Confusion about definition of data race - multithreading

A data race happens when there are two memory accesses in a program where both:
target the same location
are performed concurrently by two threads
are not reads
are not synchronization operations
This definition is taken from, which borrows it from a research paper, so we can assume it to be correct.
Now consider this example:
import java.util.concurrent.*;
class DataRace{
static boolean flag = false;
static void raiseFlag() {
flag = true;
}
public static void main(String[] args) {
ForkJoinPool.commonPool().execute(DataRace::raiseFlag);
System.out.println(flag);
}
}
By my understanding, this satisfies the definition of a data race. We have two instructions accessing same location(flag), both are not reads, both are concurrent and are not synchronization operations. And so the output depends on how the threads interleave and can be either 'True' or 'False'.
If we assume this to be a data race, then I can just add locks before accesses and solve this. But even if I add locks in both threads, we know there is a race condition in locks also. So any thread can get the lock and the output can still be 'True' or 'False'.
So this is my confusion, and here are the two questions I would like to ask:
Is this a data race? If no, why not?
If it's a data race, why the proposed solution doesn't work?

First of all, the arbitrary order of thread execution is not the data race itself, even though it can cause it. If you need to synchronize 2 or more threads to execute their code in a specific order you have to use a waiting mechanism like monitors. Monitors are the constructs that can do the both mutual exclusion (locking) and waiting. Monitors are also known as the conditional variables and Java supports them.
Now the question is what the data race is. The data race occurs when 2 or more threads access the same memory location in the same time and some of the accesses are writes. This situation can lead to unpredictable values the memory location can contain.
A classical example. Lets have a 32 bits OS and the variable that is 64 bits long like long or double types. Lets have the long variable.
long SharedVariable;
And thread 1 that executes the following code.
SharedVariable=0;
And thread 2 that executes the following code.
SharedVariable=0x7FFF_FFFF_FFFF_FFFFL;
If an access to this variable is not protected by a lock, after the execution of both threads the SharedVariable can have one of the following values.
SharedVariable==0
SharedVariable==0x7FFF_FFFF_FFFF_FFFFL
**SharedVariable==0x0000_0000_FFFF_FFFFL**
**SharedVariable==0x7FFF_FFFF_0000_0000L**
The last 2 values are unexpected - caused by the data race.
The problem here is that on 32 bits OSs there is a guarantee that an access to the 32 bits variables are atomic - so the platform guarantees that even if 2 or more threads are accessing the same 32 bits memory location at the same time the access to that memory location is atomic - only a single thread can access such variable. But because we have 64 bits variable, on the CPU level, the write to 64 bits long variable will translate into 2 CPU instructions. So the code SharedVariable=0; is translated into something like this:
mov SharedVariableHigh32bits,0
mov SharedVariableLow32bits,0
And code SharedVariable=0x7FFF_FFFF_FFFF_FFFFL; is translated into something like this:
mov SharedVariableHigh32bits,0x7FFFFFFF
mov SharedVariableLow32bits,0xFFFFFFFF
Without the lock, the CPU can execute these 4 instructions in the following orders.
Order 1.
mov SharedVariableHigh32bits,0 // T1
mov SharedVariableLow32bits,0 // T1
mov SharedVariableHigh32bits,0x7FFFFFFF // T2
mov SharedVariableLow32bits,0xFFFFFFFF // T2
The result is: 0x7FFF_FFFF_FFFF_FFFFL.
Order 2.
mov SharedVariableHigh32bits,0x7FFFFFFF // T2
mov SharedVariableLow32bits,0xFFFFFFFF // T2
mov SharedVariableHigh32bits,0 // T1
mov SharedVariableLow32bits,0 // T1
The result is: 0.
Order 3.
mov SharedVariableHigh32bits,0x7FFFFFFF // T2
mov SharedVariableHigh32bits,0 // T1
mov SharedVariableLow32bits,0 // T1
mov SharedVariableLow32bits,0xFFFFFFFF // T2
The result is: 0x0000_0000_FFFF_FFFFL.
Order 4.
mov SharedVariableHigh32bits,0 // T1
mov SharedVariableHigh32bits,0x7FFFFFFF // T2
mov SharedVariableLow32bits,0xFFFFFFFF // T2
mov SharedVariableLow32bits,0 // T1
The result is: 0x7FFF_FFFF_0000_0000L.
So, the race condition caused a serious problem because you can get a value that is completely unexpected and invalid. By using locks, you can prevent it, but just using a lock doesn't guarantee the order of execution - which thread executes its code first. So if you use a lock, you will get just 2 orders of execution - order 1 and order 2, not getting the unexpected values 0x0000_0000_FFFF_FFFFL and 0x7FFF_FFFF_0000_0000L. But still, if you need to synchronize which thread executes first and which second, you need to use not just a lock, but also a wait mechanism that monitors (conditional variables) offer.
