So I am reading this book titled Java Concurrency in Practice and I am stuck on this one explanation which I cannot seem to comprehend without an example. This is the quote:
When thread A writes to a volatile
variable and subsequently thread B
reads that same variable, the values
of all variables that were visible to
A prior to writing to the volatile
variable become visible to B after
reading the volatile variable.
Can someone give me a counterexample of why "the values of ALL variables that were visible to A prior to writing to the volatile variable become visible to B AFTER reading the volatile variable"?
I am confused why all other non-volatile variables do not become visible to B before reading the volatile variable?
Declaring a volatile Java variable means:
The value of this variable will never be cached thread-locally: all reads and writes will go straight to "main memory".
Access to the variable acts as though it is enclosed in a synchronized block, synchronized on itself.
Just for your reference, When is volatile needed ?
When multiple threads using the same
variable, each thread will have its
own copy of the local cache for that
variable. So, when it's updating the
value, it is actually updated in the
local cache not in the main variable
memory. The other thread which is
using the same variable doesn't know
anything about the values changed by
the another thread. To avoid this
problem, if you declare a variable as
volatile, then it will not be stored
in the local cache. Whenever thread
are updating the values, it is updated
to the main memory. So, other threads
can access the updated value.
From JLS §17.4.7 Well-Formed Executions
We only consider well-formed
executions. An execution E = < P, A,
po, so, W, V, sw, hb > is well formed
if the following conditions are true:
Each read sees a write to the same
variable in the execution. All reads
and writes of volatile variables are
volatile actions. For all reads r in
A, we have W(r) in A and W(r).v = r.v.
The variable r.v is volatile if and
only if r is a volatile read, and the
variable w.v is volatile if and only
if w is a volatile write.
Happens-before order is a partial
order. Happens-before order is given
by the transitive closure of
synchronizes-with edges and program
order. It must be a valid partial
order: reflexive, transitive and
antisymmetric.
The execution obeys
intra-thread consistency. For each
thread t, the actions performed by t
in A are the same as would be
generated by that thread in
program-order in isolation, with each
write wwriting the value V(w), given
that each read r sees the value
V(W(r)). Values seen by each read are
determined by the memory model. The
program order given must reflect the
program order in which the actions
would be performed according to the
intra-thread semantics of P.
The execution is happens-before consistent
(§17.4.6).
The execution obeys
synchronization-order consistency. For
all volatile reads r in A, it is not
the case that either so(r, W(r)) or
that there exists a write win A such
that w.v = r.v and so(W(r), w) and
so(w, r).
Useful Link : What do we really know about non-blocking concurrency in Java?
Thread B may have a CPU-local cache of those variables. A read of a volatile variable ensures that any intermediate cache flush from a previous write to the volatile is observed.
For an example, read the following link, which concludes with "Fixing Double-Checked Locking using Volatile":
http://www.cs.umd.edu/~pugh/java/memoryModel/DoubleCheckedLocking.html
If a variable is non-volatile, then the compiler and the CPU, may re-order instructions freely as they see fit, in order to optimize for performance.
If the variable is now declared volatile, then the compiler no longer attempts to optimize accesses (reads and writes) to that variable. It may however continue to optimize access for other variables.
At runtime, when a volatile variable is accessed, the JVM generates appropriate memory barrier instructions to the CPU. The memory barrier serves the same purpose - the CPU is also prevent from re-ordering instructions.
When a volatile variable is written to (by thread A), all writes to any other variable are completed (or will atleast appear to be) and made visible to A before the write to the volatile variable; this is often due to a memory-write barrier instruction. Likewise, any reads on other variables, will be completed (or will appear to be) before the
read (by thread B); this is often due to a memory-read barrier instruction. This ordering of instructions that is enforced by the barrier(s), will mean that all writes visible to A, will be visible B. This however, does not mean that any re-ordering of instructions has not happened (the compiler may have performed re-ordering for other instructions); it simply means that if any writes visible to A have occurred, it would be visible to B. In simpler terms, it means that strict-program order is not maintained.
I will point to this writeup on Memory Barriers and JVM Concurrency, if you want to understand how the JVM issues memory barrier instructions, in finer detail.
Related questions
What is a memory fence?
What are some tricks that a processor does to optimize code?
Threads are allowed to cache variable values that other threads may have since updated since they read them. The volatile keyword forces all threads to not cache values.
This is simply an additional bonus the memory model gives you, if you work with volatile variables.
Normally (i.e. in the absence of volatile variables and synchronization), the VM can make variables from one thread visible to other threads in any order it wants, or not at all. E.g. the reading thread could read some mixture of earlier versions of another threads variable assignments. This is caused by the threads being maybe run on different CPUs with their own caches, which are only sometimes copied to the "main memory", and additionally by code reordering for optimization purposes.
If you used a volatile variable, as soon as thread B read some value X from it, the VM makes sure that anything which thread A has written before it wrote X is also visible to B. (And also everything which A got guaranteed as visible, transitively).
Similar guarantees are given for synchronized blocks and other types of locks.
