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Today, some more words on memory management, on the practicalities of a system with conservatively-traced references. The context is that I have finally started banging into , initially in a configuration that continues to use the conservative Boehm-Demers-Weiser (BDW) collector behind the scene. In that way I can incrementally migrate over all of the uses of the BDW API in Guile to use Whippet API instead, and then if all goes well, I should be able to switch Whippet to use another GC algorithm, probably the . MMC scales better than BDW for multithreaded mutators, and it can eliminate fragmentation via Immix-inspired optimistic evacuation.WhippetGuilemostly-marking collector (MMC) A garbage-collected heap consists of memory, which is a set of addressable locations. An object is a disjoint part of a heap, and is the unit of allocation. A field is memory within an object that may refer to another object by address. Objects are nodes in a directed graph in which each edge is a field containing an object reference. A root is an edge into the heap from outside. Garbage collection reclaims memory from objects that are not reachable from the graph that starts from a set of roots. Reclaimed memory is available for new allocations. In the course of its work, a collector may want to relocate an object, moving it to a different part of the heap. The collector can do so if it can update all edges that refer to the object to instead refer to its new location. Usually a collector arranges things so all edges have the same representation, for example an aligned word in memory; updating an edge means replacing the word’s value with the new address. Relocating objects can improve locality and reduce fragmentation, so it is a good technique to have available. (Sometimes we say evacuate, move, or compact instead of relocate; it’s all the same.) Some collectors allow edges: words in memory whose value may be the address of an object, or might just be scalar data. Ambiguous edges usually come about if a compiler doesn’t precisely record which stack locations or registers contain GC-managed objects. Such ambiguous edges must be traced : the collector adds the object to its idea of the set of live objects, as if the edge were a real reference. This tracing mode isn’t supported by all collectors.ambiguousconservatively Any object that might be the target of an ambiguous edge cannot be relocated by the collector; a collector that allows conservative edges cannot rely on relocation as part of its reclamation strategy. Still, if the collector can know that a given object will not be the referent of an ambiguous edge, relocating it is possible. How can one know that an object is not the target of an ambiguous edge? We have to partition the heap somehow into possibly-conservatively-referenced and definitely-not-conservatively-referenced. The two ways that I know to do this are spatially and temporally. Spatial partitioning means that regardless of the set of root and intra-heap edges, there are some objects that will never be conservatively referenced. This might be the case for a type of object that is “internal” to a language implementation; third-party users that may lack the discipline to precisely track roots might not be exposed to objects of a given kind. Still, link-time optimization tends to weather these boundaries, so I don’t see it as being too reliable over time. Temporal partitioning is more robust: if all ambiguous references come from roots, then if one traces roots before intra-heap edges, then any object not referenced after the roots-tracing phase is available for relocation. So let’s talk about Guile! Guile uses BDW currently, which considers edges to be ambiguous by default. However, given that objects carry type tags, Guile can, with relatively little effort, switch to precisely tracing most edges. “Most”, however, is not sufficient; to allow for relocation, we need to intra-heap ambiguous edges, to confine conservative tracing to the roots-tracing phase.eliminate Conservatively tracing references from C stacks or even from static data sections is not a problem: these are roots, so, fine. Guile currently traces Scheme stacks almost-precisely: its compiler emits stack maps for every call site, which uses liveness analysis to only mark those slots that are Scheme values that will be used in the continuation. However it’s possible that any given frame is marked conservatively. The most common case is when using the BDW collector and a thread is pre-empted by a signal; then its most recent stack frame is likely not at a safepoint and indeed is likely undefined in terms of Guile’s VM. It can also happen if there is a call site within a VM operation, for example to a builtin procedure, if it throws an exception and recurses, or causes GC itself. Also, when are enabled, we can run Scheme between any two Guile VM operations.per-instruction traps So, Guile could change to trace Scheme stacks fully precisely, but this is a lot of work; in the short term