BTW according this article, Java guarantees an atomic access to all primitive type variables except the long and double. On 64 bits platforms even an access to long and double should be atomic but it looks like that the standard doesn't guarantee it.
And even if the standard guaranteed the atomic access it would be always better to use locks. Locks define the memory barriers that prevent some compiler optimizations that can reorder your code on the CPU instruction level and cause a problem if using the variables to control the order of execution.
So the simple advice here is that if you are not an concurrent programming expert (and I'm also not), and don't write SW that needs to get absolute maximum performance by using lock-free techniques, always use locks - even if accessing the variables that are guaranteed to have an atomic access.

Related

According to this function, can y = 8? [duplicate]

In general, for int num, num++ (or ++num), as a read-modify-write operation, is not atomic. But I often see compilers, for example GCC, generate the following code for it (try here):
void f()
{
int num = 0;
num++;
}
f():
push rbp
mov rbp, rsp
mov DWORD PTR [rbp-4], 0
add DWORD PTR [rbp-4], 1
nop
pop rbp
ret
Since line 5, which corresponds to num++ is one instruction, can we conclude that num++ is atomic in this case?
And if so, does it mean that so-generated num++ can be used in concurrent (multi-threaded) scenarios without any danger of data races (i.e. we don't need to make it, for example, std::atomic<int> and impose the associated costs, since it's atomic anyway)?
UPDATE
Notice that this question is not whether increment is atomic (it's not and that was and is the opening line of the question). It's whether it can be in particular scenarios, i.e. whether one-instruction nature can in certain cases be exploited to avoid the overhead of the lock prefix. And, as the accepted answer mentions in the section about uniprocessor machines, as well as this answer, the conversation in its comments and others explain, it can (although not with C or C++).
This is absolutely what C++ defines as a Data Race that causes Undefined Behaviour, even if one compiler happened to produce code that did what you hoped on some target machine. You need to use std::atomic for reliable results, but you can use it with memory_order_relaxed if you don't care about reordering. See below for some example code and asm output using fetch_add.
But first, the assembly language part of the question:
Since num++ is one instruction (add dword [num], 1), can we conclude that num++ is atomic in this case?
Memory-destination instructions (other than pure stores) are read-modify-write operations that happen in multiple internal steps. No architectural register is modified, but the CPU has to hold the data internally while it sends it through its ALU. The actual register file is only a small part of the data storage inside even the simplest CPU, with latches holding outputs of one stage as inputs for another stage, etc., etc.
Memory operations from other CPUs can become globally visible between the load and store. I.e. two threads running add dword [num], 1 in a loop would step on each other's stores. (See #Margaret's answer for a nice diagram). After 40k increments from each of two threads, the counter might have only gone up by ~60k (not 80k) on real multi-core x86 hardware.
"Atomic", from the Greek word meaning indivisible, means that no observer can see the operation as separate steps. Happening physically / electrically instantaneously for all bits simultaneously is just one way to achieve this for a load or store, but that's not even possible for an ALU operation. I went into a lot more detail about pure loads and pure stores in my answer to Atomicity on x86, while this answer focuses on read-modify-write.
The lock prefix can be applied to many read-modify-write (memory destination) instructions to make the entire operation atomic with respect to all possible observers in the system (other cores and DMA devices, not an oscilloscope hooked up to the CPU pins). That is why it exists. (See also this Q&A).
So lock add dword [num], 1 is atomic. A CPU core running that instruction would keep the cache line pinned in Modified state in its private L1 cache from when the load reads data from cache until the store commits its result back into cache. This prevents any other cache in the system from having a copy of the cache line at any point from load to store, according to the rules of the MESI cache coherency protocol (or the MOESI/MESIF versions of it used by multi-core AMD/Intel CPUs, respectively). Thus, operations by other cores appear to happen either before or after, not during.
Without the lock prefix, another core could take ownership of the cache line and modify it after our load but before our store, so that other store would become globally visible in between our load and store. Several other answers get this wrong, and claim that without lock you'd get conflicting copies of the same cache line. This can never happen in a system with coherent caches.
(If a locked instruction operates on memory that spans two cache lines, it takes a lot more work to make sure the changes to both parts of the object stay atomic as they propagate to all observers, so no observer can see tearing. The CPU might have to lock the whole memory bus until the data hits memory. Don't misalign your atomic variables!)
Note that the lock prefix also turns an instruction into a full memory barrier (like MFENCE), stopping all run-time reordering and thus giving sequential consistency. (See Jeff Preshing's excellent blog post. His other posts are all excellent, too, and clearly explain a lot of good stuff about lock-free programming, from x86 and other hardware details to C++ rules.)
