Incremental GC for Ruby Interpreter
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Ruby Conference 201442 / 65
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Transcript: English(auto-generated)
00:18
Good morning, everyone. In this presentation, I use a small character,
00:23
so, like this. So, if you cannot read this character, so please come in front of the stage. So let's start my presentation. Incremental garbage collection for Ruby interpreter.
00:43
My name is Koichi Sasada from Heroku. I live in Japan, so I come here with 11, maybe 10, 13 hours. At first, I want to show you the,
01:01
I want to say that this year, 2014, is very important year for me because the wedding, the first wedding adversary with her, I had a wedding party
01:21
at this April. And this year is the 10th anniversary of my yard development. So 10 years ago, I started to develop the YETAN ZABAJI machine.
01:40
And the first presentation at the Ruby Confine, 2004. So this is the 10th years, 10 years ago I do a presentation. And especially recently, we improved the garbage character.
02:02
So increasing the throughputs and reduce the pause time. So this kind of improvement will be included to the Ruby 2.2 at this next Christmas.
02:30
Generation garbage collection, I was introduced. I introduced Ruby 2.1 last year.
02:41
So we improved the throughput of the garbage collection dramatically by using the generation garbage collection. But seeing the pause time, it is a problem.
03:04
So generation garbage collection separates the young generation and the old generation. And JC4, young generation, it is in a small pause time. So these bars shows minor GC pause time.
03:26
But several times, there is a long pause time. It's caused by the major GC. Sorry, blue lines are simple mark and slip GC. So it is 2.0 and before.
03:44
And the orange lines are the pause time of the Ruby 2.1. Ruby 2.1 reduce the pause time. But sometime, if we do the major GC,
04:03
there is a long pause time, several times. So it is a problem for response time. So to improve such a long pause time, Ruby 2.2 is using the incremental GC algorithm.
04:27
Incremental GC algorithm is well known algorithm to reduce the pause time. But throughput is not so good. So throughput doesn't change. So generation garbage collection achieves a high performance.
04:48
But there is some long pause time. And incremental GC reduce short pause time, achieve the short pause time. So our goal is mixing the generation garbage collection
05:03
and incremental garbage collection. And we can achieve the high throughput and short pause time. So the result of our trial, we can,
05:24
so orange line is generation GC, only generation GC. But we introduced incremental GC. The gray line is the pause time with incremental GC.
05:43
So there are no long, we can see that there are no long pause time with incremental GC. So this is our achievement. And this is the conclusion of this presentation.
06:10
So we have some more time. So I want to introduce how to implement the incremental GC on Ruby.
06:21
So if you are purely a Ruby programmer, so you can move to another room. If you have any interest to the technical side, so please leave here. Sorry, please sit here. Continue to here.
06:46
Nobody goes. Okay, thank you. So let's introduce myself. My name is Koichi Sasada. I'm a Ruby committer since 2007. And originally I have a developer since 2004.
07:01
And I'm from Japan. And I'm an employee of Heroku. Thank you Heroku. Heroku employs three Ruby core team. It means our crew time should be developer.
07:21
So we three are working in Japan. And our mission is to improve the quality of Ruby interpreter. Quality means there is no bugs, there is no regression to the next version. And small amount of memory consumption and speed up the Ruby interpreter.
07:45
This is our Matsujin. Mats is our boss and he decides everything. And Nobu, so yesterday there is a AskNobu BOX session.
08:01
So Nobu is a well known patch, well known great Ruby interpreter developer. So many patches, so many fixing, by himself. And last one is me.
08:23
My main concern is to improve the performance. Before introduce Ruby, sorry, incremental garbage collection, I want to introduce upcoming Ruby 2.2.
08:40
There is, on syntax, there is no note of changes. There is one change in, I want to say, I want to show you that there is some change for the symbol syntax. So we, from Ruby 2.2, we can write
09:04
this style of hash literal. And this, it means it's a symbol to something, hash literal. So it is not a string to the value literal. So it is confusing. JSON is presented with this syntax as a,
09:25
it will be a string, but it will be a symbol. So it is a trap behavior, I think. And I already misunderstand this behavior. And something, I wrote something,
09:43
but program because of this syntax. So please care about that. And there are some classes and methods changes. But not, maybe not note of changes.
