I am stuck in an environment with CMake, GCC and Unix Make (no clang, no ninja) and getting detailed information about WHY the build is taking so long is nearly impossible.
It's also a bit of a messy build with steps like copying a bunch of files from the source into the build folder. Multiple languages (C, C++, Fortran, Python), custom cmake steps, etc.
If this tool can handle that kind of mess, I'll be very interested to see what I can learn.
Tsoding wrote https://github.com/tsoding/nob.h, single header C library for cross platform builds, only requirement is cc. GDB profiling tools can then be used to look at your build step. It's a neat idea. I suspect this is not an option but Nix is great build tool if you are dealing with multiple languages.
It's not "nearly impossible" but actually built in: https://cmake.org/cmake/help/latest/manual/cmake.1.html#cmdo... For the actual compile time you can easily insert a wrapper script. To be honest I haven't done that in over 4 years, but it has been done by many and it is easy.
There may be times when CMake itself is the bottleneck but it is almost certainly an issue with your dependencies and so on. CMake has many features to assist you in speeding up your compile and link time too. But it would take a series of blog posts to describe how you should try to speed it up.
When I was trying to improve compile time for my game engine, I ended up using compiled size as a proxy measure. Although it is an imperfect correlation, the fact that compiled size is deterministic across build runs and even across builds on different machines makes it easier to work with than wall clock time.
> I am stuck in an environment with CMake, GCC and Unix Make (no clang, no ninja) and getting detailed information about WHY the build is taking so long is nearly impossible.
I have a similar problem, with a tangential question that I think about from time to time without really having the time to investigate it further, unfortunately.
I notice sometimes that CMake recompiles files that shouldn't have been affected by the code changes made previously. Like recompiling some independent objects after only slight changes to a .cpp file without any interface changes.
So I often wonder if CMake is not making some file more inter-dependent than what they are, leading to longer compilation times.
Love it!
We did something similar using strace/dtruss back in 2018 with https://buildinfer.loopperfect.com/ and were generating graphs (using eg. graphviz and perfetto.dev) and BUCK files on the back of that
Whilst we regrettably never came around to package it as a propper product, we found it immensly valuable in our consulting work, to pinpoint issues and aid the conversion to BUCK/Bazel.
We used graphviz, https://perfetto.dev/ and couple other tools to visualise things
Recently we cicled back to this too but with a broader usecase in mind.
There are some inherent technical challanges with this approach & domain:
- syscall logs can get huge - especially when saved to disk. Our strace logs would get over 100GB for some projects (llvm was around ~50GB)
- some projects also use https and inter process communications and that needs ot be properly handled too. (We even had a customer that was retriving code from a firebird database via perl as part of the compilation step!)
- It's runtime analysis - you might need to repeat the analysis for each configuration.
That's really cool. Fascinating to think about all the problems that get missed due to poor or missing visualizations like this.
I did a lot of work to improve the Mozilla build system a decade ago where I would have loved this tool. Wish they would have said what problem they found.
If you use the Visual C++ compiler on Windows, vcperf is worth a look: https://github.com/microsoft/vcperf - comes with VS2022, or you can build from github.
I've used it with projects generated by UBT and CMake. I can't remember if it provides any info that'd let you assess the quality of build parallelism, but it does have some compiler front end info which is pretty straightforward to read. Particularly expensive headers (whether inherently so, or just because they're included a lot) are easy to find.
> It also has 6 seconds of inactivity before starting any useful work. For comparison, ninja takes 0.4 seconds to start compiling the 2,468,083 line llvm project. Ninja is not a 100% fair comparison to other tools, because it benefits from some “baked in” build logic by the tool that created the ninja file, but I think it’s a reasonable “speed of light” performance benchmark for build systems.
This is an important observation that is often overlooked. What’s more, the changes to the information on which this “baked in” build logic is based is not tracked very precisely.
How close can we get to this “speed of light” without such “baking in”? I ran a little benchmark (not 100% accurate for various reasons but good enough as a general indication) which builds the same project (Xerces-C++) both with ninja as configured by CMake and with build2, which doesn’t require a separate step and does configuration management as part of the build (and with precise change tracking). Ninja builds this project from scratch in 3.23s while build2 builds it in 3.54s. If we omit some of the steps done by CMake (like generating config.h) by not cleaning the corresponding files, then the time goes down to 3.28s. For reference, the CMake step takes 4.83s. So a fully from-scratch CMake+ninja build actually takes 8s, which is what you would normally pay if you were using this project as a dependency.
> What’s more, the changes to the information on which this “baked in” build logic is based is not tracked very precisely.
kbuild handles this on top of Make by having each target depend on a dummy file that gets updated when e.g. the CFLAGS change. It also treats Make a lot more like Ninja (e.g. avoiding putting the entire build graph into every Make process) -- I'd be interested to see how it compares.
I love the visualization, I think it's great information and will be very helpful to whoever uses it.
