hustfisher/cargo-profiler — explained in plain English
Analysis updated 2026-08-11 · repo last pushed 2022-08-30
Find which function is slowing down your Rust library so you know exactly what to optimize.
See a ranked list of functions by how many instructions they execute or how many cache misses they cause.
Profile a specific compiled binary directly instead of running through cargo.
Compare two profiling runs side by side to see if your changes improved performance.
| hustfisher/cargo-profiler | 000madz000/rfid-attendance | 00kaku/gallery-slider-block | |
|---|---|---|---|
| Language | — | TypeScript | JavaScript |
| Last pushed | 2022-08-30 | 2024-07-22 | 2021-05-19 |
| Maintenance | Dormant | Dormant | Dormant |
| Setup difficulty | moderate | easy | easy |
| Complexity | 2/5 | 2/5 | 2/5 |
| Audience | developer | developer | general |
Figures from each repo's GitHub metadata at analysis time.
Requires a Linux environment with valgrind installed separately before the tool can run.
cargo-profiler is a tool for Rust developers who want to find out where their program is spending time or resources. Think of it as a speedometer and fuel gauge for your code. Instead of guessing which functions are slow or memory-hungry, you run one command and get a ranked breakdown showing exactly which parts of your code are doing the most work. Under the hood, it wraps two established Linux profiling tools called callgrind and cachegrind. You run a command like cargo profiler callgrind from within any Rust project, and the tool handles the setup. It feeds your compiled binary through the profiler, collects the raw data, and prints a clean summary showing the top functions by instruction count or cache misses. You can also point it at a specific binary directly, pass arguments to the program being profiled, limit the output to your top N functions, or sort by specific metrics. The audience is Rust developers working on Linux who need to optimize performance. For example, if you're building a matrix math library and your tests feel sluggish, this tool would show you that a specific kernel function accounts for forty percent of all instructions executed. That tells you exactly where to focus your optimization effort rather than hunting blindly. One notable limitation is that it only runs on Linux and requires a separate tool called valgrind to be installed first. The project also notes several features still on the roadmap, including the ability to compare two profiling runs side by side and support for additional profiling tools beyond callgrind and cachegrind.
A Rust tool that shows you exactly which functions in your program are slow or resource-heavy, so you know where to focus when making your code faster.
Dormant — no commits in 2+ years (last push 2022-08-30).
The explanation does not mention the license, so the licensing terms are unknown.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
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