Whilst trying to understand how SubmissionPublisher (source code in OpenJDK 10, Javadoc), a new class added to the Java SE in version 9, has been implemented, I stumbled across a few API calls to VarHandle I wasn't previously aware of:
fullFence, acquireFence, releaseFence, loadLoadFence and storeStoreFence.
After doing some research, especially regarding the concept of memory barriers/fences (I have heard of them previously, yes; but never used them, thus was quite unfamiliar with their semantics), I think I have a basic understanding of what they are for. Nonetheless, as my questions might arise from a misconception, I want to ensure that I got it right in the first place:
Memory barriers are reordering constraints regarding reading and writing operations.
Memory barriers can be categorized into two main categories: unidirectional and bidirectional memory barriers, depending on whether they set constraints on either reads or writes or both.
C++ supports a variety of memory barriers, however, these do not match up with those provided by VarHandle. However, some of the memory barriers available in VarHandle provide ordering effects that are compatible to their corresponding C++ memory barriers.
#fullFence is compatible to atomic_thread_fence(memory_order_seq_cst)
#acquireFence is compatible to atomic_thread_fence(memory_order_acquire)
#releaseFence is compatible to atomic_thread_fence(memory_order_release)
#loadLoadFence and #storeStoreFence have no compatible C++ counter part
The word compatible seems to really important here since the semantics clearly differ when it comes to the details. For instance, all C++ barriers are bidirectional, whereas Java's barriers aren't (necessarily).
Most memory barriers also have synchronization effects. Those especially depend upon the used barrier type and previously-executed barrier instructions in other threads. As the full implications a barrier instruction has is hardware-specific, I'll stick with the higher-level (C++) barriers. In C++, for instance, changes made prior to a release barrier instruction are visible to a thread executing an acquire barrier instruction.
Are my assumptions correct? If so, my resulting questions are:
Do the memory barriers available in VarHandle cause any kind of memory synchronization?
Regardless of whether they cause memory synchronization or not, what may reordering constraints be useful for in Java? The Java Memory Model already gives some very strong guarantees regarding ordering when volatile fields, locks or VarHandle operations like #compareAndSet are involved.
In case you're looking for an example: The aforementioned BufferedSubscription, an inner class of SubmissionPublisher (source linked above), established a full fence in line 1079, function growAndAdd. However, it is unclear for me what it is there for.
This is mainly a non-answer, really (initially wanted to make it a comment, but as you can see, it's far too long). It's just that I questioned this myself a lot, did a lot of reading and research and at this point in time I can safely say: this is complicated. I even wrote multiple tests with jcstress to figure out how really they work (while looking at the assembly code generated) and while some of them somehow made sense, the subject in general is by no means easy.
The very first thing you need to understand:
The Java Language Specification (JLS) does not mention barriers, anywhere. This, for java, would be an implementation detail: it really acts in terms of happens before semantics. To be able to proper specify these according to the JMM (Java Memory Model), the JMM would have to change quite a lot.
This is work in progress.
Second, if you really want to scratch the surface here, this is the very first thing to watch. The talk is incredible. My favorite part is when Herb Sutter raises his 5 fingers and says, "This is how many people can really and correctly work with these." That should give you a hint of the complexity involved. Nevertheless, there are some trivial examples that are easy to grasp (like a counter updated by multiple threads that does not care about other memory guarantees, but only cares that it is itself incremented correctly).
Another example is when (in java) you want a volatile flag to control threads to stop/start. You know, the classical:
volatile boolean stop = false; // on thread writes, one thread reads this
If you work with java, you would know that without volatile this code is broken (you can read why double check locking is broken without it for example). But do you also know that for some people that write high performance code this is too much? volatile read/write also guarantees sequential consistency - that has some strong guarantees and some people want a weaker version of this.
A thread safe flag, but not volatile? Yes, exactly: VarHandle::set/getOpaque.
And you would question why someone might need that for example? Not everyone is interested with all the changes that are piggy-backed by a volatile.
Let's see how we will achieve this in java. First of all, such exotic things already existed in the API: AtomicInteger::lazySet. This is unspecified in the Java Memory Model and has no clear definition; still people used it (LMAX, afaik or this for more reading). IMHO, AtomicInteger::lazySet is VarHandle::releaseFence (or VarHandle::storeStoreFence).
Let's try to answer why someone needs these?