I would think about a different name. Often names are either meant to be funny or just unique nonsense but something short and elegantly descriptive (like BuildViz etc.) can go a long way to making it seem more legitimate and being more widely used.
I'll be sending out the a macOS version to another wave of beta users after I fix an outstanding issue, if you sign up (at bottom of article) and mention this comment I can make sure you're in that wave.
I've done something similar by running Instruments during the build, which not only tells me which processes are running when but also what they're doing. Unfortunately Instruments gets upset if your build takes a long time, and it doesn't really allow filtering by process tree, but it helped shipped several major wins for our builds when I was working on Twitter's iOS codebase. Alas trying to this these days will not work because Instrument's "All Processes" tracing has been broken for a while (FB14533747).
Really cool tool, but perhaps not for the original use-case. I often find myself trying to figure out what call tree a large Bash script creates, and this looks like it visualises it well.
This would have been really useful 6 months ago, when I was trying to figure out what on earth some Jetson tools actually did to build and flash an OS image.
Is there a tool that records the timestamp of each executed command during a build, and when you rebuild, it tells you how much time is left instead of "building obj 35 out of 1023" ?
Or (for cmake or ninja) use a CSV that says how long each object takes to build and use it to estimate how much is left ?
OP Here. Thats an interesting idea. What The Fork knows all the commands run, and every path they read/write, so I should be able to make it estimate build time just by looking at what files were touched.
Nice, I’ve been looking for something like this for a while.
I’ve noticed on my huge catkin cmake project that cmake is checking the existence of the same files hundreds of times too. Is there anything that can hook into fork() and provide a cached value after the first invocation?
My tips for speeding up builds (from making this same project but with ebpf):
- switch to ninja to avoid that exact issue since CMake + Make spawns a subprocess for every directory (use the binary from PyPi for jobserver integration)
- catkin as in ROS? rm /opt/ros/noetic/etc/catkin/profile.d/99.roslisp.sh to remove 2 python spawns per package
You could try ccache with the CCACHE_SLOPPINESS=file_stat_matches option, or implement a filesystem-level caching proxy like CachingFS or FUSE-based solutions that intercept and cache those redundant stat() calls.
Thank you! Yeah it can be used for any type of program, but I haven't been able to think of anything besides compilation that creates enough processes to be interesting. I'm open to ideas!
It visualizes each crate's build, shows the dependencies between them, shows when the initial compilation is done that unblocks dependents, and soon will have link information.
It looks really nice. I wonder if it’d be possible to break it down even further by somehow instrumenting the actual processes and including their execution flame graphs as part of the chart. That would expose a ton of extra information about the large gaps of “inactivity”.
the parallels between tech and manufacturing never cease to amaze, this looks so much like the machine monitoring / execution system we use in the car parts plant I want to ask if you've calculated the TEEP and OEE of your build farm
A CMake build is used as an example in the blog post. It's literally just visualizing all spawned processes, so it will work for anything that spawns subprocesses to do the build.
here, I'll copy the first paragraph of TFA for you:
> Many software projects take a long time to compile. Sometimes that’s just due to the sheer amount of code, like in the LLVM project. But often a build is slower than it should be for dumb, fixable reasons.
Night_Thastus|6 months ago
I am stuck in an environment with CMake, GCC and Unix Make (no clang, no ninja) and getting detailed information about WHY the build is taking so long is nearly impossible.
It's also a bit of a messy build with steps like copying a bunch of files from the source into the build folder. Multiple languages (C, C++, Fortran, Python), custom cmake steps, etc.
If this tool can handle that kind of mess, I'll be very interested to see what I can learn.
unddoch|6 months ago
hagendaasalpine|6 months ago
wakawaka28|6 months ago
There may be times when CMake itself is the bottleneck but it is almost certainly an issue with your dependencies and so on. CMake has many features to assist you in speeding up your compile and link time too. But it would take a series of blog posts to describe how you should try to speed it up.
phaedrus|6 months ago
fransje26|6 months ago
I have a similar problem, with a tangential question that I think about from time to time without really having the time to investigate it further, unfortunately.
I notice sometimes that CMake recompiles files that shouldn't have been affected by the code changes made previously. Like recompiling some independent objects after only slight changes to a .cpp file without any interface changes.
So I often wonder if CMake is not making some file more inter-dependent than what they are, leading to longer compilation times.
unknown|6 months ago
[deleted]
1718627440|6 months ago
pklausler|6 months ago
Mawr|6 months ago
> Here it is recording the build of a macOS app:
> <gif>
At the top of the page, it should be right under the header.
You made a thing, so show the thing. You can waffle on about it later. Just show the thing.
dhooper|6 months ago
entelechy|6 months ago
Whilst we regrettably never came around to package it as a propper product, we found it immensly valuable in our consulting work, to pinpoint issues and aid the conversion to BUCK/Bazel. We used graphviz, https://perfetto.dev/ and couple other tools to visualise things
Recently we cicled back to this too but with a broader usecase in mind.
