If your algorithm does a ton of small allocations to the point where the allocator is the bottleneck, you're already doing it wrong. The allocator necessarily comes with a lot of overhead because it needs to accommodate diverse use cases, avoid fragmentation, and ideally, implement a variety of security checks. If you're doing something alloc-intensive, you're probably allocating and freeing a lot of identical structures and you'd be better off grabbing some continuous memory and managing that yourself in a task-specific way.
But the reality is that almost no one actually cares about performance because compute is cheaper than expertise and labor, at least in the short haul. Everything is getting more bloated and slower and we just compensate by adding CPU cores, gigabytes and gigahertz.
Think about it this way because the issue isn’t specific to allocators: it’s pretty good in general but can often be beaten if you have special understanding of what you need to do. That’s OK.
You can buy cars and trucks that are optimized for driving on freeways and residential streets carrying stuff people often carry. But then there are special vehicles like fork lifts and such that are kinds of large special cases. And then there are weirdo specialised vehicles that have four wheels but are rare and their users can’t live without them.
Languages like C++ let you plug in special allocators if you want. But most people don’t. Some, like HFT people do crazy headstands to avoid slow allocations. I don’t ever want to do that but if they want to, why not. I don’t think they complain that the default case doesn’t fit their needs!
For a typical program, I bet that the overall impact of the glibc allocator is well under 0.1%. If you can choose between < 0.1% and < 0.12%, I guess it matters in some sense, but not in any practical way. We almost never spend time on other sub-0.1% optimizations. You could probably squeeze a lot more by optimizing CPU branch predictor performance, minimizing CPU cache misses, or fine-tuning the scheduling strategy, but we also don't bother. 'Tis is the era of "native" apps written in Electron.
A decade ago, I worked on a simulation program that involved a C++ core with a Python wrapper and DB interface. End users cared a lot about throughout with a rather limited size, weight and power budget. We spent a lot of time optimizing the core -- but basically hit a bottleneck once we got to about 15% of the time that was spent in malloc-related functions. It turned out that was all in the Python layer. Probably there was some level of bad code in our Python code, but it was impractical to figure out where that was. I was shocked because I assumed the simulation core (which ended up almost allocation-free by the end) would always dominate CPU usage.
Both allocators and Python have probably gotten better since then, but it was a fascinatingly large and stubborn fraction of CPU time.
"But the reality is that almost no one actually cares about performance because compute is cheaper than expertise and labor, at least in the short haul."
Doesn't have to stay that way, with hardware prices soaring and development cost allegedly in free fall.
No, musl's allocator is just bad even in completely normal programs, and it is especially awful if you are using even two threads much less a lot of them. It has no TLABs or arenas. It has a single global mutex over alloc/free paths. It does syscalls underneath that lock (mmap) meaning the few fast paths it has are rarely taken under contention and have to fall back to futex wakes, so even 2 threads with minor contention and allocation rate will have visible wait points in profiles, stuck waiting for the allocator. It returns mapped memory to the OS very eagerly when a size class is empty, so even single allocs followed by a single free can cause thrashing as it mmaps/unmmaps things repeatedly for a size class over and over. Etc. You quite literally have to limit your thread count when using musl, because it will tank the performance of actually highly threaded programs that can scale with core count, even at very modest allocation rates and small working set sizes.
Its string routines and memory copy routines are also similarly bad, as the article alludes to. They are just naive loops with nearly no optimization. These are not small insignificant functions where using them is "doing it wrong", they are the backbone of vast amounts of code and can be made multiple times faster. You can similarly see string routines pop up in profiles all the time in musl builds in my experience. And unlike the memory allocator these cannot be "fixed" systematically across the application at link time, so you are stuck with it.
Real programs have to often do things like allocate memory and use multiple threads and process strings. People have been optimizing these things for decades, there is vast amounts of prior art, the musl developers simply did not do so because they prioritize simplicity over nearly everything else (from what I can tell) including performance.
It has a single global mutex over alloc/free paths. It does syscalls underneath that lock (mmap)
Every default malloc implementation worked this way about 12 years ago. Making lots of small allocations, even from multiple threads then blaming the allocator is a losing strategy. An allocator is only going to be able to mitigate the damage to speed and interactivity.
The solution is and always has been to make larger allocations and use those efficiently.
They are just naive loops with nearly no optimization.
The compiler should be able to take something with good access patterns and make something fast, especially out of the basic C functions.
they are the backbone of vast amounts of code
Performance wise it's unlikely C string functions are actually the bottleneck in a program. Maybe for specific programs a naive memory copy function could benefit from AVX instructions.
Real programs have to often do things like allocate memory
"Have to" and "often" are debatable. Any allocations in a hot loop are the very first things that should be optimized away after profiling.
>Performance wise it's unlikely C string functions are actually the bottleneck in a program. Maybe for specific programs a naive memory copy function could benefit from AVX instructions.
Many programs use lots of strings. It tends to become a bottleneck. It also tends to be very difficult to improve because the strings are everywhere in that kind of program, and refactoring to eliminate them is either impossible or very risky.
Many programs use lots of strings. It tends to become a bottleneck.
I would dispute this in anything that isn't mostly about string processing and in that case you can always easily grab different string functions, which you should probably do anyway if strings are that important.
It also tends to be very difficult to improve because the strings are everywhere in that kind of program,
I don't know what 'that kind of program' is supposed to mean.
and refactoring to eliminate them is either impossible or very risky.
This doesn't sound like a general purpose statement that applies to anything broadly.
All I'm saying is the the title is wrong and musl doesn't do much to prevent speed in a program. If someone was really trying to optimize, blaming the standard library is not going to get them very far and it's easy to work around, but needing to do that is very rare.