Related
I am trying to understand volatile keyword from the book Java Concurrency in Practice. I compares synchronized keyword with volatile variables in three aspects: atomic-ness, volatility and reordering. I have some doubts about the same. I have discussed them one by one below:
1) Visibility: `synchronized` vs `volatile`
Book says following with respect to visibility of synchronized:
Everything thread A did in or prior to a synchronized block is visible to B when it executes a synchronized block guarded by the same lock.
It says following with respect to visibility of volatile variables:
Volatile variables are not cached in registers or in caches where they are hidden from other processors, so a read of a volatile variable always returns the most recent write by any thread.
The visibility effects of volatile variables extend beyond the value of the
volatile variable itself. When thread A writes to a volatile variable and subsequently thread B reads that same variable, the values of all variables that were visible to A prior to writing to the volatile variable become visible to B after reading the volatile variable. So from a memory visibility perspective, writing a volatile variable is like exiting a synchronized block and reading a volatile variable is like entering a synchronized block.
Q1. I feel second paragraph above (of volatile) corresponds to what book said about synchronized. But is there synchronized-equivalent to volatile's first paragraph? In other words, does using synchronized ensures any / some variables not getting cached in processor caches and registers?
Note that book also says following about visibility for synchronized:
Locking is not just about mutual exclusion; it is also about memory visibility.
2) Reordering: `synchornized` vs `volatile`
Book says following about volatile in the context of reordering:
When a field is declared volatile, the compiler and runtime are put on notice that this variable is shared and that operations on it should not be reordered with other memory operations.
Q2. Book does not say anything about reordering in the context of synchronized. Can someone explain what can be said of reordering in the context of synchronized?
3) Atomicity
Book says following about atomicity of synchronized and volatile.
the semantics of volatile are not strong enough to make the increment operation (count++) atomic, unless you can guarantee that the variable is written only from a single thread.
Locking can guarantee both visibility and atomicity; volatile variables can
only guarantee visibility.
Q3. I guess this means two threads can see volatile int a together, both will increment it and then save it. But only one last read will have effect, thus making whole "read-increment-save" non atomic. Am I correct with this interpretation on non-atomic-ness of volatile?
Q4. Does all locking-equivalent are comparable and have same visibility, ordering and atomicity property: synchronized blocks, atomic variables, locks?
PS: This question is related to and completely revamped version of this question I asked some days back. Since its full revamp, I havent deleted the older one. I wrote this question in more focused and structured way. Will delete older once I get answer to this one.
The key difference between 'synchronized' and 'volatile', is that 'synchronized' can make threads pause, whereas volatile can't.
'caches and registers' isn't a thing. The book says that because in practice that's usually how things are implemented, and it makes it easier (or perhaps not, given these questions) to understand the how & why of the JMM (java memory model).
The JMM doesn't name them, however. All it says is that the VM is free to give each thread its own local copy of any variable, or not, to be synchronized at some arbitrary time with some or all other threads, or not... unless there is a happens-before relationship anywhere, in which case the VM must ensure that at the point of execution between the two threads where a happens before relationship has been established, they observe all variables in the same state.
In practice that would presumably mean to flush caches. Or not; it might mean the other thread overwrites its local copy.
The VM is free to implement this stuff however it wants, and differently on every architecture out there. As long as the VM sticks to the guaranteed that the JMM makes, it's a good implementation, and as a consequence, your software must work given solely those guarantees and no other assumptions; because what works on your machine might not work on another if you rely on assumptions that aren't guaranteed by the JMM.
Reordering
Reordering is also not in the VM spec, at all. What IS in the VM spec are the following two concepts:
Within the confines of a single thread, all you can observe from inside it is consistent with an ordered view. That is, if you write 'x = 5; y = 10;' it is not possible to observe, from within the same thread, y being 10 but x being its old value. Regardless of synchronized or volatile. So, anytime it can reorder things without that being observable, then the VM is free to. Will it? Up to the VM. Some do, some don't.
When observing effects caused by other threads, and you have not established a happens-before relationship, you may see some, all, or none of these effects, in any order. Really, anything can happen here. In practice, then: Do NOT attempt to observe effects caused by other threads without establishing a happens-before, because the results are arbitrary and untestable.
Happens-before relationships are established by all sorts of things; synchronized blocks obviously do it (if your thread is frozen trying to acquire a lock, and it then runs, any synchronized blocks on that object that finished 'happened before', and anything they did you can now observe, with the guarantee that what you observe is consistent with those things having run in order, and where all data they wrote you can see (as in, you won't get an older 'cache' or whatnot). Volatile accesses do as well.
Atomicity
Yes, your interpretation of why x++ is not atomic even if x is volatile, is correct.
I'm not sure what your Q4 is trying to ask.
In general, if you want to atomically increment an integer, or do any of many other concurrent-esque operations, look at the java.util.concurrent package. These contain efficient and useful implementations of various concepts. AtomicInteger, for example, can be used to atomically increment something, in a way that is visible from other threads, while still being quite efficient (for example, if your CPU supports Compare-And-Set (CAS) operations, Atomicinteger will use it; not something you can do from general java without resorting to Unsafe).