On a uniprocessor machine, or in a single-threaded process, a single RMW instruction actually is atomic without a lock prefix. The only way for other code to access the shared variable is for the CPU to do a context switch, which can't happen in the middle of an instruction. So a plain dec dword [num] can synchronize between a single-threaded program and its signal handlers, or in a multi-threaded program running on a single-core machine. See the second half of my answer on another question, and the comments under it, where I explain this in more detail.
Back to C++:
It's totally bogus to use num++ without telling the compiler that you need it to compile to a single read-modify-write implementation:
;; Valid compiler output for num++
mov eax, [num]
inc eax
mov [num], eax
This is very likely if you use the value of num later: the compiler will keep it live in a register after the increment. So even if you check how num++ compiles on its own, changing the surrounding code can affect it.
(If the value isn't needed later, inc dword [num] is preferred; modern x86 CPUs will run a memory-destination RMW instruction at least as efficiently as using three separate instructions. Fun fact: gcc -O3 -m32 -mtune=i586 will actually emit this, because (Pentium) P5's superscalar pipeline didn't decode complex instructions to multiple simple micro-operations the way P6 and later microarchitectures do. See the Agner Fog's instruction tables / microarchitecture guide for more info, and the x86 tag wiki for many useful links (including Intel's x86 ISA manuals, which are freely available as PDF)).
Don't confuse the target memory model (x86) with the C++ memory model
Compile-time reordering is allowed. The other part of what you get with std::atomic is control over compile-time reordering, to make sure your num++ becomes globally visible only after some other operation.
Classic example: Storing some data into a buffer for another thread to look at, then setting a flag. Even though x86 does acquire loads/release stores for free, you still have to tell the compiler not to reorder by using flag.store(1, std::memory_order_release);.
You might be expecting that this code will synchronize with other threads:
// int flag; is just a plain global, not std::atomic<int>.
flag--; // Pretend this is supposed to be some kind of locking attempt
modify_a_data_structure(&foo); // doesn't look at flag, and the compiler knows this. (Assume it can see the function def). Otherwise the usual don't-break-single-threaded-code rules come into play!
flag++;
But it won't. The compiler is free to move the flag++ across the function call (if it inlines the function or knows that it doesn't look at flag). Then it can optimize away the modification entirely, because flag isn't even volatile.
(And no, C++ volatile is not a useful substitute for std::atomic. std::atomic does make the compiler assume that values in memory can be modified asynchronously similar to volatile, but there's much more to it than that. (In practice there are similarities between volatile int to std::atomic with mo_relaxed for pure-load and pure-store operations, but not for RMWs). Also, volatile std::atomic<int> foo is not necessarily the same as std::atomic<int> foo, although current compilers don't optimize atomics (e.g. 2 back-to-back stores of the same value) so volatile atomic wouldn't change the code-gen.)
Defining data races on non-atomic variables as Undefined Behaviour is what lets the compiler still hoist loads and sink stores out of loops, and many other optimizations for memory that multiple threads might have a reference to. (See this LLVM blog for more about how UB enables compiler optimizations.)
As I mentioned, the x86 lock prefix is a full memory barrier, so using num.fetch_add(1, std::memory_order_relaxed); generates the same code on x86 as num++ (the default is sequential consistency), but it can be much more efficient on other architectures (like ARM). Even on x86, relaxed allows more compile-time reordering.
This is what GCC actually does on x86, for a few functions that operate on a std::atomic global variable.
See the source + assembly language code formatted nicely on the Godbolt compiler explorer. You can select other target architectures, including ARM, MIPS, and PowerPC, to see what kind of assembly language code you get from atomics for those targets.
#include <atomic>
std::atomic<int> num;
void inc_relaxed() {
num.fetch_add(1, std::memory_order_relaxed);
}
int load_num() { return num; } // Even seq_cst loads are free on x86
void store_num(int val){ num = val; }
void store_num_release(int val){
num.store(val, std::memory_order_release);
}
// Can the compiler collapse multiple atomic operations into one? No, it can't.
# g++ 6.2 -O3, targeting x86-64 System V calling convention. (First argument in edi/rdi)
inc_relaxed():
lock add DWORD PTR num[rip], 1 #### Even relaxed RMWs need a lock. There's no way to request just a single-instruction RMW with no lock, for synchronizing between a program and signal handler for example. :/ There is atomic_signal_fence for ordering, but nothing for RMW.
ret
inc_seq_cst():
lock add DWORD PTR num[rip], 1
ret
load_num():
mov eax, DWORD PTR num[rip]
ret
store_num(int):
mov DWORD PTR num[rip], edi
mfence ##### seq_cst stores need an mfence
ret
store_num_release(int):
mov DWORD PTR num[rip], edi
ret ##### Release and weaker doesn't.
store_num_relaxed(int):
mov DWORD PTR num[rip], edi
ret
Notice how MFENCE (a full barrier) is needed after a sequential-consistency stores. x86 is strongly ordered in general, but StoreLoad reordering is allowed. Having a store buffer is essential for good performance on a pipelined out-of-order CPU. Jeff Preshing's Memory Reordering Caught in the Act shows the consequences of not using MFENCE, with real code to show reordering happening on real hardware.