>I would dispute this in anything that isn't mostly about string processing and in that case you can always easily grab different string functions, which you should probably do anyway if strings are that important.
I'm telling you that I've seen it, in stuff as diverse as video games and robotics. Lots of things use strings as values. It's easy to say "just change everything in millions of lines of code" when you aren't the one who has to make that change.
By the way most software does copious amounts of string processing... I think that should be common knowledge, but I guess it isn't.
>This doesn't sound like a general purpose statement that applies to anything broadly.
You sound like you have zero experience. If your config is in strings, and hundreds of thousands of lines of code already rely on the string-ness of the data, then you just can't make the change easily.
>All I'm saying is the the title is wrong and musl doesn't do much to prevent speed in a program. If someone was really trying to optimize, blaming the standard library is not going to get them very far and it's easy to work around, but needing to do that is very rare.
I believe the title is accurate. People in performance-sensitive areas gripe about libraries, even standard libraries, quite often. I don't mean to insult you but you're making bold assertions despite clearly lacking the experience to know how things are done in industry generally.
> Every default malloc implementation worked this way about 12 years ago.
Perhaps "default" is doing the heavy lifting here. Glibc malloc was quite bad for a long time, true. But TCmalloc / jemalloc are 21-22 years old, respectively, and jemalloc has been the FreeBSD (released) default malloc implementation for the last 18.
> The solution is and always has been to make larger allocations and use those efficiently.
Having a not-dogshit allocator really doesn't hurt. There's no reason to defend shitty allocator + every application doing manual memory pools on top of it to paper over the bad allocator.
I'm not defending anything, I'm saying it's usually trivial to make allocation time marginal.
+ every application doing manual memory pools
Usually it's simple data structures in flat memory.
If allocation is taking all the time, that's a poorly optimized program with lots of low hanging fruit and a different allocator is not the right fix. It's like having a boat with a hole in the bottom and someone says the solution is a smaller hole.
But TCmalloc / jemalloc are 21-22 years old, respectively, and jemalloc has been the FreeBSD (released) default malloc implementation for the last 18.
jemalloc is also possibly bigger than all of musl. If it was a problem after optimization I would use it and I have in the past, it's just nowhere near as important as minimizing allocations in the first place. OpenBSD uses straight mmap.
There's also a reason this stuff started getting adopted around 20 years ago (I'll add macOS to the pile: it added per-CPU malloc sharding in 2008). It's not just due to overall growth in OS complexity. It's because that's when multicore CPUs were taking off. Before that, the cost of a global lock was far lower.
OpenBSD is straight unconcerned about performance. That's their choice.
> Every default malloc implementation worked this way about 12 years ago.
Yes, it is now 12 years later, and memory allocators are better. The memory allocators of that time were also better than the ones 12 years their prior. That's the point.
> Making lots of small allocations, even from multiple threads then blaming the allocator is a losing strategy. An allocator is only going to be able to mitigate the damage to speed and interactivity.
It's just a reality that musl is measurably worse at multiple threads allocating even in very polite conditions, because it causes lots of contention. If your program allocates in multiple threads, it is probably going to get slower with musl. If you don't want that, other memory allocators will do great even at high allocation rates with more threads. You could write many other data structures that had equally poor behavior under multi-threaded contention by just throwing a lock around everything and calling it a day, and those bad data structures would also cause "damage to speed and interactivity" or whatever. This isn't very hard to understand.
> The compiler should be able to take something with good access patterns and make something fast, especially out of the basic C functions.
I agree, modern compilers are good. But these are extremely common specified functions, they are called everywhere all the time in every C codebase (and that's partially why compilers even recognize these patterns specifically so they can insert optimized routines). Mature implementations that are hand optimized still pay off and also tend to be tuned for various edge cases or quirks that aren't going to come for free from the C compiler either, so it's still work even if you aren't writing assembly for everything or whatever (e.g. uarch dependent codepaths, or optimizations for short strings or whatever).
glibc's AVX2 based memcpy functions have a non-negligible performance impact in at least 1 application I maintain on the order of like 8-ish% vs musl (wall clock). It just has to memcpy/memmove a whole lot. Whether or not that's tolerable is up to debate, but a spade is a spade.
> Performance wise it's unlikely C string functions are actually the bottleneck in a program. Maybe for specific programs a naive memory copy function could benefit from AVX instructions.
I said "backbone", not "bottleneck". They are common functions sprinkled in everywhere throughout every application in every codepath on something like a modern Linux desktop. An inverted callstack flamegraph can show you stuff like this. It is basically no different than compiling your application at -O1 and -O2 with GCC. Does the fact your program get 20% faster from -O2 mean that there were "bottlenecks" the compiler solved? No, there was just performance left on the table by emitting better code.
> "Have to" and "often" are debatable.
Not really. I have to spell it out apparently: actual programs written by normal human programmers do those things, all the time, they exist in and are common in the world, they depend on other code that does that and is common in the world, they run on your desktop and phone and all servers, and they benefit quite a lot from optimized components like memory allocators and string routines and -O2 making their programs faster. This is pretty easy to observe and the means of doing so should be quite obvious, so there's no real debate.
Now whether this fact holds -- whether these programs "have to" do these things or not -- in the imaginary fantasy land people have in their heads where they make up arguments to themselves about how, if every program was written how they liked it, it would be better? That I'm not so sure about, I will admit.
The memory allocators of that time were also better than the ones 12 years their prior. That's the point.
The point is that memory allocation shouldn't be a bottleneck either way. If it is the program needs to be optimized or redesigned. Better allocators give you more slack, they don't solve the problem. If the problem is already solved, then a basic allocator isn't going to make a big performance difference because it isn't the bottleneck.
those bad data structures would also cause "damage to speed and interactivity" or whatever. This isn't very hard to understand.