Just to complement rzwitserloot excellent answer:
A1. You can think of it like so: synchronized guarantees that all cashed changes will become visible to other threads that enter a synchronized block (flushed from the cache) once the first thread exits the synchronized block and before the other enters.
A2. Operations executed by a thread T1 within a synchronized block appear to some other thread T2 as not reordered if and only if T2 synchronizes on the same guard.
A3. I'm not sure what you understand by that. It may happen that when incrementing both threads will first perform a read of the variable a which will yield some value v, then both threads will locally increase their local copy of the value v producing v' = v + 1, then both threads will write v' to a. Thus finally the value of a could be v + 1 instead of v + 2.
A4. Basically yes, although in a synchronized block you can perform atomically many operations, while atomic variables allow you to only do a certain single operation like an atomic increment. Moreover, the difference is that when using the synchronized block incorrectly, i.e. by reading variables outside of a synchronized block which are modified by another thread within a synchronized block, you can observe them not-atomically and reordered. Something which is impossible with atomic variables. Locking is exactly the same as synchronized.
Q1. I feel second paragraph above (of volatile) corresponds to what book said about synchronized.
Sure. volatile access can be regarded as synchronization lite.
But is there
synchronized-equivalent to volatile's first paragraph? In other words,
does using synchronized ensures any / some variables not getting
cached in processor caches and registers?
The book has confused you by mixing levels. volatile access has nothing directly to do with processor caches or registers, and in fact the book is surely incorrect about the caches. Volatility and synchronization are about the inter-thread visibility of certain actions, especially of writes to shared variables. How the semantics are implemented is largely a separate concern.
In any case, no, synchronization does not put any constraints on storage of variables. Everything to do with synchronized semantics happens at the boundaries of synchronized regions. This is why all accesses to a given variable from a set of concurrently running threads must be synchronized on the same object in order for a program to be properly synchronized with respect to that variable.
Book says following about volatile in the context of reordering:
When a field is declared volatile, the compiler and runtime are put on notice that this variable is shared and that operations on it
should not be reordered with other memory operations.
Q2. Book does not say anything about reordering in the context of synchronized. Can someone explain what can be said of reordering in
the context of synchronized?
But that already does say something (not everything) about synchronized access. You need to understand that a "memory operation" in this sense is a read or write of a shared variable, or acquiring or releasing any object's monitor. Entry to a synchronized region involves acquiring a monitor, so already the book says, correctly, that volatile accesses will not be reordered across the boundaries of a synchronized region.
More generally, reads of shared variables will not be reordered relative to the beginning of a synchronized region, and writes will not be reordered relative to the end of one.
Q3. I guess this means two threads can see volatile int a together, both will increment it and then save it. But only one last
read will have effect, thus making whole "read-increment-save" non
atomic. Am I correct with this interpretation on non-atomic-ness of
volatile?
Yes. The autoincrement operator performs both a read and a write of the variable to which it is applied. If that variable is volatile then volatile semantics apply to those individually, so other operations on the same variable can happen between if there is no other protection.
Q4. Does all locking-equivalent are comparable and have same visibility, ordering and atomicity property: synchronized blocks,
atomic variables, locks?
Huh? This sub-question is much too broad. You're reading a whole book about it. Generally speaking, though, no these mechanisms have some characteristics in common and some that differ. All have effects on on the visibility of memory operations and their ordering, but they are not identical. "Atomicity" is a function of the other two.
I am wondering at the difference between declaring a variable as volatile and always accessing the variable in a synchronized(this) block in Java?
According to this article http://www.javamex.com/tutorials/synchronization_volatile.shtml there is a lot to be said and there are many differences but also some similarities.
I am particularly interested in this piece of info:
...
access to a volatile variable never has the potential to block: we're only ever doing a simple read or write, so unlike a synchronized block we will never hold on to any lock;
because accessing a volatile variable never holds a lock, it is not suitable for cases where we want to read-update-write as an atomic operation (unless we're prepared to "miss an update");
What do they mean by read-update-write? Isn't a write also an update or do they simply mean that the update is a write that depends on the read?
Most of all, when is it more suitable to declare variables volatile rather than access them through a synchronized block? Is it a good idea to use volatile for variables that depend on input? For instance, there is a variable called render that is read through the rendering loop and set by a keypress event?
It's important to understand that there are two aspects to thread safety.
execution control, and
memory visibility
The first has to do with controlling when code executes (including the order in which instructions are executed) and whether it can execute concurrently, and the second to do with when the effects in memory of what has been done are visible to other threads. Because each CPU has several levels of cache between it and main memory, threads running on different CPUs or cores can see "memory" differently at any given moment in time because threads are permitted to obtain and work on private copies of main memory.
Using synchronized prevents any other thread from obtaining the monitor (or lock) for the same object, thereby preventing all code blocks protected by synchronization on the same object from executing concurrently. Synchronization also creates a "happens-before" memory barrier, causing a memory visibility constraint such that anything done up to the point some thread releases a lock appears to another thread subsequently acquiring the same lock to have happened before it acquired the lock. In practical terms, on current hardware, this typically causes flushing of the CPU caches when a monitor is acquired and writes to main memory when it is released, both of which are (relatively) expensive.