10:00
But we have many internal changes from Ruby 2.2. We, so for example, we remove obsolete functions. So if you maintain some old gem or some old extension, so please check it. And we hide internal definition of data types,
10:23
such as big number and so on. And we have many improvements of internals. For example, we improve the garbage collection performance using, for example, symbol GC.
10:42
Symbol GC is very critical for some symbol rubber programmers. And it improves the performance of generation GC and increment GC. Today I want to show you. And improve performance of keyword parameters
11:00
and keyword arguments with invocation. And using the frozen string literal, if possible, we change the virtual machine to support it. So for example, we wrote such a program.
11:24
So this program shows the symbol number. And generating the one million symbols, generating the one million symbols and checks the symbol number.
11:42
And on Ruby 2.2, there are, so this is before and this is after the symbol generation. So all symbols are not remained. But Ruby 2.2, we can reduce,
12:01
so we can correct dynamically created symbols. So this is what symbol GC does. And Ruby 2.2, we can achieve the very fast keyword parameter with the implication.
12:21
So making the, define the key method using the keyword parameters. And it calls this method 10 million times with keywords. So Ruby 2.2, before this optimization, we need 70 seconds to do that.
12:43
But after optimization, we can, we only consume one second. So it means 15 times faster. So please use keyword parameters. We have no homework program on that.
13:03
Okay. So talking about the garbage collector. This is the ancient technology of the garbage collector.
13:25
So Ruby has several history about garbage collector. At first, maths used this simple conservative mark and sweep garbage collector to implement the GC.
13:41
It is very simple algorithm and easy to implement C extensions. So it is great behavior. But this policy makes difficult to improve the performance of C Ruby interpreter. And Ruby 1.9.3, we introduced lazy sweep
14:03
and Ruby 2.0 into some bit more marking and to improve, to make copyright friendly. And Ruby 2.1, last year I, I showed about this general garbage collection. And Ruby 2.0,
14:23
so this is current status of garbage collector. So we have, now we have generation of garbage collection. So to introduce how to make an incremental GC, I need to show you how to work such garbage collectors.
14:46
So simple marking safe garbage collector is very easy to understand. So there is root sets, root objects and mark reachable objects from root objects. So root objects, so this is one of the root object
15:05
and mark it and traverse another object. So this object can mark traverse them. And after traversal, we can understand
15:20
their not traversal object, traversed object use needed. So we can correct the such un-traversed objects. So it is very easy to understand. And generation garbage collection is
15:45
made by, made with this hypothesis. So most of, so most objects die young. It means that there is many, many temporary objects like string or array or something. So there are not many long-lived objects.
16:06
So we can concentrate to reclaim only for young objects. So printing young object generation to and old object, old generation and create object as young object generation
16:23
and promote old generation after surviving GCs. Usually, we can GC only on young space. We call it minor GC.
16:42
And if there are no memory, then correct everything. So we call it major GC or full GC. So this approach improves the total throughput. So this is a figure of the generation GC.
17:08
At first, we traverse like a simple mark-and-zip algorithm and traverse and check it old, make it old.
17:23
And second, we make assumption. Old objects only refer to the old objects. So if we reach to the old objects, so we can skip the traversal more.
17:50
So it will improve the performance. We don't need to traverse old objects.
18:01
But there is a problem because Ruby program can differ from old object to the new objects. So Ruby program can make such a relationship from the old object to the new objects.
18:21
And this type, so ignore the traversing from old objects. This new object will not be traversed. So it will be a critical bug. So detecting such old to new objects,
18:45
then remember this old object. And traverse from remember set to this new, and traverse this new object. So there is no problem with this technique.
19:11
I thought, I think that simply, so if we detect the old object to the new object relationship,
19:21
and we need to use the right-value technique to detect such a relationship. So old object to the new object. So it will be a right to the old object. So we detect with the right-value technique
19:42
such a different creation. But Ruby doesn't have, Ruby 2.0 and before implementation does not have right values.
20:00
So we need to introduce the right values, but it is very difficult thing, especially for the compatibility. If we need to decide to require the right values, then we need to rewrite the implementation of interpreter core and C extensions.