It depends on how much they are used and how much contention there is. Sometimes putting a mutex around things is fine.
But these are extremely common specified functions, they are called everywhere all the time
Not necessarily, especially for C string functions, but they do get linked in so it's a good thing musl makes them small.
I said "backbone", not "bottleneck".
Then the point is lost, because 'backbone' doesn't mean anything if it works. If it isn't a bottleneck in throughput or latency anywhere then the speed doesn't matter.
The other important thing is that better stuff can be included in pieces as it's needed. The reverse isn't true. If you use a big fat C library, you have a dependency that isn't going to get better.
Not really. I have to spell it out apparently: actual programs written by normal human programmers do those things, all the time,
You spelled it out last time, it's just not true in the sense that programs have to have these functions as bottlenecks. Strings, allocators and memory copying can all be dealt with independently, but again it's rare that strings and allocations really need to be the bottleneck and in those circumstances you probably want more than a different standard library anyway.
in the imaginary fantasy land people have in their heads where they make up arguments to themselves about how, if every program was written how they liked it,
I'm not sure what this is supposed to mean, there is nothing I've said that doesn't make perfect sense. If you want something to go faster you can make it go faster. A better allocator pales in comparison to lifting allocations out of hot loops.
My point is the musl is useful and the disadvantages are easy to work around. I'm not really sure what your point is, do you think people are going to force you to use it?
People have such different perspectives. 26% slower does not sound "terrible" to me; it sounds like quite a reasonable price one might choose to pay for the convenience musl offers. If musl's allocator were 2.6x slower, I might call that "not so great"... but in order to qualify as "terrible" I think the difference would have to be an order of magnitude!
The 26% number at the top of the article is from using mimalloc (which is a high performance allocator, at least as fast as the glibc allocator) + musl for some task, and the slowdown is coming from (probably) slow musl implementations of memcpy/memset. The musl allocator is even worse.
> the slowdown is coming from (probably) slow musl implementations of memcpy/memset.
It's wild that such a fundamental piece of code (you can't really implement operation on structs without those) is library-supplied. I wish compilers would just have something like __builtin_memcpy and __builtin_memset, and provided some highly optimized, specialist-crafted assembly in those, instead of having to inline the library code and hopefully be able to optimize it.
Maybe you're being sarcastic, but I'm pretty sure clang + gcc do offer these.
The problems at first glance :
- Not having control over the implementation detail of the interface that your library provides is probably not wise. Sounds like a lot of bad bug reports and edge cases that you have no control over.
As others have alluded, __builtin_memcpy doesn't resolve to a runtime implementation. GCC and clang treat functions like memcpy specially. Because they're defined by the standard and are reserved names, compilers can assume the exact semantics specified by the standard and elide library calls altogether with optimized inline code. But if the compiler can't do the optimization (can't prove alignment, indeterminate length, etc), it just emits a library call, even if your source has some other local function definition named "memcpy". Explicit use of __builtin_memcpy is treated identically to calls to memcpy, unless the compiler is invoked with -ffreestanding, in which case it only optimizes __builtin_memcpy and skips special treatment of calls to memcpy, but __builtin_memcpy could still expand into a call to memcpy. If you're writing a C library you want to use -ffreestanding. (I think. There may be more nuance. More info at https://gcc.gnu.org/bugzilla/show_bug.cgi?id=56888)
Clang and GCC do provide these, and automatically use them in many situations (particularly small copies). But c-libraries can actually do it better in many cases, especially for large copies.
Glibc, for example, has perhaps ten different implementations of memcpy just for x86. The compiler certainly could provide all that, but the next step is harder:
glibc automatically dispatches to the proper one at runtime based on the actual microarchitecture that the binary is running on. You pay the extra dispatch cost once, but all of non-inline function call cost every time. This is what allows distros to compile to a nice baseline architecture, but still get near-optimal memcpy performance on many more architectures than a single inline instance could possibly give. These differences matter.
And it does it for not just memcpy, but half-a-dozen other extremely performance sensitive library functions, like strcpy and so on.
Inlining works very much against this strategy. If you can guarantee that the target microarch never changes, then it isn't a good one. But that is somewhat unusual for everyone but those who build their own binaries to run on a single class of machines forever.
Worse, inlining the really high performance versions of these ends up being terrible from a code size perspective, because they are often hundreds of instructions, which can have bad caching effects. And once you amortize the function-call cost over many iterations of the loop, it isn't so expensive to call out to the library.
Anyway, just some additional considerations to think about.
Even if the attempt is inside of a function called memcpy() which contains no code other than your copy loop, and links with priority over the libc implementation! (as all embedded firmware engineers learn at some point in their journey)
Yeah, doing compute-heavy work a couple of jobs ago, we tried small images with musl, and the default allocator was a catastrophe: 75%+ slowdowns for our real life tasks. Even with a better allocator, we were way better off with the larger image.
Ops here, I think if you NEED that convenience, sure, rock with MUSL BUT I also see a ton of devs crowing about using MUSL on my 128GB x86 Kubernetes hosts. I have plenty of Disk Space, you can ship glibc based container.
The 26% slower appears to be for their whole application, not just the allocator. For some parts of the application to make the whole this much slower it must mean that those parts are quite a lot slower, likely much more than 2x.
Moreover the 26% is with mimalloc, with musl's allocator it's 144%, so there are likely other parts that are slower (likely the memcpy implementation)
26% slower could turn into a huge hardware bill, and could render the library unusable for some purposes. There are many applications for which 26% is negligible, but it ain't nothing...
