model-footprint
bojieli/ai-infra-book/skills/model-footprint/SKILL.md
比较模型配置或架构改变对权重容量、KV 状态、前向计算和访存的影响。用于选模型、上下文或注意力与 MoE 方案。
Skill6.1k starsChanged 27 days ago
What's in it
- 模型架构资源账
--- name: model-footprint description: 比较模型配置或架构改变对权重容量、KV 状态、前向计算和访存的影响。用于选模型、上下文或注意力与 MoE 方案。 --- # 模型架构资源账 适用:讨论长上下文、GQA/MLA、MoE、精度或 batch 变化时,先量化模型本身的资源需求。依据 `manuscripts/02-模型架构.md` 第 2.1—2.6 节。 1. 从模型配置取得层数、隐藏维、注意力头和 KV 头、专家总数及每 token 激活数、参数精度。没有配置时标记未知,勿从参数总数臆造结构。 2. 分开计算权重容量、每 token 上下文状态大小、prefill 计算、单步 decode 计算,以及完整输出期间的状态读取。区分上下文长度、输出长度和 batch 对各项的作用。 3. 对注意力变体,核对实际保存和读取的状态表示;对 MoE,区分总参数的驻留容量与每 token 的激活计算、批内被访问的专家权重。 4. 比较两种架构时固定任务质量、输入输出长度、并发与硬件;列出变化的量及未变化的量,再判断容量或带宽瓶颈是否迁移。 输出按 prefill、单步 decode、完整请求分列的容量、FLOPs、读写字节表。模型配置与示例计算见 `calculations/README.md`。系统级延迟、排队和调度交给 `workload-modeling` 或 `inference-serving`。
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11 other files this repository gives its agents.
Skill
- accelerator-selectionskills/accelerator-selection/SKILL.md
- agent-runtime-capacityskills/agent-runtime-capacity/SKILL.md
- cluster-network-analysisskills/cluster-network-analysis/SKILL.md
- distributed-inferenceskills/distributed-inference/SKILL.md
- edge-cloud-placementskills/edge-cloud-placement/SKILL.md
- inference-servingskills/inference-serving/SKILL.md
- kernel-runtime-analysisskills/kernel-runtime-analysis/SKILL.md
- parallelism-planningskills/parallelism-planning/SKILL.md
- resource-budgetskills/resource-budget/SKILL.md
- training-system-planningskills/training-system-planning/SKILL.md
- workload-modelingskills/workload-modeling/SKILL.md
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