20:24
So if we have infinite code, time and many money, I can, we can rewrite interpreter everything with many efforts, but we don't have such resources.
20:43
And we need to, and also we cannot touch a third-party C extensions. So if we have, we can see the source code on GitHub or something, we can send a patch,
21:00
but some third-party extensions is not opened, it's not published, so we cannot touch it. So it will be a big issue about compatibility. So this is why we cannot use
21:21
the generation garbage collection before Ruby 2.0, oh sorry, before Ruby 2.1. And the origin GC using the right-body unprotect object. So this idea, this idea enabled to use generation garbage collection without any breaking compatibility
21:43
before Ruby 2.0 and before. The key idea is to split object into two types, right-body unprotected object and right-body unprotected object, and decide this type as the creation type. For example, string object can be right-body,
22:01
we can easily to introduce right-body to the strings, so if there is a string creation, we can check it, right-body unprotected object. And for example, block object, if you make a block object, block object is very difficult to introduce the right-body,
22:21
and now we cannot introduce the right-body for such a block object, so we checked this block object is right-body unprotected object. So we separate right-body protected object and right-body unprotected object.
22:46
And trade with, trade correctly with right-body protected object, right-body unprotected object, we can, we find that we can make a general garbage collection.
23:04
We find that we can make a general garbage collection without any compatibility breaking with this rule. For example,
23:22
usually traversing the new object, then this object will be an old object, but if traversing the right-body unproducted object, then we cannot promote, we do not promote this right-body unproducted object
23:42
to the old object. But instead of promoting this object, we remember this object. And at the second garbage collection, minor garbage collection, we choose,
24:00
we use this unproducted object as a root object. And we can traverse correctly. So technically details, today I skip technical details. So please,
24:22
if you have any interest about details, then please ask me after that. This is a post-time of consuming time of each GC. So blue line is normal mark-and-slip marking time.
24:43
And this gray line is marking time with minor GC. So as you can see, so huge dramatically reduce such a marking time.
25:02
Sleeping time is not changed. The total amount of marking time is changed, is reduced. So huge change. But there is no change about sleeping time.
25:21
This is a microbenchmarking result. This is a last year's presentation. Not current achievement.
25:43
And so with application, with a big application, we can see the reduce of the total time.
26:02
So the total execution time can be reduced. I have several other data to write my paper. So if you have any interest, please ask me after that. algorithm GC,
26:21
generation GC, this shows the timing chart of generation GC. normal mark-and-slip with lazy-slip, then consumes a long marking time. And short sweep and run Ruby program,
26:42
and sweep and run Ruby program. With generation garbage collection, we can show the marking time like that. So we only need a short marking time and short sweep time, part of sweep time,
27:02
and run Ruby program. And do sweep, learn Ruby program, and so on. But the major GC, major GC consumes a long pause time at the marking time. So this is why we try to, we need to try to
27:23
implement the incremental GC. So algorithm GC achieves a high throughput and minor GC stop only short time, short pause time. But major GC still stops long pause time. So we decide to introduce incremental GC to reduce major GC pause time.
27:45
So only for major GC, not for minor GC. So this is today's topic. How to implement restricted, incremental garbage collection algorithms.
28:05
Incremental GC is a well-known GC algorithm to reduce the pause time. So it's simply to do GC steps incrementally. So interweaving with Ruby execution,
28:23
we say Ruby execution as a mute data and GC process. So marking some parts and learn Ruby program and continue marking phase and do the Ruby program and so on.
28:42
And lazy sweep, we already implemented lazy sweep. So lazy sweep is incremental GC, part of incremental GC for sweeping phase. So we do a small, so the goal is to make such a interweaving GC process
29:07
and a mute data process. To explain the incremental garbage collection, we want to introduce tricoloring garbage collection algorithm, terminology.
29:24
So define three colors objects. White is, white object is untraversal object and gray object is, gray objects are marking objects. Now we have, the gray object can point white objects.
29:43
And black objects are marked objects. So white, gray, black. And the incremental GC algorithm, we also say at first we need to color all objects as white objects.
30:03
This presentation, I use this point as animation. It is very tough thing with PowerPoint.