we will probably just trace Scheme stacks as roots instead of during the main trace. However, there is one more significant source of ambiguous roots, and that is reified continuation objects. Unlike active stacks, these have to be discovered during a trace and cannot be partitioned out to the root phase. For delimited continuations, these consist of a slice of the Scheme stack. Traversing a stack slice precisely is less problematic than for active stacks, because it isn’t in motion, and it is captured at a known point; but we will have to deal with stack frames that are pre-empted in unexpected locations due to exceptions within builtins. If a stack map is missing, probably the solution there is to reconstruct one using local flow analysis over the bytecode of the stack frame’s function; time-consuming, but it should be robust as we do it elsewhere. Undelimited continuations (those captured by ) contain a slice of the C stack also, for historical reasons, and there we can’t trace it precisely at all. Therefore either we disable relocation if there are any live undelimited continuation objects, or we eagerly pin any object referred to by a freshly captured stack slice.call/cc If you want to follow along with the Whippet-in-Guile work, see the branch in Git. I’ve bumped its version to 4.0 because, well, why the hell not; if it works, it will certainly be worth it. Until next time, happy hacking!wip-whippet problem statement: how to manage ambiguous edges kinds of ambiguous edges in guile fin
Earlier this weekGuileWhippet But now I do! Today’s note is about how we can support untagged allocations of a few different kinds in Whippet’s .mostly-marking collector Why bother supporting untagged allocations at all? Well, if I had my way, I wouldn’t; I would just slog through Guile and fix all uses to be tagged. There are only a finite number of use sites and I could get to them all in a month or so. The problem comes for uses of from outside itself, in C extensions and embedding programs. These users are loathe to adapt to any kind of change, and garbage-collection-related changes are the worst. So, somehow, we need to support these users if we are not to break the Guile community.scm_gc_malloclibguile The problem with , though, is that it is missing an expression of intent, notably as regards tagging. You can use it to allocate an object that has a tag and thus can be traced precisely, or you can use it to allocate, well, anything else. I think we will have to add an API for the tagged case and assume that anything that goes through is requesting an untagged, conservatively-scanned block of memory. Similarly for : you could be allocating a tagged object that happens to not contain pointers, or you could be allocating an untagged array of whatever. A new API is needed there too for pointerless untagged allocations.scm_gc_mallocscm_gc_mallocscm_gc_malloc_pointerless Recall that the mostly-marking collector can be built in a number of different ways: it can support conservative and/or precise roots, it can trace the heap precisely or conservatively, it can be generational or not, and the collector can use multiple threads during pauses or not. Consider a basic configuration with precise roots. You can make tagged pointerless allocations just fine: the trace function for that tag is just trivial. You would like to extend the collector with the ability to make pointerless allocations, for raw data. How to do this?untagged Consider first that when the collector goes to trace an object, it can’t use bits inside the object to discriminate between the tagged and untagged cases. Fortunately though . Of those 8 bits, 3 are used for the mark (five different states, allowing for future concurrent tracing), two for the , one to indicate whether the object is pinned or not, and one to indicate the end of the object, so that we can determine object bounds just by scanning the metadata byte array. That leaves 1 bit, and we can use it to indicate untagged pointerless allocations. Hooray!the main space of the mostly-marking collector has one metadata byte for each 16 bytes of payloadprecise field-logging write barrier However there is a wrinkle: when Whippet decides the it should evacuate an object, it tracks the evacuation state in the object itself; the embedder has to provide an implementation of a , allowing the collector to detect whether an object is forwarded or not, to claim an object for forwarding, to commit a forwarding pointer, and so on. We can’t do that for raw data, because all bit states belong to the object, not the collector or the embedder. So, we have to set the “pinned” bit on the object, indicating that these objects can’t move.little state machine We could in theory manage the forwarding state in the metadata byte, but we don’t have the bits to do that currently; maybe some day. For now, untagged pointerless allocations are pinned. You might also want to support untagged allocations that contain pointers to other GC-managed objects. In this case you would want these untagged allocations to