I'm glad to see the donations from big companies to open source maintainers are making measurable difference to the Rust experience. Telling these companies that their employees spend 5% less time waiting for compilation might motivate future investment in people like Nick and the others mentioned.
Doing stuff isn't free. For instance, Go compiles relatively quickly for a modern language, but the biggest reason for that is that it does less stuff than most compilers... less optimization, less checking, and some stuff built into the language to avoid some of the problems with having to read lots of headers just to compile a file and other ways of doing less stuff, but mostly the key is it does less stuff, in both the good and bad senses of that.
If you want something like Rust that offers guarantees and checks and cross-checks by the boatload, it adds up. Macros, monomorphization, implicit code generation with traits and all those other things add up too. And you can't always get O(n) or O(n log n) code to implement those checks. Maybe it can be sped up and maybe there's tricks here or there, but at the Pareto frontier, a language that has more checks will be slower to compile than one that has fewer.
And that's not a bad thing or a deficit in Rust, it's just the nature of the beast.
And since you bring up Go and contrast the compile time with Rust, it's been experienced at Google (and also Volvo and other places) that Rust and Go teams are as productive whereas C++ is less than half as productive: https://www.youtube.com/watch?t=27012&v=6mZRWFQRvmw&feature=...
So the focus on Rust compile time is misplaced. It's not a big deal in terms of overall productivity.
I don't think that follows - just that compile times aren't the only thing that matters. Maybe rust could be twice as productive as go if compile times went to zero for instance (or maybe not - just disputing that the evidence proves the claim here).
First of all, the fact that the article talks about "speeding up" the rust compiler doesn't automatically mean that the compiler is "slow"[0].
Now, is rustc slower than e.g. clang? by how much? why?
Those are different (and complicated) questions. It really depends on what you're compiling, but I'd say rustc can be 1-5x slower (maybe more at times?).
The reasons are many and varied, but in general rust compilation is slower because the compiler is doing way more things compared to C (monomorphization, complex trait resolution + type inference, borrow checker..)
[0]: Also I'd argue that "slow" without a concrete point of reference is a meaningless term in this context.
Zero-cost abstractions aren't zero cost in compilation time. High-level abstractions translate to a lot of boilerplate that the compiler has to optimize out.
In unoptimized builds often the linker is the bottleneck. Rust/Cargo can parallelize most of the build, generating tons of code and debug info, but then the poor linker has to consume all of it at once. The object/exe formats were designed in ancient times, so they're hard to build incrementally or in parallel (some linkers are trying).
I once heard (and don't know if it's still true) that the biggest compile-time sinks are macros and codegen.
Both are kind of outside the Rust compiler's influence. Macros can be almost arbitrarily complex: you pay for what you order. Codegen is LLVM, and that's a fixed choice. You can use Cranelift to get around it, but then you pay elsewhere.
Also, generics and monomorphization regularly come up in these discussion, while common wisdom seems to be that cost for the additional static analysis over other languages like C++ is no a major contributor.
Regardless, it's nice to see performance improvements in the compiler, even if you have to cooperate to benefit from them (e.g. by keeping your macros light and use less generics).
Its similar to C++ compilers, there is no one reason. It is a language that tries to optimize a lot, its a big language, it does safety checks, it uses llvm which is a bit slow, its a language that makes use of generics which generate extra code etc etc.
This is not actually the main reason, most of the time.
Generics/monomorphization and how iterators work results in a lot of compiler bytecode that has to be churned through. More bytecode = longer compilation. It increases the size of the (debug) binaries, the debuginfo in general, causes performance issues with debug binaries in some situations unless you bump the optimization level, causes more IO, etc.
It's unlikely that many people are using Rust without using Option<T> or Result<T, U> a fair bit. Idiomatic Rust fundamentally uses a lot of generics. And a basic for loop expands into quite a lot of intermediate representation due to Iterator.
The EverInitializedPlaces example really stands out. Going from ~1.5M to ~90K apply_effects_in_block calls by changing the CFG traversal is a reminder that the biggest compiler optimizations often come from changing the algorithm, not optimizing the hot loop itself.
It also seems like the new Polonius/trait-solver work is pushing compiler performance toward a more interesting problem: doing expensive analysis only when it is actually needed.
4.57% mean wall-time reduction across 629 benchmarks in two months is pretty remarkable. Great progress.
> reminder that the biggest compiler optimizations often come from changing the algorithm, not optimizing the hot loop itself.
Isn't this true for most optimizations, not just in compilers? My usual goto process for optimizing is "Find stuff we're doing that we don't have to do, re-evaluate what data structures we use and then re-evaluate what algorithms we use" basically, with minor changes depending on the results. Served me well so far, and haven't (intentionally) written any compilers.
Incremental seems to keep winning the easy wins, so the interesting part is whether the remaining compile-time still lives in the same places as last year.
Sometimes we really can have our cake and eat it too.
What is the performance killer?
If you want something like Rust that offers guarantees and checks and cross-checks by the boatload, it adds up. Macros, monomorphization, implicit code generation with traits and all those other things add up too. And you can't always get O(n) or O(n log n) code to implement those checks. Maybe it can be sped up and maybe there's tricks here or there, but at the Pareto frontier, a language that has more checks will be slower to compile than one that has fewer.
And that's not a bad thing or a deficit in Rust, it's just the nature of the beast.
So the focus on Rust compile time is misplaced. It's not a big deal in terms of overall productivity.
Now, is rustc slower than e.g. clang? by how much? why?
Those are different (and complicated) questions. It really depends on what you're compiling, but I'd say rustc can be 1-5x slower (maybe more at times?).
The reasons are many and varied, but in general rust compilation is slower because the compiler is doing way more things compared to C (monomorphization, complex trait resolution + type inference, borrow checker..)
[0]: Also I'd argue that "slow" without a concrete point of reference is a meaningless term in this context.
In unoptimized builds often the linker is the bottleneck. Rust/Cargo can parallelize most of the build, generating tons of code and debug info, but then the poor linker has to consume all of it at once. The object/exe formats were designed in ancient times, so they're hard to build incrementally or in parallel (some linkers are trying).
Both are kind of outside the Rust compiler's influence. Macros can be almost arbitrarily complex: you pay for what you order. Codegen is LLVM, and that's a fixed choice. You can use Cranelift to get around it, but then you pay elsewhere.
Also, generics and monomorphization regularly come up in these discussion, while common wisdom seems to be that cost for the additional static analysis over other languages like C++ is no a major contributor.
Regardless, it's nice to see performance improvements in the compiler, even if you have to cooperate to benefit from them (e.g. by keeping your macros light and use less generics).
Generics/monomorphization and how iterators work results in a lot of compiler bytecode that has to be churned through. More bytecode = longer compilation. It increases the size of the (debug) binaries, the debuginfo in general, causes performance issues with debug binaries in some situations unless you bump the optimization level, causes more IO, etc.
It also seems like the new Polonius/trait-solver work is pushing compiler performance toward a more interesting problem: doing expensive analysis only when it is actually needed.
4.57% mean wall-time reduction across 629 benchmarks in two months is pretty remarkable. Great progress.
Isn't this true for most optimizations, not just in compilers? My usual goto process for optimizing is "Find stuff we're doing that we don't have to do, re-evaluate what data structures we use and then re-evaluate what algorithms we use" basically, with minor changes depending on the results. Served me well so far, and haven't (intentionally) written any compilers.