Using volatile, on the other hand, forces all accesses (read or write) to the volatile variable to occur to main memory, effectively keeping the volatile variable out of CPU caches. This can be useful for some actions where it is simply required that visibility of the variable be correct and order of accesses is not important. Using volatile also changes treatment of long and double to require accesses to them to be atomic; on some (older) hardware this might require locks, though not on modern 64 bit hardware. Under the new (JSR-133) memory model for Java 5+, the semantics of volatile have been strengthened to be almost as strong as synchronized with respect to memory visibility and instruction ordering (see http://www.cs.umd.edu/users/pugh/java/memoryModel/jsr-133-faq.html#volatile). For the purposes of visibility, each access to a volatile field acts like half a synchronization.
Under the new memory model, it is still true that volatile variables cannot be reordered with each other. The difference is that it is now no longer so easy to reorder normal field accesses around them. Writing to a volatile field has the same memory effect as a monitor release, and reading from a volatile field has the same memory effect as a monitor acquire. In effect, because the new memory model places stricter constraints on reordering of volatile field accesses with other field accesses, volatile or not, anything that was visible to thread A when it writes to volatile field f becomes visible to thread B when it reads f.
-- JSR 133 (Java Memory Model) FAQ
So, now both forms of memory barrier (under the current JMM) cause an instruction re-ordering barrier which prevents the compiler or run-time from re-ordering instructions across the barrier. In the old JMM, volatile did not prevent re-ordering. This can be important, because apart from memory barriers the only limitation imposed is that, for any particular thread, the net effect of the code is the same as it would be if the instructions were executed in precisely the order in which they appear in the source.
One use of volatile is for a shared but immutable object is recreated on the fly, with many other threads taking a reference to the object at a particular point in their execution cycle. One needs the other threads to begin using the recreated object once it is published, but does not need the additional overhead of full synchronization and it's attendant contention and cache flushing.
// Declaration
public class SharedLocation {
static public volatile SomeObject someObject=new SomeObject(); // default object
}
// Publishing code
SharedLocation.someObject=new SomeObject(...); // new object is published
// Using code
// Note: do not simply use SharedLocation.someObject.xxx(), since although
// someObject will be internally consistent for xxx(), a subsequent
// call to yyy() might be inconsistent with xxx() if the object was
// replaced in between calls.
private String getError() {
SomeObject myCopy=SharedLocation.someObject; // gets current copy
...
int cod=myCopy.getErrorCode();
String txt=myCopy.getErrorText();
return (cod+" - "+txt);
}
// And so on, with myCopy always in a consistent state within and across calls
// Eventually we will return to the code that gets the current SomeObject.
Speaking to your read-update-write question, specifically. Consider the following unsafe code:
public void updateCounter() {
if(counter==1000) { counter=0; }
else { counter++; }
}
Now, with the updateCounter() method unsynchronized, two threads may enter it at the same time. Among the many permutations of what could happen, one is that thread-1 does the test for counter==1000 and finds it true and is then suspended. Then thread-2 does the same test and also sees it true and is suspended. Then thread-1 resumes and sets counter to 0. Then thread-2 resumes and again sets counter to 0 because it missed the update from thread-1. This can also happen even if thread switching does not occur as I have described, but simply because two different cached copies of counter were present in two different CPU cores and the threads each ran on a separate core. For that matter, one thread could have counter at one value and the other could have counter at some entirely different value just because of caching.
What's important in this example is that the variable counter was read from main memory into cache, updated in cache and only written back to main memory at some indeterminate point later when a memory barrier occurred or when the cache memory was needed for something else. Making the counter volatile is insufficient for thread-safety of this code, because the test for the maximum and the assignments are discrete operations, including the increment which is a set of non-atomic read+increment+write machine instructions, something like:
MOV EAX,counter
INC EAX
MOV counter,EAX
Volatile variables are useful only when all operations performed on them are "atomic", such as my example where a reference to a fully formed object is only read or written (and, indeed, typically it's only written from a single point). Another example would be a volatile array reference backing a copy-on-write list, provided the array was only read by first taking a local copy of the reference to it.
volatile is a field modifier, while synchronized modifies code blocks and methods. So we can specify three variations of a simple accessor using those two keywords:
int i1;
int geti1() {return i1;}
volatile int i2;
int geti2() {return i2;}
int i3;
synchronized int geti3() {return i3;}
geti1() accesses the value currently stored in i1 in the current thread.
Threads can have local copies of variables, and the data does not have to be the same as the data held in other threads.In particular, another thread may have updated i1 in it's thread, but the value in the current thread could be different from that updated value. In fact Java has the idea of a "main" memory, and this is the memory that holds the current "correct" value for variables. Threads can have their own copy of data for variables, and the thread copy can be different from the "main" memory. So in fact, it is possible for the "main" memory to have a value of 1 for i1, for thread1 to have a value of 2 for i1 and for thread2 to have a value of 3 for i1 if thread1 and thread2 have both updated i1 but those updated value has not yet been propagated to "main" memory or other threads.