... you're fine with trading an app running 26% slower, to save a dozen megabytes ? that sounds positively insane to me. That's accepting to go from e.g. 60fps to ~45 fps (e.g. completely unacceptable)
I really find complaints about the minimum viable placeholder malloc in musl confusing. Does anyone seriously try to use malloc-ng for performance critical use cases?
Our entire linux distro is musl based BUT we swap out the default malloc with mimalloc for high performance because why would you not? Best of both worlds.
Musl's allocator being awful is pretty well known, though mostly in that it's absolutely awful in multithreaded context. TFA points out that musl has a bunch of other noticeably slower functions, which is less well known (though they're also slower by a smaller factor, and they don't worsen as your parallelism increases).
Yeah... I've recently had a chance to compare how fgets is implemented in both GNU libc and musl, and, well. With glibc, it was a challenge to even find where the fgets's code actually is.
I haven’t dug into why, but for unknown-linux builds on x86, Rust binaries have been substantially smaller on musl than standard dynamic linking to glibc, for me. No idea if I’m doing something wrong or if the handful of cases I tried were all special in some way.
I feel with Rust I try and avoid re-allocations in most cases anyway, so I'm not sure that musl's allocator being slow would significantly affect performance (though I haven't benchmarked it). I feel like part of the appeal of Rust is that you can do imperatively-style mutation-heavy code comparatively risk-free, so despite me normally being the "Functional Programming Nerd", I generally write Rust in a style that's a bit closer to C.
I use musl for my Rust stuff because I have noticed that for the stuff I write it appears to have a lower memory footprint; since a lot of what I do is IO-bound anyway, I care more about using less memory than raw performance.
If this specific use case is of high interest to you and you have some available bandwidth, contributing to it, maybe becoming a maintainer, and eventually organising a tier 2 MCP would definitely be a good idea.
Note that this is no-std no-alloc target, with all the limitations that leads to.
You could add alloc with a custom global allocator, but I don't even know what high perf global allocator you could use that wouldn't need libc. Jemalloc and mimalloc are out. Some embedded allocators would work (but those are rarely high performance, instead being optimised for small code and data footprints).
That said, with enough effort (quite a lot!) it would be possible to add support for alloc and std without libc on Linux specifically (since it has a stable syscall ABI).
What might be more realistic though is looking at relibc (a rust implementation of libc, made for Redox OS but from what I read it also supports Linux). But I haven't tried it and I don't know the state (or goal) of it.
> it would be possible to add support for alloc and std without libc on Linux specifically (since it has a stable syscall ABI).
Well yes that’s a Linux specific target so that’s kinda the point.
Technically you could do libcless on a few other platforms which are not actively hostile to it (yet) like freebsd, but that would have no chance of getting to tier 2 if it was even accepted.
I just remembered that there is also https://github.com/sunfishcode/eyra (but I think it might be a dead project) which is close to that, it had slipped my mind.
All of these are going to mean you can't link any (non-freestanding) C code, load any dylibs, etc. So you will be fairly limited in what sort of applications you can write. Forget most GUI frameworks, even native ones. You won't be able to load GL or Vulkan drivers for example. You are basically stuck with command line or servers.
I would hazard the guess that that’s perfectly fine. Desirable even. People who run scratch or alpine images and link against musl aren’t usually looking to write desktop applications or video games.
You can do FROM scratch, and use still glibc; it’s just that you need to copy more than one file. I don’t really understand if you are already dealing with images why you still need the image to contain a single file.
I swear "bifrost" has to be the most overused name in computing, possibly only behind "yggdrasil." I'm not sure what's so magnetic about those names but I've seen at least 10 different things called that.
Most of musl's performance issues come from their allocator. Using it with a third party high performance allocator allows you to benefit from static linking with very little performance loss.
> Most of musl's performance issues come from their allocator. Using it with a third party high performance allocator allows you to benefit from static linking with very little performance loss.
This is addressed and disputed very early in the article. The very first benchmark presented shows a 26% regression using musl + mimalloc, a high-performance 3rd party allocator.
It's not really disputed since musl without mimalloc has a 144% overhead, so most of the performance issues do indeed come from the allocator, by a pretty large margin (~85% of it). Not only that, but some of the "other code" performance hit might still come from the allocator: when you set a global allocator on the Rust side, musl still uses its own allocator internally (as demonstrated by https://github.com/BurntSushi/ripgrep/issues/3494).
And the compounding issue is that the allocator issues get significantly worse as parallelism increases, as the allocator is serial, so as concurrency increases so does the impact of the allocator, which is not the case for most of the "regular slow" code (of musl), those have a relatively constant overhead per thread.
"Using it with a third party high performance allocator allows you to benefit from static linking with very little performance loss" is disputed; 26% is not "very little," even if 144% is worse.
If your algorithm does a ton of small allocations to the point where the allocator is the bottleneck, you're already doing it wrong. The allocator necessarily comes with a lot of overhead because it needs to accommodate diverse use cases, avoid fragmentation, and ideally, implement a variety of security checks. If you're doing something alloc-intensive, you're probably allocating and freeing a lot of identical structures and you'd be better off grabbing some continuous memory and managing that yourself in a task-specific way.
But the reality is that almost no one actually cares about performance because compute is cheaper than expertise and labor, at least in the short haul. Everything is getting more bloated and slower and we just compensate by adding CPU cores, gigabytes and gigahertz.
That's an interesting viewpoint, but then, will the allocator's performance never matter for any use case that is not "wrong"? It doesn't feel right.
Think about it this way because the issue isn’t specific to allocators: it’s pretty good in general but can often be beaten if you have special understanding of what you need to do. That’s OK.