be scanned conservatively. We can do this, but if we do, it will pin all objects. Thing is, conservative stack roots is a kind of a sweet spot in language run-time design. You get to avoid constraining your compiler, you avoid a class of bugs related to rooting, but you can still support compaction of the heap. How is this, you ask? Well, consider that you can move any object for which we can precisely enumerate the incoming references. This is trivially the case for precise roots and precise tracing. For conservative roots, we don’t know whether a given edge is really an object reference or not, so we have to conservatively avoid moving those objects. But once you are done tracing conservative edges, any live object that hasn’t yet been traced is fair game for evacuation, because none of its predecessors have yet been visited. But once you add conservatively-traced objects back into the mix, you don’t know when you are done tracing conservative edges; you could always discover another conservatively-traced object later in the trace, so you have to pin everything. The good news, though, is that we have gained an easier migration path. I can now shove Whippet into Guile and get it running even before I have removed untagged allocations. Once I have done so, I will be able to allow for compaction / evacuation; things only get better from here. Also as a side benefit, the mostly-marking collector’s heap-conservative configurations are now faster, because we have metadata attached to objects which allows tracing to skip known-pointerless objects. This regains an optimization that BDW has long had via its , used in Guile since time out of mind.GC_malloc_atomic With support for untagged allocations, I think I am finally ready to start getting Whippet into Guile itself. Happy hacking, and see you on the other side! inside and outside on intent on data on slop fin
Salutations, populations. Today’s note is more of a work-in-progress than usual; I have been finally starting to look at getting into , and there are some open questions.WhippetGuile I started by taking a look at how Guile uses the ‘s API, to make sure I had all my bases covered for an eventual switch to something that was not BDW. I think I have a good overview now, and have divided the parts of BDW-GC used by Guile into seven categories.Boehm-Demers-Weiser collector Firstly there are the ways in which Guile’s run-time and compiler depend on BDW-GC’s behavior, without actually using BDW-GC’s API. By this I mean principally that we assume that any reference to a GC-managed object from any thread’s stack will keep that object alive. The same goes for references originating in global variables, or static data segments more generally. Additionally, we rely on GC objects not to move: references to GC-managed objects in registers or stacks are valid across a GC boundary, even if those references are outside the GC-traced graph: all objects are pinned. Some of these “uses” are internal to Guile’s implementation itself, and thus amenable to being changed, albeit with some effort. However some escape into the wild via Guile’s API, or, as in this case, as implicit behaviors; these are hard to change or evolve, which is why I am putting my hopes on Whippet’s , which allows for conservative roots.mostly-marking collector Then there are the uses of BDW-GC’s API, not to accomplish a task, but to protect the mutator from the collector: , explicitly enabling or disabling GC, calls to that take BDW-GC’s use of POSIX signals into account, and so on. BDW-GC can stop any thread at any time, between any two instructions; for most users is anodyne, but if ever you use weak references, things start to get really gnarly.GC_call_with_alloc_locksigmask Of course a new collector would have its own constraints, but switching to cooperative instead of pre-emptive safepoints would be a welcome relief from this mess. On the other hand, we will require client code to explicitly mark their threads as inactive during calls in more cases, to ensure that all threads can promptly reach safepoints at all times. Swings and roundabouts? Did you know that the Boehm collector allows for precise tracing? It does! It’s slow and truly gnarly, but when you need precision, precise tracing nice to have. (This is the interface.) Guile uses it to mark Scheme stacks, allowing it to avoid treating unboxed locals as roots. When it loads compiled files, Guile also adds some sliced of the mapped files to the root set. These interfaces will need to change a bit in a switch to Whippet but are ultimately internal, so that’s fine.GC_new_kind What is not fine is that Guile allows C users to hook into precise tracing, notably via . This is not only the wrong interface, not allowing for copying collection, but these functions are just truly gnarly. I don’t know know what to do with them yet; are our external users ready to forgo this interface entirely? We have been working on them over time, but I am not sure.scm_smob_set_mark Weak references, weak maps of various kinds: the implementation of