On the other hand, geti2() effectively accesses the value of i2 from "main" memory. A volatile variable is not allowed to have a local copy of a variable that is different from the value currently held in "main" memory. Effectively, a variable declared volatile must have it's data synchronized across all threads, so that whenever you access or update the variable in any thread, all other threads immediately see the same value. Generally volatile variables have a higher access and update overhead than "plain" variables. Generally threads are allowed to have their own copy of data is for better efficiency.
There are two differences between volitile and synchronized.
Firstly synchronized obtains and releases locks on monitors which can force only one thread at a time to execute a code block. That's the fairly well known aspect to synchronized. But synchronized also synchronizes memory. In fact synchronized synchronizes the whole of thread memory with "main" memory. So executing geti3() does the following:
The thread acquires the lock on the monitor for object this .
The thread memory flushes all its variables, i.e. it has all of its variables effectively read from "main" memory .
The code block is executed (in this case setting the return value to the current value of i3, which may have just been reset from "main" memory).
(Any changes to variables would normally now be written out to "main" memory, but for geti3() we have no changes.)
The thread releases the lock on the monitor for object this.
So where volatile only synchronizes the value of one variable between thread memory and "main" memory, synchronized synchronizes the value of all variables between thread memory and "main" memory, and locks and releases a monitor to boot. Clearly synchronized is likely to have more overhead than volatile.
http://javaexp.blogspot.com/2007/12/difference-between-volatile-and.html
There are 3 main issues with multithreading:
Race Conditions
Caching / stale memory
Compiler and CPU optimisations
volatile can solve 2 & 3, but can't solve 1. synchronized/explicit locks can solve 1, 2 & 3.
Elaboration:
Consider this thread unsafe code:
x++;
While it may look like one operation, it's actually 3: reading the current value of x from memory, adding 1 to it, and saving it back to memory. If few threads try to do it at the same time, the result of the operation is undefined. If x originally was 1, after 2 threads operating the code it may be 2 and it may be 3, depending on which thread completed which part of the operation before control was transferred to the other thread. This is a form of race condition.
Using synchronized on a block of code makes it atomic - meaning it make it as if the 3 operations happen at once, and there's no way for another thread to come in the middle and interfere. So if x was 1, and 2 threads try to preform x++ we know in the end it will be equal to 3. So it solves the race condition problem.
synchronized (this) {
x++; // no problem now
}
Marking x as volatile does not make x++; atomic, so it doesn't solve this problem.
In addition, threads have their own context - i.e. they can cache values from main memory. That means that a few threads can have copies of a variable, but they operate on their working copy without sharing the new state of the variable among other threads.
Consider that on one thread, x = 10;. And somewhat later, in another thread, x = 20;. The change in value of x might not appear in the first thread, because the other thread has saved the new value to its working memory, but hasn't copied it to the main memory. Or that it did copy it to the main memory, but the first thread hasn't updated its working copy. So if now the first thread checks if (x == 20) the answer will be false.
Marking a variable as volatile basically tells all threads to do read and write operations on main memory only. synchronized tells every thread to go update their value from main memory when they enter the block, and flush the result back to main memory when they exit the block.
Note that unlike data races, stale memory is not so easy to (re)produce, as flushes to main memory occur anyway.
The complier and CPU can (without any form of synchronization between threads) treat all code as single threaded. Meaning it can look at some code, that is very meaningful in a multithreading aspect, and treat it as if it’s single threaded, where it’s not so meaningful. So it can look at a code and decide, in sake of optimisation, to reorder it, or even remove parts of it completely, if it doesn’t know that this code is designed to work on multiple threads.
Consider the following code:
boolean b = false;
int x = 10;
void threadA() {
x = 20;
b = true;
}
void threadB() {
if (b) {
System.out.println(x);
}
}
You would think that threadB could only print 20 (or not print anything at all if threadB if-check is executed before setting b to true), as b is set to true only after x is set to 20, but the compiler/CPU might decide to reorder threadA, in that case threadB could also print 10. Marking b as volatile ensures that it won’t be reordered (or discarded in certain cases). Which mean threadB could only print 20 (or nothing at all). Marking the methods as syncrhonized will achieve the same result. Also marking a variable as volatile only ensures that it won’t get reordered, but everything before/after it can still be reordered, so synchronization can be more suited in some scenarios.
Note that before Java 5 New Memory Model, volatile didn’t solve this issue.
synchronized is method level/block level access restriction modifier. It will make sure that one thread owns the lock for critical section. Only the thread,which own a lock can enter synchronized block. If other threads are trying to access this critical section, they have to wait till current owner releases the lock.
volatile is variable access modifier which forces all threads to get latest value of the variable from main memory. No locking is required to access volatile variables. All threads can access volatile variable value at same time.
A good example to use volatile variable : Date variable.
Assume that you have made Date variable volatile. All the threads, which access this variable always get latest data from main memory so that all threads show real (actual) Date value. You don't need different threads showing different time for same variable. All threads should show right Date value.