You can buy cars and trucks that are optimized for driving on freeways and residential streets carrying stuff people often carry. But then there are special vehicles like fork lifts and such that are kinds of large special cases. And then there are weirdo specialised vehicles that have four wheels but are rare and their users can’t live without them.
Languages like C++ let you plug in special allocators if you want. But most people don’t. Some, like HFT people do crazy headstands to avoid slow allocations. I don’t ever want to do that but if they want to, why not. I don’t think they complain that the default case doesn’t fit their needs!
For a typical program, I bet that the overall impact of the glibc allocator is well under 0.1%. If you can choose between < 0.1% and < 0.12%, I guess it matters in some sense, but not in any practical way. We almost never spend time on other sub-0.1% optimizations. You could probably squeeze a lot more by optimizing CPU branch predictor performance, minimizing CPU cache misses, or fine-tuning the scheduling strategy, but we also don't bother. 'Tis is the era of "native" apps written in Electron.
A decade ago, I worked on a simulation program that involved a C++ core with a Python wrapper and DB interface. End users cared a lot about throughout with a rather limited size, weight and power budget. We spent a lot of time optimizing the core -- but basically hit a bottleneck once we got to about 15% of the time that was spent in malloc-related functions. It turned out that was all in the Python layer. Probably there was some level of bad code in our Python code, but it was impractical to figure out where that was. I was shocked because I assumed the simulation core (which ended up almost allocation-free by the end) would always dominate CPU usage.
Both allocators and Python have probably gotten better since then, but it was a fascinatingly large and stubborn fraction of CPU time.
"But the reality is that almost no one actually cares about performance because compute is cheaper than expertise and labor, at least in the short haul."
Doesn't have to stay that way, with hardware prices soaring and development cost allegedly in free fall.
No, musl's allocator is just bad even in completely normal programs, and it is especially awful if you are using even two threads much less a lot of them. It has no TLABs or arenas. It has a single global mutex over alloc/free paths. It does syscalls underneath that lock (mmap) meaning the few fast paths it has are rarely taken under contention and have to fall back to futex wakes, so even 2 threads with minor contention and allocation rate will have visible wait points in profiles, stuck waiting for the allocator. It returns mapped memory to the OS very eagerly when a size class is empty, so even single allocs followed by a single free can cause thrashing as it mmaps/unmmaps things repeatedly for a size class over and over. Etc. You quite literally have to limit your thread count when using musl, because it will tank the performance of actually highly threaded programs that can scale with core count, even at very modest allocation rates and small working set sizes.
Its string routines and memory copy routines are also similarly bad, as the article alludes to. They are just naive loops with nearly no optimization. These are not small insignificant functions where using them is "doing it wrong", they are the backbone of vast amounts of code and can be made multiple times faster. You can similarly see string routines pop up in profiles all the time in musl builds in my experience. And unlike the memory allocator these cannot be "fixed" systematically across the application at link time, so you are stuck with it.
Real programs have to often do things like allocate memory and use multiple threads and process strings. People have been optimizing these things for decades, there is vast amounts of prior art, the musl developers simply did not do so because they prioritize simplicity over nearly everything else (from what I can tell) including performance.
It has a single global mutex over alloc/free paths. It does syscalls underneath that lock (mmap)
Every default malloc implementation worked this way about 12 years ago. Making lots of small allocations, even from multiple threads then blaming the allocator is a losing strategy. An allocator is only going to be able to mitigate the damage to speed and interactivity.
The solution is and always has been to make larger allocations and use those efficiently.
They are just naive loops with nearly no optimization.
The compiler should be able to take something with good access patterns and make something fast, especially out of the basic C functions.
they are the backbone of vast amounts of code
Performance wise it's unlikely C string functions are actually the bottleneck in a program. Maybe for specific programs a naive memory copy function could benefit from AVX instructions.
Real programs have to often do things like allocate memory
"Have to" and "often" are debatable. Any allocations in a hot loop are the very first things that should be optimized away after profiling.
>Performance wise it's unlikely C string functions are actually the bottleneck in a program. Maybe for specific programs a naive memory copy function could benefit from AVX instructions.
Many programs use lots of strings. It tends to become a bottleneck. It also tends to be very difficult to improve because the strings are everywhere in that kind of program, and refactoring to eliminate them is either impossible or very risky.
Many programs use lots of strings. It tends to become a bottleneck.
I would dispute this in anything that isn't mostly about string processing and in that case you can always easily grab different string functions, which you should probably do anyway if strings are that important.
It also tends to be very difficult to improve because the strings are everywhere in that kind of program,
I don't know what 'that kind of program' is supposed to mean.
and refactoring to eliminate them is either impossible or very risky.
This doesn't sound like a general purpose statement that applies to anything broadly.
All I'm saying is the the title is wrong and musl doesn't do much to prevent speed in a program. If someone was really trying to optimize, blaming the standard library is not going to get them very far and it's easy to work around, but needing to do that is very rare.
>I would dispute this in anything that isn't mostly about string processing and in that case you can always easily grab different string functions, which you should probably do anyway if strings are that important.
I'm telling you that I've seen it, in stuff as diverse as video games and robotics. Lots of things use strings as values. It's easy to say "just change everything in millions of lines of code" when you aren't the one who has to make that change.
By the way most software does copious amounts of string processing... I think that should be common knowledge, but I guess it isn't.
>This doesn't sound like a general purpose statement that applies to anything broadly.
You sound like you have zero experience. If your config is in strings, and hundreds of thousands of lines of code already rely on the string-ness of the data, then you just can't make the change easily.