JMM has basically two ways to access a field: plain and volatile (which guarantees sequential consistency). All these methods that you mention are there to bring something in-between these two - release/acquire semantics; there are cases, I guess, where people actually need this.
An even more relaxation from release/acquire would be opaque, which I am still trying to fully understand.
Thus bottom line (your understanding is fairly correct, btw): if you plan to use this in java - they have no specification at the moment, do it on you own risk. If you do want to understand them, their C++ equivalent modes are the place to start.
Related
This is a follow up question to
How to demonstrate Java instruction reordering problems?
There are many articles and blogs referring to Java and JVM instruction reordering which may lead to counter-intuitive results in user operations.
When I asked for a demonstration of Java instruction reordering causing unexpected results, several comments were made to the effect that a more general area of concern is memory reordering, and that it would be difficult to demonstrate on an x86 CPU.
Is instruction reordering just a part of a bigger issue of memory reordering, compiler optimizations and memory models? Are these issues really unique to the Java compiler and the JVM? Are they specific to certain CPU types?
Memory reordering is possible without compile-time reordering of operations in source vs. asm. The order of memory operations (loads and stores) to coherent shared cache (i.e. memory) done by a CPU running a thread is also separate from the order it executes those instructions in.
Executing a load is accessing cache (or the store buffer), but executing" a store in a modern CPU is separate from its value actually being visible to other cores (commit from store buffer to L1d cache). Executing a store is really just writing the address and data into the store buffer; commit isn't allowed until after the store has retired, thus is known to be non-speculative, i.e. definitely happening.
Describing memory reordering as "instruction reordering" is misleading. You can get memory reordering even on a CPU that does in-order execution of asm instructions (as long as it has some mechanisms to find memory-level parallelism and let memory operations complete out of order in some ways), even if asm instruction order matches source order. Thus that term wrongly implies that merely having plain load and store instructions in the right order (in asm) would be useful for anything related to memory order; it isn't, at least on non-x86 CPUs. It's also weird because instructions have effects on registers (at least loads, and on some ISAs with post-increment addressing modes, stores can, too).
It's convenient to talk about something like StoreLoad reordering as x = 1 "happening" after a tmp = y load, but the thing to talk about is when the effects happen (for loads) or are visible to other cores (for stores) in relation to other operations by this thread. But when writing Java or C++ source code, it makes little sense to care whether that happened at compile time or run-time, or how that source turned into one or more instructions. Also, Java source doesn't have instructions, it has statements.
Perhaps the term could make sense to describe compile-time reordering between bytecode instructions in a .class vs. JIT compiler-generate native machine code, but if so then it's a mis-use to use it for memory reordering in general, not just compile/JIT-time reordering excluding run-time reordering. It's not super helpful to highlight just compile-time reordering, unless you have signal handlers (like POSIX) or an equivalent that runs asynchronously in the context of an existing thread.
This effect is not unique to Java at all. (Although I hope this weird use of "instruction reordering" terminology is!) It's very much the same as C++ (and I think C# and Rust for example, probably most other languages that want to normally compile efficiently, and require special stuff in the source to specify when you want your memory operations ordered wrt. each other, and promptly visible to other threads). https://preshing.com/20120625/memory-ordering-at-compile-time/
C++ defines even less than Java about access to non-atomic<> variables without synchronization to ensure that there's never a write in parallel with anything else (undefined behaviour1).
And even present in assembly language, where by definition there's no reordering between source and machine code. All SMP CPUs except a few ancient ones like 80386 also do memory-reordering at run-time, so lack of instruction reordering doesn't gain you anything, especially on machines with a "weak" memory model (most modern CPUs other than x86): https://preshing.com/20120930/weak-vs-strong-memory-models/ - x86 is "strongly ordered", but not SC: it's program-order plus a store buffer with store forwarding. So if you want to actually demo the breakage from insufficient ordering in Java on x86, it's either going to be compile-time reordering or lack of sequential consistency via StoreLoad reordering or store-buffer effects. Other unsafe code like the accepted answer on your previous question that might happen to work on x86 will fail on weakly-ordered CPUs like ARM.
(Fun fact: modern x86 CPUs aggressively execute loads out of order, but check to make sure they were "allowed" to do that according to x86's strongly-ordered memory model, i.e. that the cache line they loaded from is still readable, otherwise roll back the CPU state to before that: machine_clears.memory_ordering perf event. So they maintain the illusion of obeying the strong x86 memory-ordering rules. Other ISAs have weaker orders and can just aggressively execute loads out of order without later checks.)
