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Another problem with Java is inability to return multiple values. For that one often creates a wrapper object holding the results. JVM can recognize this pattern and stack allocate those wrapper objects, but it does not happen always increasing GC pressure.

The lack of custom value types has ramifications not only for GC, but for cache behavior. Which is why there's serious work on custom value types for Java; it's the major feature planned for Java 10.

Of course, most of the old-gen GC work in G1 is also done in parallel with the application, too.

> Of course, most of the old-gen GC work in G1 is also done in parallel with the application, too.

Did you want to write concurrently? If so that would be wrong because evacuation can't be done concurrently with the application in G1, only initial marking.

I didn't say that all work is done concurrently with the app. How much work needs to be done in the STW phase is application-dependent. It is likely that if the application exhibits a transactional behavior, namely that objects are created in the beginning of a transaction and are all reclaimed at the end, there's very little need compaction required, as entire regions are likely to be completely free.

Another strong point for the JVM is the availability of alternate implementations from several vendors. Is this possible for Go say in the future?

It is certainly possible. There are already two Go implementations, the official one, and a gcc based one. And due to the fact that the whole Go implementation is available under BSD license, allows anyone without any license worries to fork a custom Go implementation.

You forgot GopherJS.

There's also llgo.

Many view this as an overall negative point, particularly for those who are tasked with running complex JVM applications without deep operational knowledge...

This observation has fed into the Go team's design philosophy; they're doing their best to minimize the "knobs" the GC has, because tuning them is inevitably a black art. As far as I know, there's still just one right now, GOGC, documented in the third paragraph of https://golang.org/pkg/runtime/ .

Yes, but HotSpot G1 is meant to be usable with only a single knob too (target pause time). Other knobs do exist, but only for unusual cases where you want to precisely control the GC's operation to work around some bad app/gc interaction, for instance. And Go lacking such knobs is probably not really a feature: it's not like the Java guys set out from the start saying "we will build a complicated and hard to configure GC". It's just that as you work through more and more customer cases, these knobs become valuable for the hard ones.

The point is not that lacking knobs is a feature. The point is that the designers are well aware of the issues and they are explicitly making it a goal that knobs should be unnecessary. (Especially since it has had some knobs off and on in the various versions, as mentioned in the article.)

This is in contrast to something we've probably all done at one point or another, which is just to add a checkbox to avoid having an argument about what the behavior should be. They're committing to having the argument out instead of "just adding knobs".

They also have a track record of, for better or worse, just refusing to add knobs and telling you to either do without or use a different language. If you've got an intensely GC-based workload, I'd consider using something other than Go. (However, bear in mind what may be an intensely GC-based workload in Java may not be in Go, since Go has value types already.)

HotSpot cares a lot about proper defaults too. I don't think that there's a significant philosophy difference between HotSpot and Go there. The philosophy difference is, as you say, that Go is opposed to adding configuration options, while HotSpot does have those options (per customers' requests).

I have seen how G1 suppose to have this one flag but I often get a bad feeling about G1 (without really using it much). It seems it reduces average GC pauses but performs really bad in the really lower (CMS) range. One of thing that looked bad to me is that originally they believed that it can completely ignore the generational hypothesis and then had to brought that back when finding the performance bad. There are also other issues like cross region links that it doesn't handle well. It seems to me that they thought their regional idea was a silver bullet and now tweaking it all over the place. It is a nice GC probably but I don't think its really the GC to end all other GC like Oracle wants it to be.

I get what they're doing but it's a false dichotomy and therefore wrong. The dichotomy being it has to be one, ultra-simple GC or what Java was doing.

https://stas-blogspot.blogspot.com.au/2011/07/most-complete-...

It's well-known after over a decade of research and deployments in GC's that certain styles match certain workloads better. So, multiple ones should be available. This can be a small number that are largely pre-built with sane settings. What's left to tune can likewise be small: pause time, max memory, or whatever. There can also be a default as in current Go that covers 95% of apps well. The result is that specific apps or libraries if they went that far can have GC well-suited to their requirements with about one page of HTML describing what those GC's do and how to choose them.

That's what they should do. It will be easy for them and developers. Nothing like JVM mess. Still avoids one-size-fits-all: longest-running, failed concept in IT. Meanwhile, I can't wait to see someone make a HW version of their GC like I've seen in LISP and RT-Java research. IT would be badass given the current metrics. Allow whole OS to be done memory managed like A2 Bluebottle Oberon without performance penalty.

Can hardware accelerated GC be generalized enough to make it useful? Isn't that what killed previous efforts?

Previous efforts got killed because the off-brand hardware, especially the CPU's, were never as fast and/or cheap as Intel/AMD. They also required new tooling and such most of the time. This happened to LISP machines and apparently Azul's Vega's as they're pushing SW solution these days. So, that's my guess.