Re: discussion in comments on #Richard Hodges' answer about compilers merging std::atomic num++; num-=2; operations into one num--; instruction:
A separate Q&A on this same subject: Why don't compilers merge redundant std::atomic writes?, where my answer restates a lot of what I wrote below.
Current compilers don't actually do this (yet), but not because they aren't allowed to. C++ WG21/P0062R1: When should compilers optimize atomics? discusses the expectation that many programmers have that compilers won't make "surprising" optimizations, and what the standard can do to give programmers control. N4455 discusses many examples of things that can be optimized, including this one. It points out that inlining and constant-propagation can introduce things like fetch_or(0) which may be able to turn into just a load() (but still has acquire and release semantics), even when the original source didn't have any obviously redundant atomic ops.
The real reasons compilers don't do it (yet) are: (1) nobody's written the complicated code that would allow the compiler to do that safely (without ever getting it wrong), and (2) it potentially violates the principle of least surprise. Lock-free code is hard enough to write correctly in the first place. So don't be casual in your use of atomic weapons: they aren't cheap and don't optimize much. It's not always easy easy to avoid redundant atomic operations with std::shared_ptr<T>, though, since there's no non-atomic version of it (although one of the answers here gives an easy way to define a shared_ptr_unsynchronized<T> for gcc).
Getting back to num++; num-=2; compiling as if it were num--:
Compilers are allowed to do this, unless num is volatile std::atomic<int>. If a reordering is possible, the as-if rule allows the compiler to decide at compile time that it always happens that way. Nothing guarantees that an observer could see the intermediate values (the num++ result).
I.e. if the ordering where nothing becomes globally visible between these operations is compatible with the ordering requirements of the source
(according to the C++ rules for the abstract machine, not the target architecture), the compiler can emit a single lock dec dword [num] instead of lock inc dword [num] / lock sub dword [num], 2.
num++; num-- can't disappear, because it still has a Synchronizes With relationship with other threads that look at num, and it's both an acquire-load and a release-store which disallows reordering of other operations in this thread. For x86, this might be able to compile to an MFENCE, instead of a lock add dword [num], 0 (i.e. num += 0).
As discussed in PR0062, more aggressive merging of non-adjacent atomic ops at compile time can be bad (e.g. a progress counter only gets updated once at the end instead of every iteration), but it can also help performance without downsides (e.g. skipping the atomic inc / dec of ref counts when a copy of a shared_ptr is created and destroyed, if the compiler can prove that another shared_ptr object exists for entire lifespan of the temporary.)
Even num++; num-- merging could hurt fairness of a lock implementation when one thread unlocks and re-locks right away. If it's never actually released in the asm, even hardware arbitration mechanisms won't give another thread a chance to grab the lock at that point.
With current gcc6.2 and clang3.9, you still get separate locked operations even with memory_order_relaxed in the most obviously optimizable case. (Godbolt compiler explorer so you can see if the latest versions are different.)
void multiple_ops_relaxed(std::atomic<unsigned int>& num) {
num.fetch_add( 1, std::memory_order_relaxed);
num.fetch_add(-1, std::memory_order_relaxed);
num.fetch_add( 6, std::memory_order_relaxed);
num.fetch_add(-5, std::memory_order_relaxed);
//num.fetch_add(-1, std::memory_order_relaxed);
}
multiple_ops_relaxed(std::atomic<unsigned int>&):
lock add DWORD PTR [rdi], 1
lock sub DWORD PTR [rdi], 1
lock add DWORD PTR [rdi], 6
lock sub DWORD PTR [rdi], 5
ret
Without many complications an instruction like add DWORD PTR [rbp-4], 1 is very CISC-style.
It perform three operations: load the operand from memory, increment it, store the operand back to memory.
During these operations the CPU acquire and release the bus twice, in between any other agent can acquire it too and this violates the atomicity.
AGENT 1 AGENT 2
load X
inc C
load X
inc C
store X
store X
X is incremented only once.