>All I'm saying is the the title is wrong and musl doesn't do much to prevent speed in a program. If someone was really trying to optimize, blaming the standard library is not going to get them very far and it's easy to work around, but needing to do that is very rare.
I believe the title is accurate. People in performance-sensitive areas gripe about libraries, even standard libraries, quite often. I don't mean to insult you but you're making bold assertions despite clearly lacking the experience to know how things are done in industry generally.
> Every default malloc implementation worked this way about 12 years ago.
Perhaps "default" is doing the heavy lifting here. Glibc malloc was quite bad for a long time, true. But TCmalloc / jemalloc are 21-22 years old, respectively, and jemalloc has been the FreeBSD (released) default malloc implementation for the last 18.
> The solution is and always has been to make larger allocations and use those efficiently.
Having a not-dogshit allocator really doesn't hurt. There's no reason to defend shitty allocator + every application doing manual memory pools on top of it to paper over the bad allocator.
I'm not defending anything, I'm saying it's usually trivial to make allocation time marginal.
+ every application doing manual memory pools
Usually it's simple data structures in flat memory.
If allocation is taking all the time, that's a poorly optimized program with lots of low hanging fruit and a different allocator is not the right fix. It's like having a boat with a hole in the bottom and someone says the solution is a smaller hole.
But TCmalloc / jemalloc are 21-22 years old, respectively, and jemalloc has been the FreeBSD (released) default malloc implementation for the last 18.
jemalloc is also possibly bigger than all of musl. If it was a problem after optimization I would use it and I have in the past, it's just nowhere near as important as minimizing allocations in the first place. OpenBSD uses straight mmap.
There's also a reason this stuff started getting adopted around 20 years ago (I'll add macOS to the pile: it added per-CPU malloc sharding in 2008). It's not just due to overall growth in OS complexity. It's because that's when multicore CPUs were taking off. Before that, the cost of a global lock was far lower.
OpenBSD is straight unconcerned about performance. That's their choice.
Yes, it is now 12 years later, and memory allocators are better. The memory allocators of that time were also better than the ones 12 years their prior. That's the point.
It's just a reality that musl is measurably worse at multiple threads allocating even in very polite conditions, because it causes lots of contention. If your program allocates in multiple threads, it is probably going to get slower with musl. If you don't want that, other memory allocators will do great even at high allocation rates with more threads. You could write many other data structures that had equally poor behavior under multi-threaded contention by just throwing a lock around everything and calling it a day, and those bad data structures would also cause "damage to speed and interactivity" or whatever. This isn't very hard to understand.
I agree, modern compilers are good. But these are extremely common specified functions, they are called everywhere all the time in every C codebase (and that's partially why compilers even recognize these patterns specifically so they can insert optimized routines). Mature implementations that are hand optimized still pay off and also tend to be tuned for various edge cases or quirks that aren't going to come for free from the C compiler either, so it's still work even if you aren't writing assembly for everything or whatever (e.g. uarch dependent codepaths, or optimizations for short strings or whatever).
glibc's AVX2 based memcpy functions have a non-negligible performance impact in at least 1 application I maintain on the order of like 8-ish% vs musl (wall clock). It just has to memcpy/memmove a whole lot. Whether or not that's tolerable is up to debate, but a spade is a spade.
I said "backbone", not "bottleneck". They are common functions sprinkled in everywhere throughout every application in every codepath on something like a modern Linux desktop. An inverted callstack flamegraph can show you stuff like this. It is basically no different than compiling your application at -O1 and -O2 with GCC. Does the fact your program get 20% faster from -O2 mean that there were "bottlenecks" the compiler solved? No, there was just performance left on the table by emitting better code.
Not really. I have to spell it out apparently: actual programs written by normal human programmers do those things, all the time, they exist in and are common in the world, they depend on other code that does that and is common in the world, they run on your desktop and phone and all servers, and they benefit quite a lot from optimized components like memory allocators and string routines and -O2 making their programs faster. This is pretty easy to observe and the means of doing so should be quite obvious, so there's no real debate.
Now whether this fact holds -- whether these programs "have to" do these things or not -- in the imaginary fantasy land people have in their heads where they make up arguments to themselves about how, if every program was written how they liked it, it would be better? That I'm not so sure about, I will admit.
The memory allocators of that time were also better than the ones 12 years their prior. That's the point.
The point is that memory allocation shouldn't be a bottleneck either way. If it is the program needs to be optimized or redesigned. Better allocators give you more slack, they don't solve the problem. If the problem is already solved, then a basic allocator isn't going to make a big performance difference because it isn't the bottleneck.
those bad data structures would also cause "damage to speed and interactivity" or whatever. This isn't very hard to understand.
It depends on how much they are used and how much contention there is. Sometimes putting a mutex around things is fine.
But these are extremely common specified functions, they are called everywhere all the time
Not necessarily, especially for C string functions, but they do get linked in so it's a good thing musl makes them small.
I said "backbone", not "bottleneck".
Then the point is lost, because 'backbone' doesn't mean anything if it works. If it isn't a bottleneck in throughput or latency anywhere then the speed doesn't matter.
The other important thing is that better stuff can be included in pieces as it's needed. The reverse isn't true. If you use a big fat C library, you have a dependency that isn't going to get better.
Not really. I have to spell it out apparently: actual programs written by normal human programmers do those things, all the time,
You spelled it out last time, it's just not true in the sense that programs have to have these functions as bottlenecks. Strings, allocators and memory copying can all be dealt with independently, but again it's rare that strings and allocations really need to be the bottleneck and in those circumstances you probably want more than a different standard library anyway.
in the imaginary fantasy land people have in their heads where they make up arguments to themselves about how, if every program was written how they liked it,
I'm not sure what this is supposed to mean, there is nothing I've said that doesn't make perfect sense. If you want something to go faster you can make it go faster. A better allocator pales in comparison to lifting allocations out of hot loops.