Have a look at this article for better understanding of volatile concept.
Lawrence Dol cleary explained your read-write-update query.
Regarding your other queries
When is it more suitable to declare variables volatile than access them through synchronized?
You have to use volatile if you think all threads should get actual value of the variable in real time like the example I have explained for Date variable.
Is it a good idea to use volatile for variables that depend on input?
Answer will be same as in first query.
Refer to this article for better understanding.
The following quote is taken from this tutorial.
I am unable to understand the last line of the paragraph (which I have applied a bold font to). What is meant by side-effects of code?
Atomic actions cannot be interleaved, so they can be used without fear of thread interference. However, this does not eliminate all need to synchronize atomic actions, because memory consistency errors are still possible. Using volatile variables reduces the risk of memory consistency errors, because any write to a volatile variable establishes a happens-before relationship with subsequent reads of that same variable. This means that changes to a volatile variable are always visible to other threads. What's more, it also means that when a thread reads a volatile variable, it sees not just the latest change to the volatile, but also the side effects of the code that led up the change.
"Side-effect" here means that the thread updates some memory location outside of its own stack. Basically that means that it changed the state of some object on the heap.
The synchronization mechanism that ensures that the volatile field gets published properly also results (as a side-effect, hihi) in the same guarantee for any memory writes that the other thread did before it updated that field.
A side effect refers simply to the modification of some kind of state - for instance:
Changing the value of a variable;
Writing some data to disk;
Enabling or disabling a button in the User Interface.
So in the last line, the thread would see any changes of state caused by a side effect of the code beyond just that of the volatile variable being read.
If a variable is declared as volatile then for every read access the local cache is updated from main memory and for every write access the local cache is flushed to main memory. But which variables are synched? I believe that if I declare v to be volatile that is not the only variable that is synched. But some other(or all) variables in the thread cache is also synched. A thread stack consists of several frames each for every method called. Does it go ahead and sync every frame? Does a synchronized block sync every variable in the object?
You need to clarify what you mean be a "cache flush". accessing volatile variables does have memory effects outside of the variable itself. in fact, volatile variables have the same memory semantics as a synchronized block. everything done by a thread before it writes a volatile variable is flushed to "main memory" in such a way that any other thread which subsequently reads that volatile variable will see the effects. that said, the guarantees of volatile variables are scoped such that the only guarantees are related to accesses on the same volatile variable. i.e. there is no guarantee that after a volatile variable is written that everything done by the thread will be visible to all other threads.
When you read a volatile variable all the JVM promises is that that variable contains the latest value that has been written to it by any thread.
Behind the scenes the system is probably causing a complete cache flush of all threads to RAM before the read occurs but this is not specified and therefore may or may not happen.
So, in summary, it could be every frame but it will include the variable accessed.
Pay a visit to Brian Goetz's excellent Java theory and practice: Managing volatility. You will find comments such as:
... threads will automatically see the most up-to-date value for volatile variables.
and that really sums it up, the important point here is that volatile variables are no more than that. They are not a cache flushing mechanism, although they use cache flushing to achieve their goal.
I am wondering at the difference between declaring a variable as volatile and always accessing the variable in a synchronized(this) block in Java?
According to this article http://www.javamex.com/tutorials/synchronization_volatile.shtml there is a lot to be said and there are many differences but also some similarities.
I am particularly interested in this piece of info:
...
access to a volatile variable never has the potential to block: we're only ever doing a simple read or write, so unlike a synchronized block we will never hold on to any lock;
because accessing a volatile variable never holds a lock, it is not suitable for cases where we want to read-update-write as an atomic operation (unless we're prepared to "miss an update");
What do they mean by read-update-write? Isn't a write also an update or do they simply mean that the update is a write that depends on the read?
Most of all, when is it more suitable to declare variables volatile rather than access them through a synchronized block? Is it a good idea to use volatile for variables that depend on input? For instance, there is a variable called render that is read through the rendering loop and set by a keypress event?
It's important to understand that there are two aspects to thread safety.
execution control, and
memory visibility
The first has to do with controlling when code executes (including the order in which instructions are executed) and whether it can execute concurrently, and the second to do with when the effects in memory of what has been done are visible to other threads. Because each CPU has several levels of cache between it and main memory, threads running on different CPUs or cores can see "memory" differently at any given moment in time because threads are permitted to obtain and work on private copies of main memory.
Using synchronized prevents any other thread from obtaining the monitor (or lock) for the same object, thereby preventing all code blocks protected by synchronization on the same object from executing concurrently. Synchronization also creates a "happens-before" memory barrier, causing a memory visibility constraint such that anything done up to the point some thread releases a lock appears to another thread subsequently acquiring the same lock to have happened before it acquired the lock. In practical terms, on current hardware, this typically causes flushing of the CPU caches when a monitor is acquired and writes to main memory when it is released, both of which are (relatively) expensive.