30:22
And gray root objects, gray root objects. And choose gray object. So there is only one gray object, so choose this gray object. And gray, white object as gray,
30:43
gray reachable object from this chosen gray object. And after that, there is no white object reachable from this gray object. So we can color, we can block this gray object to the object.
31:02
And repeating this process, and go back to Ruby program, go back to Ruby program, and continue Ruby program, and after that, back to this GC process. So this step three, this step three can be incrementally,
31:26
can do incrementally. And so, after that, there is no gray object. There is no gray object. So we can finish the GC marking phase.
31:42
And sweep white objects as unmarked objects. So we can correct such white objects. So there is a similar problem as a generational GC.
32:00
So stop the garbage collection marking phase, and run Ruby program. Ruby program can make a difference from the black object, this black object, to this white object. So mutator can add the difference from the black object to white object. So it will become a marking miss
32:22
because we do not traverse from black objects. So we need to remember this black object, or gray this object as this object, or black to gray.
32:41
And we can traverse this white object correctly. So this is what the incremental GC do, incremental GC does. And as I introduced, there is a right-value approach protecting the object, and right-value unprotected object.
33:01
So we cannot make this algorithm without consider about the right-value unprotected object. So we decide to use this technique. So introducing the new rule. Scan all black object, all the black, right-value unprotected object at the end of incremental GC at once.
33:24
At once means stop the world's GC. So right-value protected object can point white object. So scan from all black and white right-value unprotected object at once. So this is a modified one.
33:41
Please consider that there is a black object and a black right-value unprotected object, right-value unprotected object. And there is a state we need to consider
34:02
about creating the difference from the black right-value unprotected object to the white object. But we cannot detect such a difference because there is no right-value for this object.
34:24
So this time there is no gray object. So finish the marking phase. And after that, scan all black
34:40
light-value unprotected object. So there is two such objects. So we need to think it is a root object. And try again the scanning. And we can traverse all white objects,
35:02
all reachable white objects at last. And sweep the untraversed objects. So this algorithm has a problem
35:21
because the pause time is, so this approach can increase pause times relative to the number of right-value unprotected objects.
35:42
So if there is many, many right-value unprotected objects then the pause time will be very long time. So this is why we named this algorithm as restricted. Not a complete incremental GC.
36:01
But this pause time is similar or shorter than the minor GC's pause time. So I think if you are satisfied by a minor GC pause time so it will work for you. If the minor GC pause time is not satisfying you
36:22
so this Ruby 2.2 is not satisfying, is not enough. So there is some implementation details. I may rename the function, the GC function like that.
36:44
And making the right-value protected objects always one bit. And introduce three more bits to represent these state changes.
37:00
And these bits are managed by the bitmap techniques. So bitmap techniques is easy to manage remember set and fast traversing and easy to get a set of, for example, the marked right-value unprotected object. So it means the block right-value unprotected object.
37:22
We need to scan at last of the integrated GC but it is easy to do with bitmap marking, sorry, bitmap technique. Thank you for Aaron. So I use a benchmark program written by Aaron Patterson
37:42
and try to check the incremental GC performance. So this figure is the same as I show at first of this presentation.
38:02
So we can see the orange line is long pause time because of the major GC for general GC. But there are no such a long pause time
38:20
for incremental GC. These lines are plot of the, 2,500 plots of the GC pause time at the measure GC.
38:42
So this first line is the pause time of the measure GC but with incremental GC we can see the only a small amount of pause time. And do the lazy sweep. Lazy sweep only consumes only few minutes.
39:04
And this small peak is minor GC marking time. And so maximum pause time we can reduce. So generation GC we need to,
39:22
this time, but only this time incremental GC needs.
39:40
So we need to say one more thing. So incremental GC does not solve everything. So incremental GC does not guarantee improving your application's response time. So if your application,
40:02
incremental GC does not reduce the total time so that's the big task. So for example the web application one request needs some several times measure GC then so the total response time is not changed. So please check the GC count with these methods
40:25
for each request if you need to consider about the response time. So today I show you the Ruby 2.2 has a very fancy
40:43
incremental garbage collection. And I talk about how to implement such a implemented GC for Ruby interpreter. Thank you very much.