Some CPU memory models even allow different threads to disagree about the order of stores done by two other threads. So the C++ memory model allows that, too, so extra barriers on PowerPC are only needed for sequential consistency (atomic with memory_order_seq_cst, like Java volatile) not acquire/release or weaker orders.
Related:
How does memory reordering help processors and compilers?
How is load->store reordering possible with in-order commit? - memory reordering on in-order CPUs via other effects, like scoreboarding loads with a cache that can do hit-under-miss, and/or out-of-order commit from the store buffer, on weakly-ordered ISAs that allow this. (Also LoadStore reordering on OoO exec CPUs that still retire instructions in order, which is actually more surprising than on in-order CPUs which have special mechanisms to allow memory-level parallelism for loads, that OoO exec could replace.)
Are memory barriers needed because of cpu out of order execution or because of cache consistency problem? (basically a duplicate of this; I didn't say much there that's not here)
Are loads and stores the only instructions that gets reordered? (at runtime)
Does an x86 CPU reorder instructions? (yes)
Can a speculatively executed CPU branch contain opcodes that access RAM? - store execution order isn't even relevant for memory ordering between threads, only commit order from the store buffer to L1d cache. A store buffer is essential to decouple speculative exec (including of store instructions) from anything that's visible to other cores. (And from cache misses on those stores.)
Why is integer assignment on a naturally aligned variable atomic on x86? - true in asm, but not safe in C/C++; you need std::atomic<int> with memory_order_relaxed to get the same asm but in portably-safe way.
Globally Invisible load instructions - where does load data come from: store forwarding is possible, so it's more accurate to say x86's memory model is "program order + a store buffer with store forwarding" than to say "only StoreLoad reordering", if you ever care about this core reloading its own recent stores.
Why memory reordering is not a problem on single core/processor machines? - just like the as-if rule for compilers, out-of-order exec (and other effects) have to preserve the illusion (within one core and thus thread) of instructions fully executing one at a time, in program order, with no overlap of their effects. This is basically the cardinal rule of CPU architecture.
LWN: Who's afraid of a big bad optimizing compiler? - surprising things compilers can do to C code that uses plain (non-volatile / non-_Atomic accesses). This is mostly relevant for the Linux kernel, which rolls its own atomics with inline asm for some things like barriers, but also just C volatile for pure loads / pure stores (which is very different from Java volatile2.)
Footnote 1: C++ UB means not just an unpredictable value loaded, but that the ISO C++ standard has nothing to say about what can/can't happen in the whole program at any time before or after UB is encountered. In practice for memory ordering, the consequences are often predictable (for experts who are used to looking at compiler-generated asm) depending on the target machine and optimization level, e.g. hoisting loads out of loops breaking spin-wait loops that fail to use atomic. But of course you're totally at the mercy of whatever the compiler happens to do when your program contains UB, not at all something you can rely on.
Caches are coherent, despite common misconceptions
However, all real-world systems that Java or C++ run multiple threads across do have coherent caches; seeing stale data indefinitely in a loop is a result of compilers keeping values in registers (which are thread-private), not of CPU caches not being visible to each other. This is what makes C++ volatile work in practice for multithreading (but don't actually do that because C++11 std::atomic made it obsolete).
Effects like never seeing a flag variable change are due to compilers optimizing global variables into registers, not instruction reordering or cpu caching. You could say the compiler is "caching" a value in a register, but you can choose other wording that's less likely to confuse people that don't already understand thread-private registers vs. coherent caches.
Footnote 2: When comparing Java and C++, also note that C++ volatile doesn't guarantee anything about memory ordering, and in fact in ISO C++ it's undefined behaviour for multiple threads to be writing the same object at the same time even with volatile. Use std::memory_order_relaxed if you want inter-thread visibility without ordering wrt. surrounding code.
(Java volatile is like C++ std::atomic<T> with the default std::memory_order_seq_cst, and AFAIK Java provides no way to relax that to do more efficient atomic stores, even though most algorithms only need acquire/release semantics for their pure-loads and pure-stores, which x86 can do for free. Draining the store buffer for sequential consistency costs extra. Not much compared to inter-thread latency, but significant for per-thread throughput, and a big deal if the same thread is doing a bunch of stuff to the same data without contention from other threads.)