...and now let's enable optimisations:
f():
rep ret
OK, let's give it a chance:
void f(int& num)
{
num = 0;
num++;
--num;
num += 6;
num -=5;
--num;
}
result:
f(int&):
mov DWORD PTR [rdi], 0
ret
another observing thread (even ignoring cache synchronisation delays) has no opportunity to observe the individual changes.
compare to:
#include <atomic>
void f(std::atomic<int>& num)
{
num = 0;
num++;
--num;
num += 6;
num -=5;
--num;
}
where the result is:
f(std::atomic<int>&):
mov DWORD PTR [rdi], 0
mfence
lock add DWORD PTR [rdi], 1
lock sub DWORD PTR [rdi], 1
lock add DWORD PTR [rdi], 6
lock sub DWORD PTR [rdi], 5
lock sub DWORD PTR [rdi], 1
ret
Now, each modification is:-
observable in another thread, and
respectful of similar modifications happening in other threads.
atomicity is not just at the instruction level, it involves the whole pipeline from processor, through the caches, to memory and back.
Further info
Regarding the effect of optimisations of updates of std::atomics.
The c++ standard has the 'as if' rule, by which it is permissible for the compiler to reorder code, and even rewrite code provided that the outcome has the exact same observable effects (including side-effects) as if it had simply executed your code.
The as-if rule is conservative, particularly involving atomics.
consider:
void incdec(int& num) {
++num;
--num;
}
Because there are no mutex locks, atomics or any other constructs that influence inter-thread sequencing, I would argue that the compiler is free to rewrite this function as a NOP, eg:
void incdec(int&) {
// nada
}
This is because in the c++ memory model, there is no possibility of another thread observing the result of the increment. It would of course be different if num was volatile (might influence hardware behaviour). But in this case, this function will be the only function modifying this memory (otherwise the program is ill-formed).
However, this is a different ball game:
void incdec(std::atomic<int>& num) {
++num;
--num;
}
num is an atomic. Changes to it must be observable to other threads that are watching. Changes those threads themselves make (such as setting the value to 100 in between the increment and decrement) will have very far-reaching effects on the eventual value of num.
Here is a demo:
#include <thread>
#include <atomic>
int main()
{
for (int iter = 0 ; iter < 20 ; ++iter)
{
std::atomic<int> num = { 0 };
std::thread t1([&] {
for (int i = 0 ; i < 10000000 ; ++i)
{
++num;
--num;
}
});
std::thread t2([&] {
for (int i = 0 ; i < 10000000 ; ++i)
{
num = 100;
}
});
t2.join();
t1.join();
std::cout << num << std::endl;
}
}
sample output:
99
99
99
99
99
100
99
99
100
100
100
100
99
99
100
99
99
100
100
99
The add instruction is not atomic. It references memory, and two processor cores may have different local cache of that memory.
IIRC the atomic variant of the add instruction is called lock xadd
Since line 5, which corresponds to num++ is one instruction, can we conclude that num++ is atomic in this case?
It is dangerous to draw conclusions based on "reverse engineering" generated assembly. For example, you seem to have compiled your code with optimization disabled, otherwise the compiler would have thrown away that variable or loaded 1 directly to it without invoking operator++. Because the generated assembly may change significantly, based on optimization flags, target CPU, etc., your conclusion is based on sand.
Also, your idea that one assembly instruction means an operation is atomic is wrong as well. This add will not be atomic on multi-CPU systems, even on the x86 architecture.
Even if your compiler always emitted this as an atomic operation, accessing num from any other thread concurrently would constitute a data race according to the C++11 and C++14 standards and the program would have undefined behavior.
But it is worse than that. First, as has been mentioned, the instruction generated by the compiler when incrementing a variable may depend on the optimization level. Secondly, the compiler may reorder other memory accesses around ++num if num is not atomic, e.g.
int main()
{
std::unique_ptr<std::vector<int>> vec;
int ready = 0;
std::thread t{[&]
{
while (!ready);
// use "vec" here
});
vec.reset(new std::vector<int>());
++ready;
t.join();
}
Even if we assume optimistically that ++ready is "atomic", and that the compiler generates the checking loop as needed (as I said, it's UB and therefore the compiler is free to remove it, replace it with an infinite loop, etc.), the compiler might still move the pointer assignment, or even worse the initialization of the vector to a point after the increment operation, causing chaos in the new thread. In practice, I would not be surprised at all if an optimizing compiler removed the ready variable and the checking loop completely, as this does not affect observable behavior under language rules (as opposed to your private hopes).
In fact, at last year's Meeting C++ conference, I've heard from two compiler developers that they very gladly implement optimizations that make naively written multi-threaded programs misbehave, as long as language rules allow it, if even a minor performance improvement is seen in correctly written programs.
Lastly, even if you didn't care about portability, and your compiler was magically nice, the CPU you are using is very likely of a superscalar CISC type and will break down instructions into micro-ops, reorder and/or speculatively execute them, to an extent only limited by synchronizing primitives such as (on Intel) the LOCK prefix or memory fences, in order to maximize operations per second.
