mold
17,746
Stars
585
Forks
107
Watchers
213
Open Issues
MIT
许可证
Rust
语言
2020-09-29
创建时间
2026-10-22
最近更新
项目能做什么
使用 Rust 编写的现代化高速链接器(Linker)。
来源:AI 基于仓库事实生成
· 内容以仓库实际 README 为准
使用说明 查看原始 README 原仓库文档
中文使用说明暂未生成。下面保留原仓库 README 摘录,命令与配置均以原文为准。
原始 README 摘录(英文原文,节选前 3000 字符)
# mold: A Modern Linker mold is a high-performance drop-in replacement for existing Unix linkers, designed to speed up builds. In our August 2026 benchmarks, it links 4.9x faster than [LLVM lld](https://lld.llvm.org) and 1.9x faster than [wild](https://github.com/wild-linker/wild) at the median; see [Benchmark](#benchmark) for the full results. mold is written by the original developer of LLVM lld, the linker that Android, Chrome, FreeBSD, PlayStation, Nintendo Switch, and other production systems are built with. mold started as an effort to build an even faster linker from scratch, free of the architectural limits its author had run into while optimizing lld. It has been in production use since 2021, and today it is the default linker of many large open-source projects and is used internally by many companies. mold supports x86-64, i386, ARM 32/64, RISC-V 32/64, PowerPC 32/64, s390x, LoongArch 32/64, SPARC64, m68k, and SH-4. ## Why does linking speed matter? If you are using a compiled language such as C, C++, or Rust, a build consists of two phases. In the first phase, a compiler compiles source files into object files (`.o` files). In the second phase, a linker takes all object files and combines them into a single executable or shared library file. The second phase can be time-consuming if your build output is large. mold can speed up this process, saving you time and preventing distractions while waiting for a lengthy build to finish. The difference is most noticeable during rapid debug-edit-rebuild cycles. ## Benchmark Here is a performance comparison of lld, wild, and mold when linking nine large programs on two machines: - AMD Ryzen Threadripper 7980X (64 cores) running Ubuntu 24.04 - Apple M1 Ultra (16 performance cores and 4 efficiency cores) running Fedora Asahi Remix 42; the benchmark is restricted to the performance cores The Threadripper represents many-core workstation and server processors, and the M1 Ultra represents high-performance desktop processors. All three linkers were built from source in release configuration as of 2026-08-28 and ran with their default options. Times are wall-clock times as seen by the caller, the median of three runs after a warm-up. The ARM64 rows are the ARM64 builds of the same programs. The benchmark suite, including all linker inputs, is available on [Zenodo](https://zenodo.org/records/21882261). **AMD Ryzen Threadripper 7980X, debug builds** | Program (output size) | lld | wild | mold | wild/mold | lld/mold |-----------------------------------|--------|-------|-------|-----------|--------- | Blender 5.2 (2.46 GiB) | 4.72s | 1.98s | 0.86s | 2.3x | 5.5x | Chromium 145 (4.51 GiB) | 16.64s | 3.98s | 1.65s | 2.4x | 10.1x | Chromium 145 ARM64 (4.76 GiB) | 20.91s | N/A | 1.83s | N/A | 11.4x | Clang 21 (4.19 GiB) | 6.19s | 3.71s | 1.34s | 2.8x | 4.6x | ClickHouse 26.1 (5.58 GiB) | 6.62s | 4.40s | 0.98s阅读完整原文
项目深度分析 AI 生成
企业级编译与链接工具链技术支持与咨询服务
| 产品构想 | 针对使用大型 C++/Rust 项目(如游戏、金融高频交易、自动驾驶)的头部公司,提供定制化构建性能调优、工具链集成支持以及专属 Bug 修复 SLA。 |
| 核心功能 | 优先 Issue 处理与定制补丁、专用架构/内部工具链适配、构建性能瓶颈审计与调优报告 |
| 目标用户 | 拥有大型代码库的科技公司工程效能团队、游戏开发工作室、金融高频交易基础设施组 |
| 难度/周期 | 高 · 3 - 6 个月 · 成本:极高(需具备极深厚的底层系统、ELF/链接器知识) |
| 收费模式 | 年度技术支持合同(Enterprise Support Retainer)或顾问咨询按人天收费 |
| 竞争风险 | 依赖极高专业声誉与顶尖系统级人才,交付周期长,标准化难度大难以规模化复制 |
| 依据 | 数据支持的判断 |
闭源商业平台扩展与加速支持(macOS / Windows 专用商业版)
| 产品构想 | 围绕 Windows (PE/COFF) 和 macOS (Mach-O) 提供闭源商业版快速链接器扩展,针对商业桌面与移动端开发团队收费。 |
| 核心功能 | Mach-O 与 PE/COFF 原生格式极速链接、Xcode 与 MSVC 工具链透明集成、增量链接支持 |
| 目标用户 | iOS/macOS 应用与大型游戏客户端开发者、Windows 原生开发团队 |
| 难度/周期 | 极高 · 6 - 12 个月 · 成本:高(逆向工程、处理苹果/微软私有二进制规范与频繁系统变动的维护成本) |
| 收费模式 | 席位订阅制(Seat License)或企业级买断授权 |
| 竞争风险 | 开源替代方案(如 wild、新版 lld)正在快速演进,平台封闭规范可能频繁破坏兼容性 |
| 依据 | 已验证事实 |
云端分布式编译与缓存智能集成代理(DevOps 加速方案)
| 产品构想 | 构建与 mold 原生绑定的轻量级 CI 编译加速代理插件,结合远程缓存(如 sccache/bazel)与内存盘/并行链接优化,一键缩短 CI 流水线时间并降低计算成本。 |
| 核心功能 | 开箱即用的 CI 链接器自动注入、链接产物智能去重与缓存加速、构建耗时与瓶颈分析看板 |
| 目标用户 | 使用 GitHub Actions、GitLab CI 等云流水线的大中型企业研发团队 |
| 难度/周期 | 中等 · 2 - 4 个月 · 成本:低到中等(主要是云集成、SaaS 平台开发与推广成本) |
| 收费模式 | 基于加速流水线节省时间的 SaaS 订阅制或按构建节点数收费 |
| 竞争风险 | 用户可能自行在 Docker/CI 镜像中手动安装 mold 而绕过付费商业封装 |
| 依据 | 尚需验证的假设 |
AI 基于仓库公开数据分析生成,含推测成分,不构成收益承诺。
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项目优势与风险
| 技术成熟度 | 创建于 2020-09-29,近 30 天仍在推送,发布过 67 个 Release |
| 社区活跃 | Star 17,746 / Fork 585 / Issue 213(数据支持,可自行核实) |
| 许可证 | MIT |
| 主要风险 | 上游项目方向可能变化;同赛道竞争者较多(见竞品表);热度与需求不完全等价 |
安装与使用
此项目未提供 Docker 镜像,安装步骤以原仓库 README 为准(涉及依赖安装与环境配置,对新手门槛较高)。