Java's multithreaded code is finally mapped to the operating system thread for execution.
Is the operating system thread not thread safe?
Why use the Java memory model to ensure thread safety?Why define the Java memory model?
I hope someone can answer this question, I have looked up a lot of information on the Internet, still do not understand!
The material on the web is all about atomicity, visibility, orderliness, and using the cache consistency model as an example, but I don't think it really answers the question.
thank you very much!
The operating system thread is not thread safe (that statement does not make a lot of sense, but basically, the operating system does not ensure that the intended atomicity of your code is respected).
The problem is that whether two data items are related and therefore need to be synchronized is only really understood by your application.
For example, imagine you are defining a ListOfIntegers class which contains an int array and count of the number of items used in the array. These two data items are related and the way they are updated needs to be co-ordinated in order to ensure that if the object is accessed by two different threads they are always updated in a consistent manner, even if the threads update them simultaneously. Only your application knows how these data items are related. The operating system doesn't know. They are just two pieces of memory as far as it is concerned. That is why you have to implement the thread safety (by using synchronized or carefully arranging how the fields are updated).
The Java "memory model" is pretty close to the hardware model. There is a stack for primitives and objects are allocated on the heap. Synchronization is provided to allow the programmer to lock access to shared data on the heap. In addition, there are rules that the optimizer must follow so that the opimisations don't defeat the synchronisations put in place.
Every programing language that takes concurrency seriously needs a memory model - and here is why.
The memory model is the crux of the concurrency semantics of shared-memory systems. It defines the possible values that a read operation is allowed to return for any given set of write operations performed by a concurrent program, thereby defining the basic semantics of shared variables. In other words, the memory model specifies the set of allowed outputs of a program's read and write operations, and constrains an implementation to produce only (but at least one) such allowed executions. The memory model may and often does allow executions where the outcome cannot be inferred from the order in which read and write operations occur in the program. It is impossible to meaningfully reason about a program or any part of the programming language implementation without an unambiguous memory model. The memory model defines the possible outcomes of a concurrent programs read and write operations. Conversely, the memory model also defines which instruction reorderings may be permitted, either by the processor, the memory system, or the compiler.
This is an excerpt from the paper Memory Models for C/C++ Programmers which I have co-authored. Even though a large part of it is dedicated to the C++ memory model, it also covers more general areas -
starting with the reason why we need a memory model in the first place, explaining the (intuitive) sequential consistent model, and finally the weaker memory models provided by current hardware in x86 and ARM/POWER CPUs.
The Java Memory Model answers the following question: What shall happen when multiple threads modify the same memory location.
And the answer the memory model gives is:
If a program has no data races, then all executions of the program will appear to be sequentially consistent.
There is a great paper by Sarita V. Adve, Hans-J. Boehm about why the Java and C++ Memory Model are designed the way they are: Memory Models: A Case For Rethinking Parallel Languages and Hardware
From the paper:
We have been repeatedly surprised at how difficult it is to formalize the seemingly simple and fundamental property of “what value a read should return in a multithreaded program.”
Memory models, which describe the semantics of shared variables, are crucial to both correct multithreaded applications and the entire underlying implementation stack. It is difficult to teach multithreaded programming without clarity on memory models.
After much prior confusion, major programming languages are converging on a model that guarantees simple interleaving-based semantics for "data-race-free" programs and most hardware vendors have committed to support this model.
The JVM performs a neat trick called lock elision to avoid the cost of locking on objects that are only visible to one thread.
There's a good description of the trick here:
http://www.ibm.com/developerworks/java/library/j-jtp10185/
Does the .Net CLR do something similar? If not then why not?
It's neat, but is it useful? I have a hard time coming up with an example where the compiler can prove that a lock is thread local. Almost all classes don't use locking by default, and when you choose one that locks, then in most cases it will be referenced from some kind of static variable foiling the compiler optimization anyways.
Another thing is that the java vm uses escape analysis in its proof. And AFAIK .net hasn't implemented escape analysis. Other uses of escape analysis such as replacing heap allocations with stack allocations sound much more useful and should be implemented first.
IMO it's currently not worth the coding effort. There are many areas in the .net VM which are not optimized very well and have much bigger impact.