Most general I saw was in a Scheme CPU where the designer put the GC in the memory subsystem. The Scheme CPU would just allocate and deallocate memory. The GC tracked what was still in use on its own in concurrent fashion. Like reference counting I think. Eventually, it would delete what wasn't needed. Pretty cool stuff.

I don't see how it can be a negative. The availability of multiple vendors has given us commercial solutions tuned for particular needs.

For example Azul's C4 garbage collector which they claim is pauseless: https://www.azul.com/resources/azul-technology/azul-c4-garba... ; a pauseless GC is great if you want to tackle real-time systems. For real-time systems actually most garbage collected platforms are unsuitable.

But even more problematic is that stop-the-world latency is directly proportional to the size of the heap memory and today's mainstream garbage collectors cannot cope with more than 4 GB of heap memory without introducing serious latency that's measured in seconds. Think about that for a second - with most GC implementations you cannot have a process that can use 20 GB of RAM, which is pretty cheap these days btw. So keeping a lot of data in memory, like databases are doing, is not feasible with a garbage collector.

> For example Azul's C4 garbage collector which they claim is pauseless: https://www.azul.com/resources/azul-technology/azul-c4-garba.... ; a pauseless GC is great if you want to tackle real-time systems. For real-time systems actually most garbage collected platforms are unsuitable.

As far as I can tell Azul's collector claims to be pauseless because they use the new x86 nested page tables (https://en.wikipedia.org/wiki/Second_Level_Address_Translati...) to implement a read barrier (interesting aside: this means it should be possible to implement a read barrier on CPUs without nested page tables by moving the GC into the kernel). Here is an interesting discussion: http://stackoverflow.com/questions/4491260/explanation-of-az...

That still does not mean that C4 is necessarily real-time. You have to take a fundamentally different approach to GC to guarantee real-time bounds (see these papers on the Metronome collector: http://researcher.watson.ibm.com/researcher/files/us-bacon/B... https://www.cs.purdue.edu/homes/hosking/690M/ft_gateway.cfm....) and that comes with a restriction that ties your program's allocation rate to the scheduling of the GC. I am still skeptical about this - it is easy to imagine coming up with an adversarial allocation pattern that breaks time bound guarantees because of some detail of the GC implementation, so both the algorithm and every implementation will need proofs.

> So keeping a lot of data in memory, like databases are doing, is not feasible with a garbage collector.

It is very feasible if you do not make garbage. Either mmap some memory that the GC won't touch or pre-allocate large arrays of primitive types.

You also have Excelsior[0], which provides full Java AOT (ahead-of-time) compilation to native machine code.

[0]: https://www.excelsiorjet.com/

Is the output code faster than HotSpot after its been warmed up?

Eh, HotSpot can handle heaps of hundreds of gigabytes with pause times in the 100msec range. It takes a bit of tuning but can be done with the basic open source code.

What HotSpot are you talking about? I assume you aren't talking about the Serial, or the Parallel GC or about CMS, which are the older generation, but about G1, right?

Well, I have extensive experience with tuning G1. G1 is a good GC, capable of low latency incremental pauses.

The problem is that with a stressed process, at some point G1 still falls back to a full freeze-the-world mark-and-sweep. For 50 GB I've seen the pause last for over 2 minutes !!!

2 minutes is cute. If you stress a CMS setup hard enough that the young generation is completely full, it will allocate directly in the old generation. This of course screws the full gc heuristic totally, up to the point where the GC is started too late and you fully run out of memory. At which point the JVM drops down to a single threaded oldschool serial GC as last line of defense. On a 96GiB heap, that thing can take hours; all stuck 100% on a single cpu with even signal handling suspended. Fun times.

That said, for heaps above 32ish GiB, we still go with our tuned CMS settings and overcommit one or two additional memory modules. It's a lot cheaper than the time it takes trying to tune in G1 on a large heap with a lot of gc pressure.

Got any sources for that? I would be very interested in these tuning parameters and some explanation of what they do! :)

Cassandra works around this by pushing some of that responsibility onto the OS's disk-caching mechanism.

No it won't, I asked and got an answer from Brad Fitzpatrick:

https://www.reddit.com/r/golang/comments/4pmlv9/transaction_...

The link you posted was about switchable GCs in the official Go runtime, which won't be there, but the question was whether there are multiple Go implementations.

Is there any data from production systems available that confirms that is an issue in most/many real world applications (the lack of value types)? From the allocation profiles I have seen in the applications I have seen most allocations in Java programs seem to be from strings, often in logging, or byte array buffers. Value types would no help here but compressed strings would.