There are some inherent technical challanges with this approach & domain:
- syscall logs can get huge - especially when saved to disk. Our strace logs would get over 100GB for some projects (llvm was around ~50GB)
- some projects also use https and inter process communications and that needs ot be properly handled too. (We even had a customer that was retriving code from a firebird database via perl as part of the compilation step!)
- It's runtime analysis - you might need to repeat the analysis for each configuration.
flakes|6 months ago
bgirard|6 months ago
I did a lot of work to improve the Mozilla build system a decade ago where I would have loved this tool. Wish they would have said what problem they found.
dhooper|6 months ago
My call with the Mozilla engineer was cut short, so we didn't have time to go into detail about what he found, I want to look into it myself.
tom_|6 months ago
I've used it with projects generated by UBT and CMake. I can't remember if it provides any info that'd let you assess the quality of build parallelism, but it does have some compiler front end info which is pretty straightforward to read. Particularly expensive headers (whether inherently so, or just because they're included a lot) are easy to find.
muststopmyths|6 months ago
bdash|6 months ago
boris|6 months ago
This is an important observation that is often overlooked. What’s more, the changes to the information on which this “baked in” build logic is based is not tracked very precisely.
How close can we get to this “speed of light” without such “baking in”? I ran a little benchmark (not 100% accurate for various reasons but good enough as a general indication) which builds the same project (Xerces-C++) both with ninja as configured by CMake and with build2, which doesn’t require a separate step and does configuration management as part of the build (and with precise change tracking). Ninja builds this project from scratch in 3.23s while build2 builds it in 3.54s. If we omit some of the steps done by CMake (like generating config.h) by not cleaning the corresponding files, then the time goes down to 3.28s. For reference, the CMake step takes 4.83s. So a fully from-scratch CMake+ninja build actually takes 8s, which is what you would normally pay if you were using this project as a dependency.
remexre|6 months ago
kbuild handles this on top of Make by having each target depend on a dummy file that gets updated when e.g. the CFLAGS change. It also treats Make a lot more like Ninja (e.g. avoiding putting the entire build graph into every Make process) -- I'd be interested to see how it compares.
CyberDildonics|6 months ago
I would think about a different name. Often names are either meant to be funny or just unique nonsense but something short and elegantly descriptive (like BuildViz etc.) can go a long way to making it seem more legitimate and being more widely used.
dhooper|6 months ago
hiccuphippo|6 months ago
torarnv|6 months ago
aanet|6 months ago
Is there a version available for MacOS today?? I'd love to give it a whirl... For Rust, C++ / Swift and other stuff.
Thanks!
dhooper|6 months ago
Night_Thastus|6 months ago
saagarjha|6 months ago
forrestthewoods|6 months ago
JackYoustra|6 months ago
audiofish|6 months ago
This would have been really useful 6 months ago, when I was trying to figure out what on earth some Jetson tools actually did to build and flash an OS image.
xuhu|6 months ago
Or (for cmake or ninja) use a CSV that says how long each object takes to build and use it to estimate how much is left ?
dhooper|6 months ago
tiddles|6 months ago
I’ve noticed on my huge catkin cmake project that cmake is checking the existence of the same files hundreds of times too. Is there anything that can hook into fork() and provide a cached value after the first invocation?
lights0123|6 months ago
- switch to ninja to avoid that exact issue since CMake + Make spawns a subprocess for every directory (use the binary from PyPi for jobserver integration)
- catkin as in ROS? rm /opt/ros/noetic/etc/catkin/profile.d/99.roslisp.sh to remove 2 python spawns per package
ethan_smith|6 months ago
supportengineer|6 months ago
What limits your tool to compiler/build tools, can it be used for any arbitrary process?
dhooper|6 months ago
pjmlp|6 months ago
Without trying to devalue it, note that VS and XCode have similar visualization tools.
jeffbee|6 months ago
MathMonkeyMan|6 months ago
epage|6 months ago
It visualizes each crate's build, shows the dependencies between them, shows when the initial compilation is done that unblocks dependents, and soon will have link information.
tempodox|6 months ago
terabytest|6 months ago
proctorg76|6 months ago
rustystump|6 months ago
corysama|6 months ago
ItsHarper|6 months ago
secondcoming|6 months ago
I've used clang's -ftime-trace option in the past and that's also really good. It's a pity gcc has nothing similar.
time4tea|6 months ago
This is an ad not a helpful announcement.
bitbasher|6 months ago
lsuresh|6 months ago
mrlonglong|6 months ago
MBCook|6 months ago
ItsHarper|6 months ago
Cloudef|6 months ago
emigre|6 months ago
brcmthrowaway|6 months ago
dhooper|6 months ago
mgaunard|6 months ago
Developers always get it wrong and do it badly.
kirito1337|6 months ago
metalliqaz|6 months ago
Surac|6 months ago
rvrb|6 months ago
> Many software projects take a long time to compile. Sometimes that’s just due to the sheer amount of code, like in the LLVM project. But often a build is slower than it should be for dumb, fixable reasons.
klik99|6 months ago