97%E6%B3%95%E7%9A%84%E6%8A%80%E6%9C%AF%E7%AA%81%E5%9B%B4/ 深度解析Flash Attention如何通过IO感知算法设计突破GPU内存墙瓶颈，实现注意力计算的数倍加速。从GPU内存层级到分块计算，全面揭示这项改变大模型训练格局的核心技术。 https://answer.freetools.me/%E5%A4%A7%E6%A8%A1%E5%9E%8B%E6%8E%A8%E7%90%86%E4%B8%BA%E4%BD%95%E8%BF%99%E4%B9%88%E6%85%A2%E4%BB%8E%E5%86%85%E5%AD%98%E5%B8%A6%E5%AE%BD%E7%93%B6%E9%A2%88%E5%88%B0kv-cache%E4%BC%98%E5%8C%96%E7%9A%84%E6%8A%80%E6%9C%AF%E7%AA%81%E5%9B%B4/ Fri, 06 Mar 2026 12:41:49 +0800 https://answer.freetools.me/%E5%A4%A7%E6%A8%A1%E5%9E%8B%E6%8E%A8%E7%90%86%E4%B8%BA%E4%BD%95%E8%BF%99%E4%B9%88%E6%85%A2%E4%BB%8E%E5%86%85%E5%AD%98%E5%B8%A6%E5%AE%BD%E7%93%B6%E9%A2%88%E5%88%B0kv-cache%E4%BC%98%E5%8C%96%E7%9A%84%E6%8A%80%E6%9C%AF%E7%AA%81%E5%9B%B4/ 深入解析大语言模型推理的性能瓶颈，从内存带宽限制到KV Cache优化的完整技术演进路线。涵盖FlashAttention、PagedAttention、GQA、连续批处理等核心技术，以及vLLM与TensorRT-LLM框架的选型建议。