To make a long story short, the natural responsibilities of thread-safe programming are:
Your duty is to write code that has well-defined behavior under language rules (and in particular the language standard memory model).
Your compiler's duty is to generate machine code which has the same well-defined (observable) behavior under the target architecture's memory model.
Your CPU's duty is to execute this code so that the observed behavior is compatible with its own architecture's memory model.
If you want to do it your own way, it might just work in some cases, but understand that the warranty is void, and you will be solely responsible for any unwanted outcomes. :-)
PS: Correctly written example:
int main()
{
std::unique_ptr<std::vector<int>> vec;
std::atomic<int> ready{0}; // NOTE the use of the std::atomic template
std::thread t{[&]
{
while (!ready);
// use "vec" here
});
vec.reset(new std::vector<int>());
++ready;
t.join();
}
This is safe because:
The checks of ready cannot be optimized away according to language rules.
The ++ready happens-before the check that sees ready as not zero, and other operations cannot be reordered around these operations. This is because ++ready and the check are sequentially consistent, which is another term described in the C++ memory model and that forbids this specific reordering. Therefore the compiler must not reorder the instructions, and must also tell the CPU that it must not e.g. postpone the write to vec to after the increment of ready. Sequentially consistent is the strongest guarantee regarding atomics in the language standard. Lesser (and theoretically cheaper) guarantees are available e.g. via other methods of std::atomic<T>, but these are definitely for experts only, and may not be optimized much by the compiler developers, because they are rarely used.
On a single-core x86 machine, an add instruction will generally be atomic with respect to other code on the CPU1. An interrupt can't split a single instruction down the middle.
Out-of-order execution is required to preserve the illusion of instructions executing one at a time in order within a single core, so any instruction running on the same CPU will either happen completely before or completely after the add.
Modern x86 systems are multi-core, so the uniprocessor special case doesn't apply.
If one is targeting a small embedded PC and has no plans to move the code to anything else, the atomic nature of the "add" instruction could be exploited. On the other hand, platforms where operations are inherently atomic are becoming more and more scarce.
(This doesn't help you if you're writing in C++, though. Compilers don't have an option to require num++ to compile to a memory-destination add or xadd without a lock prefix. They could choose to load num into a register and store the increment result with a separate instruction, and will likely do that if you use the result.)
Footnote 1: The lock prefix existed even on original 8086 because I/O devices operate concurrently with the CPU; drivers on a single-core system need lock add to atomically increment a value in device memory if the device can also modify it, or with respect to DMA access.
Back in the day when x86 computers had one CPU, the use of a single instruction ensured that interrupts would not split the read/modify/write and if the memory would not be used as a DMA buffer too, it was atomic in fact (and C++ did not mention threads in the standard, so this wasn’t addressed).
When it was rare to have a dual processor (e.g. dual-socket Pentium Pro) on a customer desktop, I effectively used this to avoid the LOCK prefix on a single-core machine and improve performance.
Today, it would only help against multiple threads that were all set to the same CPU affinity, so the threads you are worried about would only come into play via time slice expiring and running the other thread on the same CPU (core). That is not realistic.
With modern x86/x64 processors, the single instruction is broken up into several micro ops and furthermore the memory reading and writing is buffered. So different threads running on different CPUs will not only see this as non-atomic but may see inconsistent results concerning what it reads from memory and what it assumes other threads have read to that point in time: you need to add memory fences to restore sane behavior.
No.
https://www.youtube.com/watch?v=31g0YE61PLQ
(That's just a link to the "No" scene from "The Office")
Do you agree that this would be a possible output for the program:
sample output:
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
100
If so, then the compiler is free to make that the only possible output for the program, in whichever way the compiler wants. ie a main() that just puts out 100s.
This is the "as-if" rule.
And regardless of output, you can think of thread synchronization the same way - if thread A does num++; num--; and thread B reads num repeatedly, then a possible valid interleaving is that thread B never reads between num++ and num--. Since that interleaving is valid, the compiler is free to make that the only possible interleaving. And just remove the incr/decr entirely.
There are some interesting implications here:
while (working())
progress++; // atomic, global
(ie imagine some other thread updates a progress bar UI based on progress)
Can the compiler turn this into:
int local = 0;
while (working())
local++;
progress += local;
probably that is valid. But probably not what the programmer was hoping for :-(
The committee is still working on this stuff. Currently it "works" because compilers don't optimize atomics much. But that is changing.
And even if progress was also volatile, this would still be valid:
int local = 0;
while (working())
local++;
while (local--)
progress++;
:-/
That a single compiler's output, on a specific CPU architecture, with optimizations disabled (since gcc doesn't even compile ++ to add when optimizing in a quick&dirty example), seems to imply incrementing this way is atomic doesn't mean this is standard-compliant (you would cause undefined behavior when trying to access num in a thread), and is wrong anyways, because add is not atomic in x86.