My point is the musl is useful and the disadvantages are easy to work around. I'm not really sure what your point is, do you think people are going to force you to use it?
People have such different perspectives. 26% slower does not sound "terrible" to me; it sounds like quite a reasonable price one might choose to pay for the convenience musl offers. If musl's allocator were 2.6x slower, I might call that "not so great"... but in order to qualify as "terrible" I think the difference would have to be an order of magnitude!
The 26% number at the top of the article is from using mimalloc (which is a high performance allocator, at least as fast as the glibc allocator) + musl for some task, and the slowdown is coming from (probably) slow musl implementations of memcpy/memset. The musl allocator is even worse.
> the slowdown is coming from (probably) slow musl implementations of memcpy/memset.
It's wild that such a fundamental piece of code (you can't really implement operation on structs without those) is library-supplied. I wish compilers would just have something like __builtin_memcpy and __builtin_memset, and provided some highly optimized, specialist-crafted assembly in those, instead of having to inline the library code and hopefully be able to optimize it.
Maybe you're being sarcastic, but I'm pretty sure clang + gcc do offer these.
The problems at first glance :
- Not having control over the implementation detail of the interface that your library provides is probably not wise. Sounds like a lot of bad bug reports and edge cases that you have no control over.
- Not all compilers may provide these.
As others have alluded, __builtin_memcpy doesn't resolve to a runtime implementation. GCC and clang treat functions like memcpy specially. Because they're defined by the standard and are reserved names, compilers can assume the exact semantics specified by the standard and elide library calls altogether with optimized inline code. But if the compiler can't do the optimization (can't prove alignment, indeterminate length, etc), it just emits a library call, even if your source has some other local function definition named "memcpy". Explicit use of __builtin_memcpy is treated identically to calls to memcpy, unless the compiler is invoked with -ffreestanding, in which case it only optimizes __builtin_memcpy and skips special treatment of calls to memcpy, but __builtin_memcpy could still expand into a call to memcpy. If you're writing a C library you want to use -ffreestanding. (I think. There may be more nuance. More info at https://gcc.gnu.org/bugzilla/show_bug.cgi?id=56888)
Clang and GCC do provide these, and automatically use them in many situations (particularly small copies). But c-libraries can actually do it better in many cases, especially for large copies.
Glibc, for example, has perhaps ten different implementations of memcpy just for x86. The compiler certainly could provide all that, but the next step is harder:
glibc automatically dispatches to the proper one at runtime based on the actual microarchitecture that the binary is running on. You pay the extra dispatch cost once, but all of non-inline function call cost every time. This is what allows distros to compile to a nice baseline architecture, but still get near-optimal memcpy performance on many more architectures than a single inline instance could possibly give. These differences matter.
And it does it for not just memcpy, but half-a-dozen other extremely performance sensitive library functions, like strcpy and so on.
Inlining works very much against this strategy. If you can guarantee that the target microarch never changes, then it isn't a good one. But that is somewhat unusual for everyone but those who build their own binaries to run on a single class of machines forever.
Worse, inlining the really high performance versions of these ends up being terrible from a code size perspective, because they are often hundreds of instructions, which can have bad caching effects. And once you amortize the function-call cost over many iterations of the loop, it isn't so expensive to call out to the library.
Anyway, just some additional considerations to think about.
> I wish compilers would just have something like __builtin_memcpy and __builtin_memset
The ones provided by the compilers are simply the libc ones.
LLVM will even go as far as detect attempts to rewrite memcpy and replace them with a call to the libc one!
Even if the attempt is inside of a function called memcpy() which contains no code other than your copy loop, and links with priority over the libc implementation! (as all embedded firmware engineers learn at some point in their journey)
These builtins of course exist, it's how compilers keep track of the behavior of these functions.
For GCC, there is -minline-all-stringops:
https://gcc.gnu.org/onlinedocs/gcc-16.2.0/gcc/x86-Options.ht...
It does what it says, but the results may not be what you expect.
Yeah, doing compute-heavy work a couple of jobs ago, we tried small images with musl, and the default allocator was a catastrophe: 75%+ slowdowns for our real life tasks. Even with a better allocator, we were way better off with the larger image.
Ops here, I think if you NEED that convenience, sure, rock with MUSL BUT I also see a ton of devs crowing about using MUSL on my 128GB x86 Kubernetes hosts. I have plenty of Disk Space, you can ship glibc based container.
The 26% slower appears to be for their whole application, not just the allocator. For some parts of the application to make the whole this much slower it must mean that those parts are quite a lot slower, likely much more than 2x.
Moreover the 26% is with mimalloc, with musl's allocator it's 144%, so there are likely other parts that are slower (likely the memcpy implementation)
Tell your employer a 26% pay decrease for you is acceptable.
I'm curious. What convenience, specifically, are people benefiting from by using musl?
The convenience (?) of not having to comply with GPL terms. Some people really hate copyleft.
Glibc is lgpl, you _definitely_ don't need to comply with GPL to link to it.
If you want to ship a prebuilt binary that'll run on any linux distro you need to statically link libc and musl is by far the easiest way to do that.
except it only can work for CLI apps or anything that doesn't use the GPU as for instance nvidia drivers require glibc
26% slower could turn into a huge hardware bill, and could render the library unusable for some purposes. There are many applications for which 26% is negligible, but it ain't nothing...