these in terms of BDW’s API is incredibly gnarly and ultimately unsatisfying. We will be able to replace all of these with ephemerons and tables of ephemerons, which are natively supported by Whippet. The same goes with finalizers. The same goes for constructs built on top of finalizers, such as ; we’ll get to reimplement these on top of nice Whippet-supplied primitives. Whippet allows for resuscitation of finalized objects, so all is good here.guardians There is a long list of miscellanea: the interfaces to explicitly trigger GC, to get statistics, to control the number of marker threads, to initialize the GC; these will change, but all uses are internal, making it not a terribly big deal. I should mention one API concern, which is that BDW’s state is all implicit. For example, when you go to allocate, you don’t pass the API a handle which you have obtained for your thread, and which might hold some thread-local freelists; BDW will instead load thread-local variables in its API. That’s not as efficient as it could be and Whippet goes the explicit route, so there is some additional plumbing to do. Finally I should mention the true miscellaneous BDW-GC function: . Guile exposes it via an API, . It was already vestigial and we should just remove it, as it has no sensible semantics or implementation.GC_freescm_gc_free That brings me to what I wanted to write about today, but am going to have to finish tomorrow: the actual allocation routines. BDW-GC provides two, essentially: and . The difference is that “atomic” allocations don’t refer to other GC-managed objects, and as such are well-suited to raw data. Otherwise you can think of atomic allocations as a pure optimization, given that BDW-GC mostly traces conservatively anyway.GC_mallocGC_malloc_atomic From the perspective of a user of BDW-GC looking to switch away, there are two broad categories of allocations, tagged and untagged. Tagged objects have attached metadata bits allowing their type to be inspected by the user later on. This is the happy path! We’ll be able to write a function that takes any object, does a switch on, say, some bits in the first word, dispatching to type-specific tracing code. As long as the object is sufficiently initialized by the time the next safepoint comes around, we’re good, and given cooperative safepoints, the compiler should be able to ensure this invariant.gc_trace_object Then there are untagged allocations. Generally speaking, these are of two kinds: temporary and auxiliary. An example of a temporary allocation would be growable storage used by a C run-time routine, perhaps as an unbounded-sized alternative to . Guile uses these a fair amount, as they compose well with non-local control flow as occurring for example in exception handling.alloca An auxiliary allocation on the other hand might be a data structure only referred to by the internals of a tagged object, but which itself never escapes to Scheme, so you never need to inquire about its type; it’s convenient to have the lifetimes of these values managed by the GC, and when desired to have the GC automatically trace their contents. Some of these should just be folded into the allocations of the tagged objects themselves, to avoid pointer-chasing. Others are harder to change, notably for mutable objects. And the trouble is that for external users of , I fear that we won’t be able to migrate them over, as we don’t know whether they are making tagged mallocs or not.scm_gc_malloc One conventional way to handle untagged allocations is to manage to fit your data into other tagged data structures; V8 does this in many places with instances of FixedArray, for example, and Guile should do more of this. Otherwise, you make new tagged data types. In either case, all auxiliary data should be tagged. I think there may be an alternative, which would be just to support the equivalent of untagged and ; but for that, I am out of time today, so type at y’all tomorrow. Happy hacking!GC_mallocGC_malloc_atomic inventory what is to be done? implicit uses defensive uses precise tracing reachability misc allocation
Hey all, quick post today to mention that I added tracing support to the . If the support library for is available when Whippet is compiled, Whippet embedders can visualize the GC process. Like this!Whippet GC libraryLTTng Click above for a full-scale screenshot of the trace explorer processing the with the on a 2.5x heap. Of course no image will have all the information; the nice thing about trace visualizers like is that you can zoom in to sub-microsecond spans to see exactly what is happening, have nice mouseovers and clicky-clickies. Fun times!Perfetto microbenchmarknboyerparallel copying collector Adding tracepoints to a library is not too hard in the end. You need to , which has a file. You need to . Then you have a that includes the header, to generate the code needed to emit tracepoints.pull in the librarylttng-ustdeclare your tracepoints in one of your header filesminimal C filepkg-config Annoyingly, this header file you write needs to be in one of the directories; it can’t be just in the the source directory, because includes it seven times (!!) using (!!!) and because the LTTng file header that does all the computed including isn’t in your directory, GCC won’t find it. It’s pretty ugly. Ugliest part, I would say. But, grit your teeth, because it’s worth it.