Note that atomics (using the lock instruction prefix) are relatively heavy on x86 (see this relevant answer), but still remarkably less than a mutex, which isn't very appropriate in this use-case.
Following results are taken from clang++ 3.8 when compiling with -Os.
Incrementing an int by reference, the "regular" way :
void inc(int& x)
{
++x;
}
This compiles into :
inc(int&):
incl (%rdi)
retq
Incrementing an int passed by reference, the atomic way :
#include <atomic>
void inc(std::atomic<int>& x)
{
++x;
}
This example, which is not much more complex than the regular way, just gets the lock prefix added to the incl instruction - but caution, as previously stated this is not cheap. Just because assembly looks short doesn't mean it's fast.
inc(std::atomic<int>&):
lock incl (%rdi)
retq
Yes, but...
Atomic is not what you meant to say. You're probably asking the wrong thing.
The increment is certainly atomic. Unless the storage is misaligned (and since you left alignment to the compiler, it is not), it is necessarily aligned within a single cache line. Short of special non-caching streaming instructions, each and every write goes through the cache. Complete cache lines are being atomically read and written, never anything different.
Smaller-than-cacheline data is, of course, also written atomically (since the surrounding cache line is).
Is it thread-safe?
This is a different question, and there are at least two good reasons to answer with a definite "No!".
First, there is the possibility that another core might have a copy of that cache line in L1 (L2 and upwards is usually shared, but L1 is normally per-core!), and concurrently modifies that value. Of course that happens atomically, too, but now you have two "correct" (correctly, atomically, modified) values -- which one is the truly correct one now?
The CPU will sort it out somehow, of course. But the result may not be what you expect.
Second, there is memory ordering, or worded differently happens-before guarantees. The most important thing about atomic instructions is not so much that they are atomic. It's ordering.
You have the possibility of enforcing a guarantee that everything that happens memory-wise is realized in some guaranteed, well-defined order where you have a "happened before" guarantee. This ordering may be as "relaxed" (read as: none at all) or as strict as you need.
For example, you can set a pointer to some block of data (say, the results of some calculation) and then atomically release the "data is ready" flag. Now, whoever acquires this flag will be led into thinking that the pointer is valid. And indeed, it will always be a valid pointer, never anything different. That's because the write to the pointer happened-before the atomic operation.
When your compiler uses only a single instruction for the increment and your machine is single-threaded, your code is safe. ^^
Try compiling the same code on a non-x86 machine, and you'll quickly see very different assembly results.
The reason num++ appears to be atomic is because on x86 machines, incrementing a 32-bit integer is, in fact, atomic (assuming no memory retrieval takes place). But this is neither guaranteed by the c++ standard, nor is it likely to be the case on a machine that doesn't use the x86 instruction set. So this code is not cross-platform safe from race conditions.
You also don't have a strong guarantee that this code is safe from Race Conditions even on an x86 architecture, because x86 doesn't set up loads and stores to memory unless specifically instructed to do so. So if multiple threads tried to update this variable simultaneously, they may end up incrementing cached (outdated) values
The reason, then, that we have std::atomic<int> and so on is so that when you're working with an architecture where the atomicity of basic computations is not guaranteed, you have a mechanism that will force the compiler to generate atomic code.

Not understanding semaphore on low level

Just watched a video on semaphores and tried digging for more information. Not quite sure how a semaphore works on an assembly level.
P(s):
s = s - 1
if (s < 0) {wait on s}
CRITICAL SECTION
V(s):
s = s + 1
if(threads are waiting on s) {wake one}
I understand what the concept is behind these function, however I am having trouble wrapping my head around this.
say S = 1
and you have 2 Threads: Thread 1 and Thread 2
Thread One Thread Two
load s load s
subtract s,1 subtract s,1
save s save s
Then there is a context switch in between the subtract and the save for both setting s to 0 for both. Wont both threads see s as 0 entering the critical section. I am not sure how one thread becomes exclusive if it is possible on the assembly level to context switch so that both can see s = 0.
The key thing is that the increment and decrement use atomic instructions in some way. Within x86, there is a form of the add instruction which combined with the lock prefix lets you perform an addition to a memory location atomically. Because it is a single instruction, a context switch can't happen during its execution, and the lock prefix means that the CPU ensures that no other accesses appear to happen during the increment.
If an atomic add is not available then there are other options. One common one is an atomic compare and swap instruction. Found on most systems supporting parallel or concurrent code, it is an instruction that takes two values, an old and new, and if the memory location is equal to to the old, set it to the new value. This can be used in a loop to implement an atomic add:
l:
load r0 s
mov r1 r0
add r0 -1
cas s r1 r0
jmpf l
This loads a value, then subtracts 1 from a copy of the value. we then attempt to store the the lower value, but if it has changed we fail, and start again.

