kvcache-ai-ktransformers/archive/ktransformers/website/vue.config.js
Jiaqi Liao 57d14d22bc
Refactor: restructure repository to focus on kt-kernel and KT-SFT modulesq recon (#1581)
* refactor: move legacy code to archive/ directory

  - Moved ktransformers, csrc, third_party, merge_tensors to archive/
  - Moved build scripts and configurations to archive/
  - Kept kt-kernel, KT-SFT, doc, and README files in root
  - Preserved complete git history for all moved files

* refactor: restructure repository to focus on kt-kernel and KT-SFT modules

* fix README

* fix README

* fix README

* fix README

* docs: add performance benchmarks to kt-kernel section

Add comprehensive performance data for kt-kernel to match KT-SFT's presentation:
- AMX kernel optimization: 21.3 TFLOPS (3.9× faster than PyTorch)
- Prefill phase: up to 20× speedup vs baseline
- Decode phase: up to 4× speedup
- NUMA optimization: up to 63% throughput improvement
- Multi-GPU (8×L20): 227.85 tokens/s total throughput with DeepSeek-R1 FP8

Source: https://lmsys.org/blog/2025-10-22-KTransformers/

This provides users with concrete performance metrics for both core modules,
making it easier to understand the capabilities of each component.

* refactor: improve kt-kernel performance data with specific hardware and models

Replace generic performance descriptions with concrete benchmarks:
- Specify exact hardware: 8×L20 GPU + Xeon Gold 6454S, Single/Dual-socket Xeon + AMX
- Include specific models: DeepSeek-R1-0528 (FP8), DeepSeek-V3 (671B)
- Show detailed metrics: total throughput, output throughput, concurrency details
- Match KT-SFT presentation style for consistency

This provides users with actionable performance data they can use to evaluate
hardware requirements and expected performance for their use cases.

* fix README

* docs: clean up performance table and improve formatting

* add pic for README

* refactor: simplify .gitmodules and backup legacy submodules

- Remove 7 legacy submodules from root .gitmodules (archive/third_party/*)
- Keep only 2 active submodules for kt-kernel (llama.cpp, pybind11)
- Backup complete .gitmodules to archive/.gitmodules
- Add documentation in archive/README.md for researchers who need legacy submodules

This reduces initial clone size by ~500MB and avoids downloading unused dependencies.

* refactor: move doc/ back to root directory

Keep documentation in root for easier access and maintenance.

* refactor: consolidate all images to doc/assets/

- Move kt-kernel/assets/heterogeneous_computing.png to doc/assets/
- Remove KT-SFT/assets/ (images already in doc/assets/)
- Update KT-SFT/README.md image references to ../doc/assets/
- Eliminates ~7.9MB image duplication
- Centralizes all documentation assets in one location

* fix pic path for README
2025-11-10 17:42:26 +08:00

40 lines
No EOL
1.4 KiB
JavaScript
Raw Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

module.exports = {
// 配置 webpack-dev-server 行为。
devServer: {
open: false, // 编译后默认打开浏览器
host: '0.0.0.0', // 域名
port: 8082, // 端口
https: false, // 是否https
proxy: {
'/api': {
target: 'http://localhost:9016/v1', // 你的后端服务器地址
changeOrigin: true, // 是否允许跨域
pathRewrite: {
'/api': '' // 将 '/api' 前缀替换为空,如果你的后端不需要这个前缀
}
}
}
},
publicPath: '/web/', // 基本路径
outputDir: 'dist', // 构建时的输出目录
assetsDir: 'static', // 放置静态资源的目录
indexPath: 'index.html', // html 的输出路径
filenameHashing: true, // 文件名哈希值
lintOnSave: false, // 是否在保存的时候使用 `eslint-loader` 进行检查。
// 组件是如何被渲染到页面中的? ast抽象语法树vDom虚拟DOM
// template ---> ast ---> render ---> vDom ---> 真实的Dom ---> 页面
// runtime-only将template在打包的时候就已经编译为render函数
// runtime-compiler在运行的时候才去编译template
runtimeCompiler: false,
transpileDependencies: [], // babel-loader 默认会跳过 node_modules 依赖。
productionSourceMap: false, // 是否为生产环境构建生成 source map
//调整内部的 webpack 配置
configureWebpack: () => {},
chainWebpack: () => {},
}