-Ilttngcomputed includes Finally you pepper your source with tracepoints, which probably you so that you don’t have to require LTTng, and so you can switch to other tracepoint libraries, and so on.wrap in some macro I wrote up a little . It’s not as easy as , which I think is an error. Another ugly point. Buck up, though, you are so close to graphs!guide for Whippet users about how to actually get tracesperf record By which I mean, so close to having to write a Python script to make graphs! Because LTTng writes its logs in so-called Common Trace Format, which as you might guess is not very common. I have a colleague who swears by it, that for him it is the lowest-overhead system, and indeed in my case it has no measurable overhead when trace data is not being collected, but his group uses custom scripts to convert the CTF data that he collects to... (?!?!?!!).GTKWave In my case I wanted to use Perfetto’s UI, so I found a to convert from CTF to the . But, it uses an old version of Babeltrace that wasn’t available on my system, so I had to write a (!!?!?!?!!), probably the most Python I have written in the last 20 years.scriptJSON-based tracing format that Chrome profiling used to usenew script Yes. God I love blinkenlights. As long as it’s low-maintenance going forward, I am satisfied with the tradeoffs. Even the fact that I had to write a script to process the logs isn’t so bad, because it let me get nice nested events, which most stock tracing tools don’t allow you to do. I fixed a small performance bug because of it – a . A win, and one that never would have shown up on a sampling profiler too. I suspect that as I add more tracepoints, more bugs will be found and fixed.worker thread was spinning waiting for a pool to terminate instead of helping out I think the only thing that would be better is if tracepoints were a part of Linux system ABIs – that there would be header files to emit tracepoint metadata in all binaries, that you wouldn’t have to link to any library, and the actual tracing tools would be intermediated by that ABI in such a way that you wouldn’t depend on those tools at build-time or distribution-time. But until then, I will take what I can get. Happy tracing! on adding tracepoints using the thing is it worth it? fin
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I started writing this early last week but Real Life Stuff happened and now you're getting the first-draft late this week. Warning, unedited thoughts ahead! New Logic for Programmers release! v0.9 is out! This is a big release, with a new cover design, several rewritten chapters, online code samples and much more. See the full release notes at the changelog page, and get the book here! Write the cleverest code you possibly can There are millions of articles online about how programmers should not write "clever" code, and instead write simple, maintainable code that everybody understands. Sometimes the example of "clever" code looks like this (src): # Python p=n=1 exec("p*=n*n;n+=1;"*~-int(input())) print(p%n) This is code-golfing, the sport of writing the most concise code possible. Obviously you shouldn't run this in production for the same reason you shouldn't eat dinner off a Rembrandt. Other times the example looks like this: def is_prime(x): if x == 1: return True return all([x%n != 0 for n in range(2, x)] This is "clever" because it uses a single list comprehension, as opposed to a "simple" for loop. Yes, "list comprehensions are too clever" is something I've read in one of these articles. I've also talked to people who think that datatypes besides lists and hashmaps are too clever to use, that most optimizations are too clever to bother with, and even that functions and classes are too clever and code should be a linear script.1. Clever code is anything using features or domain concepts we don't understand. Something that seems unbearably clever to me might be utterly mundane for you, and vice versa. How do we make something utterly mundane? By using it and working at the boundaries of our skills. Almost everything I'm "good at" comes from banging my head against it more than is healthy. That suggests a really good reason to write clever code: it's an excellent form of purposeful practice. Writing clever code forces us to code outside of our comfort zone, developing our skills as software engineers. Debugging is twice as hard as writing the code in the first place. Therefore, if you write the code as cleverly as possible, you [will get excellent debugging practice at exactly the right level required to push your skills as a software engineer] — Brian Kernighan, probably There are other benefits, too, but first let's kill the elephant in the room:2 Don't commit clever code I am proposing writing