SSE vector instructions and delegate inlining are two examples from which my code would profit much more than from this optimization.
EDIT: As chibacity points out below, this is talking about making locks really cheap rather than completely eliminating them. I don't believe the JIT has the concept of "thread-local objects" although I could be mistaken... and even if it doesn't now, it might in the future of course.
EDIT: Okay, the below explanation is over-simplified, but has at least some basis in reality :) See Joe Duffy's blog post for some rather more detailed information.
I can't remember where I read this - probably "CLR via C#" or "Concurrent Programming on Windows" - but I believe that the CLR allocates sync blocks to objects lazily, only when required. When an object whose monitor has never been contested is locked, the object header is atomically updated with a compare-exchange operation to say "I'm locked". If a different thread then tries to acquire the lock, the CLR will be able to determine that it's already locked, and basically upgrade that lock to a "full" one, allocating it a sync block.
When an object has a "full" lock, locking operations are more expensive than locking and unlocking an otherwise-uncontested object.
If I'm right about this (and it's a pretty hazy memory) it should be feasible to lock and unlock a monitor on different threads cheaply, so long as the locks never overlap (i.e. there's no contention).
I'll see if I can dig up some evidence for this...
In answer to your question: No, the CLR\JIT does not perform "lock elision" optimization i.e. the CLR\JIT does not remove locks from code which is only visible to single threads. This can easily be confirmed with simple single threaded benchmarks on code where lock elision should apply as you would expect in Java.
There are likely to be a number of reasons why it does not do this, but chiefly is the fact that in the .Net framework this is likely to be an uncommonly applied optimization, so is not worth the effort of implementing.
Also in .Net uncontended locks are extremely fast due to the fact they are non-blocking and executed in user space (JVMs appear to have similar optimizations for uncontended locks e.g. IBM). To quote from C# 3.0 In A Nutshell's threading chapter
Locking is fast: you can expect to acquire and release a lock in less
than 100 nanoseconds on a 3 GHz computer if the lock is uncontended"
A couple of example scenarios where lock elision could be applied, and why it's not worth it:
Using locks within a method in your own code that acts purely on locals
There is not really a good reason to use locking in this scenario in the first place, so unlike optimizations such as hoisting loop invariants or method inling, this is a pretty uncommon case and the result of unnecessary use of locks. The runtime shouldn't be concerned with optimizing out uncommon and extreme bad usage.
Using someone else's type that is declared as a local which uses locks internally
Although this sounds more useful, the .Net framework's general design philosophy is to leave the responsibility for locking to clients, so it's rare that types have any internal lock usage. Indeed, the .Net framework is pathologically unsynchronized when it comes to instance methods on types that are not specifically designed and advertized to be concurrent. On the other hand, Java has common types that do include synchronization e.g. StringBuffer and Vector. As the .Net BCL is largely unsynchronized, lock elision is likely to have little effect.
Summary
I think overall, there are fewer cases in .Net where lock elision would kick in, because there are simply not as many places where there would be thread-local locks. Locks are far more likely to be used in places which are visible to multiple threads and therefore should not be elided. Also, uncontended locking is extremely quick.
I had difficulty finding any real-world evidence that lock elision actually provides that much of a performance benefit in Java (for example...), and the latest docs for at least the Oracle JVM state that elision is not always applied for thread local locks, hinting that it is not an always given optimization anyway.
I suspect that lock elision is something that is made possible through the introduction of escape analysis in the JVM, but is not as important for performance as EA's ability to analyze whether reference types can be allocated on the stack.
Use of volatile only makes sense in multiprocessor systems. is this wrong?
i'm trying to learn about thread programming, so if you know any good articles/pdfs ... i like stuff that mentions a bit about how the operating system works as well not just the language's syntax.
No. Volatile can be used in multi-threaded applications. These may or may not run on more than one processor.
volatile is used to ensure all thread see the same copy of the data. If there is only one thread reading/writing to a field, it doesn't need to be volatile. It will work just fine, just be a bit slower.
In Java you don't have much visibility as to the processor architecture, generally you talk in terms of threads and multi-threading.
I suggest Java Concurrency in Practice, it good whatever your level of knowledge, http://www.javaconcurrencyinpractice.com/
The whole point of using Java is you don't need to know most of the details of how threads work etc. If you learn lots of stuff you don't use you are likely to forget it. ;)
Volatile makes sense in a multithreaded programm, running these threads on a single processor or multiple processors does not make a difference. The volatile keyword is used to tell the JVM (and the Java Memory Model it uses) that it should not re-order or cache the value of a variable with this keyword. This guarantees that Threads using a volatile variable will never see a stale version of that variable.