> for the convenience musl offers
... you're fine with trading an app running 26% slower, to save a dozen megabytes ? that sounds positively insane to me. That's accepting to go from e.g. 60fps to ~45 fps (e.g. completely unacceptable)
This is only one aspect of "performance". glibc's allocator may be faster, but it also uses more memory.
For a much more technical discussion, see https://github.com/sharkdp/fd/issues/710
I really find complaints about the minimum viable placeholder malloc in musl confusing. Does anyone seriously try to use malloc-ng for performance critical use cases?
Our entire linux distro is musl based BUT we swap out the default malloc with mimalloc for high performance because why would you not? Best of both worlds.
https://codeberg.org/stagex/stagex/src/branch/main/packages/...
Posted this the other day but the whole musl allocator thing seems to be well known [0]
[0]: https://news.ycombinator.com/item?id=45143347
Musl's allocator being awful is pretty well known, though mostly in that it's absolutely awful in multithreaded context. TFA points out that musl has a bunch of other noticeably slower functions, which is less well known (though they're also slower by a smaller factor, and they don't worsen as your parallelism increases).
I think the size of linked binaries and simplicity were always the main features?
Yeah... I've recently had a chance to compare how fgets is implemented in both GNU libc and musl, and, well. With glibc, it was a challenge to even find where the fgets's code actually is.
I haven’t dug into why, but for unknown-linux builds on x86, Rust binaries have been substantially smaller on musl than standard dynamic linking to glibc, for me. No idea if I’m doing something wrong or if the handful of cases I tried were all special in some way.
I feel with Rust I try and avoid re-allocations in most cases anyway, so I'm not sure that musl's allocator being slow would significantly affect performance (though I haven't benchmarked it). I feel like part of the appeal of Rust is that you can do imperatively-style mutation-heavy code comparatively risk-free, so despite me normally being the "Functional Programming Nerd", I generally write Rust in a style that's a bit closer to C.
I use musl for my Rust stuff because I have noticed that for the stuff I write it appears to have a lower memory footprint; since a lot of what I do is IO-bound anyway, I care more about using less memory than raw performance.
Are there other options if I want to ship a 'FROM scratch' image with just a single Rust executable, and everything compiled in?
That to me is the main driver for MUSL.
Same usecase here, I use musl for compiling self contained Nim utilities I use on containers and servers without having to deal with glibc hell.
The best option would be the x86_64-unknown-linux-none target (https://doc.rust-lang.org/nightly/rustc/platform-support/x86...) however it currently a tier 3 with a single maintainer (so it is technically available but unsupported).
If this specific use case is of high interest to you and you have some available bandwidth, contributing to it, maybe becoming a maintainer, and eventually organising a tier 2 MCP would definitely be a good idea.
Note that this is no-std no-alloc target, with all the limitations that leads to.
You could add alloc with a custom global allocator, but I don't even know what high perf global allocator you could use that wouldn't need libc. Jemalloc and mimalloc are out. Some embedded allocators would work (but those are rarely high performance, instead being optimised for small code and data footprints).
That said, with enough effort (quite a lot!) it would be possible to add support for alloc and std without libc on Linux specifically (since it has a stable syscall ABI).
What might be more realistic though is looking at relibc (a rust implementation of libc, made for Redox OS but from what I read it also supports Linux). But I haven't tried it and I don't know the state (or goal) of it.
> it would be possible to add support for alloc and std without libc on Linux specifically (since it has a stable syscall ABI).
Well yes that’s a Linux specific target so that’s kinda the point.
Technically you could do libcless on a few other platforms which are not actively hostile to it (yet) like freebsd, but that would have no chance of getting to tier 2 if it was even accepted.
I just remembered that there is also https://github.com/sunfishcode/eyra (but I think it might be a dead project) which is close to that, it had slipped my mind.
All of these are going to mean you can't link any (non-freestanding) C code, load any dylibs, etc. So you will be fairly limited in what sort of applications you can write. Forget most GUI frameworks, even native ones. You won't be able to load GL or Vulkan drivers for example. You are basically stuck with command line or servers.
I would hazard the guess that that’s perfectly fine. Desirable even. People who run scratch or alpine images and link against musl aren’t usually looking to write desktop applications or video games.
You can do FROM scratch, and use still glibc; it’s just that you need to copy more than one file. I don’t really understand if you are already dealing with images why you still need the image to contain a single file.
I swear "bifrost" has to be the most overused name in computing, possibly only behind "yggdrasil." I'm not sure what's so magnetic about those names but I've seen at least 10 different things called that.
Also musl is not a complete runtime
Funny thing is that the major reason most people use musl is because glibc make it (artificially) hard to do completely static linking.
Most of musl's performance issues come from their allocator. Using it with a third party high performance allocator allows you to benefit from static linking with very little performance loss.
> Most of musl's performance issues come from their allocator. Using it with a third party high performance allocator allows you to benefit from static linking with very little performance loss.
This is addressed and disputed very early in the article. The very first benchmark presented shows a 26% regression using musl + mimalloc, a high-performance 3rd party allocator.
It's not really disputed since musl without mimalloc has a 144% overhead, so most of the performance issues do indeed come from the allocator, by a pretty large margin (~85% of it). Not only that, but some of the "other code" performance hit might still come from the allocator: when you set a global allocator on the Rust side, musl still uses its own allocator internally (as demonstrated by https://github.com/BurntSushi/ripgrep/issues/3494).
And the compounding issue is that the allocator issues get significantly worse as parallelism increases, as the allocator is serial, so as concurrency increases so does the impact of the allocator, which is not the case for most of the "regular slow" code (of musl), those have a relatively constant overhead per thread.
"Using it with a third party high performance allocator allows you to benefit from static linking with very little performance loss" is disputed; 26% is not "very little," even if 144% is worse.