rustc-perf VS rand

> what do people use to run benchmarks on CI?

Typically, you purchase/rent a server that does nothing but sequentially run queued benchmarks (and the size/performance of this server doesn't really matter, as long as the performance is consistent), then sends the report somewhere for hosting and processing. Of course, this could be triggered by something running in CI, and the CI job could wait for the results, if benchmarking is an important part of your workflow.

But CI and benchmarks really shouldn't be run on the same host.

> What does the rust project use?

It's not clear exactly where the Rust benchmark "perf-runner" is hosted, but here are the specifications of the machine at least: https://github.com/rust-lang/rustc-perf/blob/414230abc695bd7...

> What do other projects use?

Essentially what I described above, a dedicated machine that runs benchmarks. The Rust project seems to do it via GitHub comments (as I understand https://github.com/rust-lang/rustc-perf/tree/master/collecto...), others have API servers that respond to HTTP requests done from CI/chat, others have remote GUIs that triggers the runs. I don't think there is a single solution that everyone/most are using.

A lot of effort is spent to reduce the size of structs in the Rust compiler

https://nnethercote.github.io/2023/03/24/how-to-speed-up-the...

3% and 6% of improvement doesn't seem like much, but at the level of rustc those big wins

Performance of Rustc must be continously tracked (here https://perf.rust-lang.org/) because if you don't proactively fight against bloat, the tendency is that the code will become slower over time (due to new features etc)

hmm really really hard to answer :'), it's tradeoffs I think, no matter what you think Rust (cmiiw, I'm not qualified to say this) has (and probably in the future will adds more with guards on compiler metrics https://perf.rust-lang.org/) several phases that given the diffs to other language, might not available to any language compiler out there, if it's available I think rustc already did their best in here (some already being parallized etc etc, might be wrong since I can't refs any reference MRs, but it does exists though labels regarding this)

About a year ago I was looking for a tool like Rust perf for my application code. I did some research and found a lot of prior art. However, nothing checked all the boxes I was looking for, so I built Bencher!

https://www.pingcap.com/blog/rust-compilation-model-calamity... is a good overview. In general it varies depending on the crate but we track the performance at https://perf.rust-lang.org/ - if you look at cargo, for example, over 60% of the time is spent in codegen through LLVM: https://perf.rust-lang.org/detailed-query.html?commit=222d1f...

Something like https://perf.rust-lang.org/?

The performance full-report link is dead: https://github.com/rust-lang/rustc-perf/blob/master/triage/2022-10-04.md

Making compatibility promises for distributions means they cannot take advantage of potential advancements in the field.

Defining an error type that is meaningful, portable, and compatible with no-std isn't straightforward. If the std lib's getrandom requires std, then just like that, rand and many other crates won't use it anyway. Using io::Result seems to me to face this challenge.

Some wasm targets can’t generate random numbers at all but in the case of the book because you are using wasm in a browser you can use JS to generate random numbers. I believe there’s a way to get the rand crate to use JS as the backend for generating rand but its a bit more convoluted than the easy one-liner that the book suggests.

rand

This uses rand and xcomplex to handle the mathematics, png to write image files, and dialoguer and indicatif for some pretty prompts and progress bars.

You can often achieve this without any unsafe by putting an assert!() on the length before the hot loop. For example, I got rid of some unsafe in rand that way.

This is a widely used method to map random integers to floating point numbers, but it has the disadvantage of wasting 1 bit of float mantissa precision.

On modern CPUs, its computational advantage over full-precision mapping methods, such as multiplication by a float, is not always clear [1].

[1] https://github.com/rust-random/rand/issues/416

In fact, there are a lot of crates in Rust where in other programming languages, it would be included in the standard library. Examples are regex, random number generators, additional iterator methods, macros for other collections, num traits, loggers, HTTP libraries, error handling, async runtimes, serialization and deserialization, date and time, and many more.