See this link on the Java Memory Model in general for more details. Or this one for information about Volatile.
No. Volatile is used to support concurrency. In certain circumstances, it can be used instead of synchronization.
This article by Brian Goetz really helped me understand volatile. It has several examples of the use of volatile, and it explains under what conditions it can be used.
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After reading "Java concurrent in practice" and "OSGI in practice" I found a specific subject very interesting; Safe Publication. The following is from JCIP:
To publish an object safely, both the reference to the object and the object's state must be made visible to other threads at the same time. A properly constructed object can be safely published by:
Initializing an object reference from a static initializer.
Storing a reference to it into a volatile field.
Storing a reference to it into a final field.
Storing a reference to it into a field that is properly guarded by a (synchronized) lock.
My first question: how many java developers are aware of this (problem)?
How many real world java applications are really following this, AND is this really a real problem? I have a feeling that 99% of the implemented JVMs out there are not that "evil", i.e. a thread is not guaranteed (in fact its practical (almost) "impossible") to see stale data just because the reference is not following the "safe publication idiom" above.
Proportionally, it's probably fair to say that very few programmers sufficiently understand synchronization and concurrency. Who knows how many server applications there are out there right now managing financial transactions, medical records, police records, telephony etc etc that are full of synchronization bugs and essentially work by accident, or very very occasionally fail (never heard of anybody get a phantom phone call added to their telephone bill?) for reasons that are never really looked into or gotten to the bottom of.
Object publication is a particular problem because it's often overlooked, and it's a place where it's quite reasonable for compilers to make optimisations that could result in unexpected behaviour if you don't know about it: in the JIT-compiled code, storing a pointer, then incrementing it and storing the data is a very reasonable thing to do. You might think it's "evil", but at a low level, it's really how you'd expect the JVM spec to be. (Incidentally, I've heard of real-life programs running in JRockit suffering from this problem-- it's not purely theoretical.)
If you know that your application has synchronization bugs but isn't misbehaving in your current JVM on your current hardware, then (a) congratulations; and (b), now is the time to start "walking calmly towards the fire exit", fixing your code and educating your programmers before you need to upgrade too many components.
"is this really a real problem?"
Yes absolutely. Even the most trivial web application has to confront issues surrounding concurrency. Servlets are accessed by multiple threads, for example.
The other issue is that threading and concurrency is very hard to handle correctly. It is almost too hard. That is why we are seeing trends emerge like transactional memory, and languages like Clojure that hopefully make concurrency easier to deal with. But we have a ways to go before these become main stream. Thus we have to do the best with what we have. Reading JCiP is a very good start.
Firstly "safe publication" is not really an idiom (IMO). It comes straight from the language.
There have been cases of problems with unsafe publication, with use of NIO for instance.
Most Java code is very badly written. Threaded code is obviously more difficult than average line-of-business code.
It's not a matter of being "evil". It is a real problem, and will become much more apparent with the rise of multicore architectures in the coming years. I have seen very real production bugs due to improper synchronization. And to answer your other question, I would say that very few programmers are aware of the issue, even among otherwise "good" developers.
I would say very few programmers are away of this issue. When was the last code example you have seen that used the volatile keyword? However, most of the other conditioned mentioned - I just took for granted as best practices.
If a developer completely neglects those conditions, they will quickly encounter multi-threading errors.
My experience (short-terming and consulting in lots of different kinds of environments
Most applications I've seen) agrees with this intuition - I've never seen an entire system clearly architected to manage this problem carefully (well, I've also almost never seen an entire system clearly architected) . I've worked with very, very few developers with a good knowledge of threading issues.
Especially with web apps, you can often get away with this, or at least seem to get away with it. If you have spring-based instantiations managing your object creation and stateless servlets, you can often pretend that there's no such thing as synchronization, and this is sort where lots of applications end up. Eventually someone starts putting some shared state where it doesn't belong and 3 months later someone notices some wierd intermittent errors. This is often "good enough" for many people (as long as you're not writing banking transactions).
How many java developer are aware of this problem? Hard to say, as it depends heavily on where you work.