Using volatile, on the other hand, forces all accesses (read or write) to the volatile variable to occur to main memory, effectively keeping the volatile variable out of CPU caches. This can be useful for some actions where it is simply required that visibility of the variable be correct and order of accesses is not important. Using volatile also changes treatment of long and double to require accesses to them to be atomic; on some (older) hardware this might require locks, though not on modern 64 bit hardware. Under the new (JSR-133) memory model for Java 5+, the semantics of volatile have been strengthened to be almost as strong as synchronized with respect to memory visibility and instruction ordering (see http://www.cs.umd.edu/users/pugh/java/memoryModel/jsr-133-faq.html#volatile). For the purposes of visibility, each access to a volatile field acts like half a synchronization.
Under the new memory model, it is still true that volatile variables cannot be reordered with each other. The difference is that it is now no longer so easy to reorder normal field accesses around them. Writing to a volatile field has the same memory effect as a monitor release, and reading from a volatile field has the same memory effect as a monitor acquire. In effect, because the new memory model places stricter constraints on reordering of volatile field accesses with other field accesses, volatile or not, anything that was visible to thread A when it writes to volatile field f becomes visible to thread B when it reads f.
-- JSR 133 (Java Memory Model) FAQ
So, now both forms of memory barrier (under the current JMM) cause an instruction re-ordering barrier which prevents the compiler or run-time from re-ordering instructions across the barrier. In the old JMM, volatile did not prevent re-ordering. This can be important, because apart from memory barriers the only limitation imposed is that, for any particular thread, the net effect of the code is the same as it would be if the instructions were executed in precisely the order in which they appear in the source.
One use of volatile is for a shared but immutable object is recreated on the fly, with many other threads taking a reference to the object at a particular point in their execution cycle. One needs the other threads to begin using the recreated object once it is published, but does not need the additional overhead of full synchronization and it's attendant contention and cache flushing.
// Declaration
public class SharedLocation {
static public volatile SomeObject someObject=new SomeObject(); // default object
}
// Publishing code
SharedLocation.someObject=new SomeObject(...); // new object is published
// Using code
// Note: do not simply use SharedLocation.someObject.xxx(), since although
// someObject will be internally consistent for xxx(), a subsequent
// call to yyy() might be inconsistent with xxx() if the object was
// replaced in between calls.
private String getError() {
SomeObject myCopy=SharedLocation.someObject; // gets current copy
...
int cod=myCopy.getErrorCode();
String txt=myCopy.getErrorText();
return (cod+" - "+txt);
}
// And so on, with myCopy always in a consistent state within and across calls
// Eventually we will return to the code that gets the current SomeObject.
Speaking to your read-update-write question, specifically. Consider the following unsafe code:
public void updateCounter() {
if(counter==1000) { counter=0; }
else { counter++; }
}
Now, with the updateCounter() method unsynchronized, two threads may enter it at the same time. Among the many permutations of what could happen, one is that thread-1 does the test for counter==1000 and finds it true and is then suspended. Then thread-2 does the same test and also sees it true and is suspended. Then thread-1 resumes and sets counter to 0. Then thread-2 resumes and again sets counter to 0 because it missed the update from thread-1. This can also happen even if thread switching does not occur as I have described, but simply because two different cached copies of counter were present in two different CPU cores and the threads each ran on a separate core. For that matter, one thread could have counter at one value and the other could have counter at some entirely different value just because of caching.
What's important in this example is that the variable counter was read from main memory into cache, updated in cache and only written back to main memory at some indeterminate point later when a memory barrier occurred or when the cache memory was needed for something else. Making the counter volatile is insufficient for thread-safety of this code, because the test for the maximum and the assignments are discrete operations, including the increment which is a set of non-atomic read+increment+write machine instructions, something like:
MOV EAX,counter
INC EAX
MOV counter,EAX
Volatile variables are useful only when all operations performed on them are "atomic", such as my example where a reference to a fully formed object is only read or written (and, indeed, typically it's only written from a single point). Another example would be a volatile array reference backing a copy-on-write list, provided the array was only read by first taking a local copy of the reference to it.
volatile is a field modifier, while synchronized modifies code blocks and methods. So we can specify three variations of a simple accessor using those two keywords:
int i1;
int geti1() {return i1;}
volatile int i2;
int geti2() {return i2;}
int i3;
synchronized int geti3() {return i3;}
geti1() accesses the value currently stored in i1 in the current thread.
Threads can have local copies of variables, and the data does not have to be the same as the data held in other threads.In particular, another thread may have updated i1 in it's thread, but the value in the current thread could be different from that updated value. In fact Java has the idea of a "main" memory, and this is the memory that holds the current "correct" value for variables. Threads can have their own copy of data for variables, and the thread copy can be different from the "main" memory. So in fact, it is possible for the "main" memory to have a value of 1 for i1, for thread1 to have a value of 2 for i1 and for thread2 to have a value of 3 for i1 if thread1 and thread2 have both updated i1 but those updated value has not yet been propagated to "main" memory or other threads.
On the other hand, geti2() effectively accesses the value of i2 from "main" memory. A volatile variable is not allowed to have a local copy of a variable that is different from the value currently held in "main" memory. Effectively, a variable declared volatile must have it's data synchronized across all threads, so that whenever you access or update the variable in any thread, all other threads immediately see the same value. Generally volatile variables have a higher access and update overhead than "plain" variables. Generally threads are allowed to have their own copy of data is for better efficiency.