clever code as a means of practice. Being at work is a job with coworkers who will not appreciate if your code is too clever. Similarly, don't use too many innovative technologies. Don't put anything in production you are uncomfortable with. We can still responsibly write clever code at work, though: Solve a problem in both a simple and a clever way, and then only commit the simple way. This works well for small scale problems where trying the "clever way" only takes a few minutes. Write our personal tools cleverly. I'm a big believer of the idea that most programmers would benefit from writing more scripts and support code customized to their particular work environment. This is a great place to practice new techniques, languages, etc. If clever code is absolutely the best way to solve a problem, then commit it with extensive documentation explaining how it works and why it's preferable to simpler solutions. Bonus: this potentially helps the whole team upskill. Writing clever code... ...teaches simple solutions Usually, code that's called too clever composes several powerful features together — the "not a single list comprehension or function" people are the exception. Josh Comeau's "don't write clever code" article gives this example of "too clever": const extractDataFromResponse = (response) => { const [Component, props] = response; const resultsEntries = Object.entries({ Component, props }); const assignIfValueTruthy = (o, [k, v]) => (v ? { ...o, [k]: v } : o ); return resultsEntries.reduce(assignIfValueTruthy, {}); } What makes this "clever"? I count eight language features composed together: entries, argument unpacking, implicit objects, splats, ternaries, higher-order functions, and reductions. Would code that used only one or two of these features still be "clever"? I don't think so. These features exist for a reason, and oftentimes they make code simpler than not using them. We can, of course, learn these features one at a time. Writing the clever version (but not committing it) gives us practice with all eight at once and also with how they compose together. That knowledge comes in handy when we want to apply a single one of the ideas. I've recently had to do a bit of pandas for a project. Whenever I have to do a new analysis, I try to write it as a single chain of transformations, and then as a more balanced set of updates. ...helps us master concepts Even if the composite parts of a "clever" solution aren't by themselves useful, it still makes us better at the overall language, and that's inherently valuable. A few years ago I wrote Crimes with Python's Pattern Matching. It involves writing horrible code like this: from abc import ABC class NotIterable(ABC): @classmethod def __subclasshook__(cls, C): return not hasattr(C, "__iter__") def f(x): match x: case NotIterable(): print(f"{x} is not iterable") case _: print(f"{x} is iterable") if __name__ == "__main__": f(10) f("string") f([1, 2, 3]) This composes Python match statements, which are broadly useful, and abstract base classes, which are incredibly niche. But even if I never use ABCs in real production code, it helped me understand Python's match semantics and Method Resolution Order better. ...prepares us for necessity Sometimes the clever way is the only way. Maybe we need something faster than the simplest solution. Maybe we are working with constrained tools or frameworks that demand cleverness. Peter Norvig argued that design patterns compensate for missing language features. I'd argue that cleverness is another means of compensating: if our tools don't have an easy way to do something, we need to find a clever way. You see this a lot in formal methods like TLA+. Need to check a hyperproperty? Cast your state space to a directed graph. Need to compose ten specifications together? Combine refinements with state machines. Most difficult problems have a "clever" solution. The real problem is that clever solutions have a skill floor. If normal use of the tool is at difficult 3 out of 10, then basic clever solutions are at 5 out of 10, and it's hard to jump those two steps in the moment you need the cleverness. But if you've practiced with writing overly clever code, you're used to working at a 7 out of 10 level in short bursts, and then you can "drop down" to 5/10. I don't know if that makes too much sense, but I see it happen a lot in practice. ...builds comradery On a few occasions, after getting a pull request merged, I pulled the reviewer over and said "check out this horrible way of doing the same thing". I find that as long as people know they're not going to be subjected to a clever solution in production, they enjoy seeing it! Next week's newsletter will probably also be late, after that we should be back to a regular schedule for the rest of the summer. Mostly grad students outside of CS who have to write scripts to do research. And in more than one data scientist. I think it's correlated with using Jupyter. ↩ If I don't put this at the beginning, I'll get a bajillion responses like "your team will hate you" ↩