There are two differences between volitile and synchronized.
Firstly synchronized obtains and releases locks on monitors which can force only one thread at a time to execute a code block. That's the fairly well known aspect to synchronized. But synchronized also synchronizes memory. In fact synchronized synchronizes the whole of thread memory with "main" memory. So executing geti3() does the following:
The thread acquires the lock on the monitor for object this .
The thread memory flushes all its variables, i.e. it has all of its variables effectively read from "main" memory .
The code block is executed (in this case setting the return value to the current value of i3, which may have just been reset from "main" memory).
(Any changes to variables would normally now be written out to "main" memory, but for geti3() we have no changes.)
The thread releases the lock on the monitor for object this.
So where volatile only synchronizes the value of one variable between thread memory and "main" memory, synchronized synchronizes the value of all variables between thread memory and "main" memory, and locks and releases a monitor to boot. Clearly synchronized is likely to have more overhead than volatile.
http://javaexp.blogspot.com/2007/12/difference-between-volatile-and.html
There are 3 main issues with multithreading:
Race Conditions
Caching / stale memory
Compiler and CPU optimisations
volatile can solve 2 & 3, but can't solve 1. synchronized/explicit locks can solve 1, 2 & 3.
Elaboration:
Consider this thread unsafe code:
x++;
While it may look like one operation, it's actually 3: reading the current value of x from memory, adding 1 to it, and saving it back to memory. If few threads try to do it at the same time, the result of the operation is undefined. If x originally was 1, after 2 threads operating the code it may be 2 and it may be 3, depending on which thread completed which part of the operation before control was transferred to the other thread. This is a form of race condition.
Using synchronized on a block of code makes it atomic - meaning it make it as if the 3 operations happen at once, and there's no way for another thread to come in the middle and interfere. So if x was 1, and 2 threads try to preform x++ we know in the end it will be equal to 3. So it solves the race condition problem.
synchronized (this) {
x++; // no problem now
}
Marking x as volatile does not make x++; atomic, so it doesn't solve this problem.
In addition, threads have their own context - i.e. they can cache values from main memory. That means that a few threads can have copies of a variable, but they operate on their working copy without sharing the new state of the variable among other threads.
Consider that on one thread, x = 10;. And somewhat later, in another thread, x = 20;. The change in value of x might not appear in the first thread, because the other thread has saved the new value to its working memory, but hasn't copied it to the main memory. Or that it did copy it to the main memory, but the first thread hasn't updated its working copy. So if now the first thread checks if (x == 20) the answer will be false.
Marking a variable as volatile basically tells all threads to do read and write operations on main memory only. synchronized tells every thread to go update their value from main memory when they enter the block, and flush the result back to main memory when they exit the block.
Note that unlike data races, stale memory is not so easy to (re)produce, as flushes to main memory occur anyway.
The complier and CPU can (without any form of synchronization between threads) treat all code as single threaded. Meaning it can look at some code, that is very meaningful in a multithreading aspect, and treat it as if it’s single threaded, where it’s not so meaningful. So it can look at a code and decide, in sake of optimisation, to reorder it, or even remove parts of it completely, if it doesn’t know that this code is designed to work on multiple threads.
Consider the following code:
boolean b = false;
int x = 10;
void threadA() {
x = 20;
b = true;
}
void threadB() {
if (b) {
System.out.println(x);
}
}
You would think that threadB could only print 20 (or not print anything at all if threadB if-check is executed before setting b to true), as b is set to true only after x is set to 20, but the compiler/CPU might decide to reorder threadA, in that case threadB could also print 10. Marking b as volatile ensures that it won’t be reordered (or discarded in certain cases). Which mean threadB could only print 20 (or nothing at all). Marking the methods as syncrhonized will achieve the same result. Also marking a variable as volatile only ensures that it won’t get reordered, but everything before/after it can still be reordered, so synchronization can be more suited in some scenarios.
Note that before Java 5 New Memory Model, volatile didn’t solve this issue.
synchronized is method level/block level access restriction modifier. It will make sure that one thread owns the lock for critical section. Only the thread,which own a lock can enter synchronized block. If other threads are trying to access this critical section, they have to wait till current owner releases the lock.
volatile is variable access modifier which forces all threads to get latest value of the variable from main memory. No locking is required to access volatile variables. All threads can access volatile variable value at same time.
A good example to use volatile variable : Date variable.
Assume that you have made Date variable volatile. All the threads, which access this variable always get latest data from main memory so that all threads show real (actual) Date value. You don't need different threads showing different time for same variable. All threads should show right Date value.
Have a look at this article for better understanding of volatile concept.
Lawrence Dol cleary explained your read-write-update query.
Regarding your other queries
When is it more suitable to declare variables volatile than access them through synchronized?
You have to use volatile if you think all threads should get actual value of the variable in real time like the example I have explained for Date variable.
Is it a good idea to use volatile for variables that depend on input?
Answer will be same as in first query.
Refer to this article for better understanding.