Storing of wider operands in an atomic way. Why did lock solve the issue?

I am writing this post in reference to Atomic store. Structures
#Peter Cordes said:
What does it mean to lock? Especially, I know that lock is a prefix
that ensures about atomicity of "prefixed" instruction.
Lock as in
spinlock / mutex, not lock prefix. The lock prefix only ever works on
read-modify-write instructions; there is no lock mov [mem], eax to do
an atomic unaligned store or something. locked bus cycles are always
read-modify-write, as documented by Intel in the docs for cmpxchg. So
a lock mov store would also generate a load, which has different
semantics if you use it on memory-mapped I/O. (A read can trigger side
effects).
Ok, so I understand it well. But, I cannot understand why it is copied (stored) atomically. It could be a spinlock instead of a mutex, but the situation is the same. A critical section is safe, I agree. But there is no certainty about atomic execution of that.
I add an example to explain what I mean:
struct S{int a, b, c, d, e;};
std::mutex mut; // global
S s = {0}; // global
//From what I understand atomic store could look like:
store(const S& src){
mut.lock();
S* dst = this->getPointerOfRawStructure(); // pseudocode
dst->a = src.a;
dst->b = src.b;
dst->c = src.c;
dst->d = src.d;
dst->e = src.e;
// I know that we can copy it in a better (faster) way.
mut.unlock();
});
And now, let thread1 do:
std::atomic<S> as;
as.store(s);
Now, mutex is free, so thread1 succesfully calls store.
Let thread2 do something like;
S* ptr = &s; // address of global variable s declared before.
int ee = s->e;
And, let assume that thread1 executed
dst->a = src.a;
dst->b = src.b;
dst->c = src.c;
And now thread2 executed:
int ee = s->e;
Thread2 sees old value of s->e though as.store() was started firstly and it should be executed in atomic way. ( The another thread cannot see a half-written variable, actually it sees).
So, I don't still understand how atomicity is ensured with lock (spinlocks/mutex).
Of course, locks and critical sections make no guarantees about what can be observed by rogue agents who just go around them.
If you do some operations in a critical section, however you implement it, then everyone who agrees to also use it can only make observations consistent with the idea what a critical section executes atomically, because their own use of the critical section happens either before or after anyone elses use of it, not during.
If you're just going to go poking around in things that were supposed to be protected by some mechanism without using that mechanism, obviously that mechanism is then in no position to stop Bad Things happening.
Locking the door doesn't help if someone decides to enter through the window.

pthreads: If I increment a global from two different threads, can there be sync issues?

Suppose I have two threads A and B that are both incrementing a ~global~ variable "count". Each thread runs a for loop like this one:
for(int i=0; i<1000; i++)
count++; //alternatively, count = count + 1;
i.e. each thread increments count 1000 times, and let's say count starts at 0. Can there be sync issues in this case? Or will count correctly equal 2000 when the execution is finished? I guess since the statement "count = count + 1" may break down into TWO assembly instructions, there is potential for the other thread to be swapped in between these two instructions? Not sure. What do you think?
Yes there can be sync issues in this case. You need to either protect the count variable with a mutex, or use a (usually platform specific) atomic operation.
Example using pthread mutexes
static pthread_mutex_t mutex = PTHREAD_MUTEX_INITIALIZER;
for(int i=0; i<1000; i++) {
pthread_mutex_lock(&mutex);
count++;
pthread_mutex_unlock(&mutex);
}
Using atomic ops
There is a prior discussion of platform specific atomic ops here:
UNIX Portable Atomic Operations
If you only need to support GCC, this approach is straightforward. If you're supporting other compilers, you'll probably have to make some per-platform decisions.
Count clearly needs to be protected with a mutex or other synchronization mechanism.
At a fundamental level, the count++ statment breaks down to:
load count into register
increment register
store count from register
A context switch could occur before/after any of those steps, leading to situations like:
Thread 1: load count into register A (value = 0)
Thread 2: load count into register B (value = 0)
Thread 1: increment register A (value = 1)
Thread 1: store count from register A (value = 1)
Thread 2: increment register B (value = 1)
Thread 2: store count from register B (value = 1)
As you can see, both threads completed one iteration of the loop, but the net result is that count was only incremented once.
You probably would also want to make count volatile to force loads & stores to go to memory, since a good optimizer would likely keep count in a register unless otherwise told.
Also, I would suggest that if this is all the work that's going to be done in your threads, performance will dramatically drop from all the mutex locking/unlocking required to keep it consistent. Threads should have much bigger work units to perform.
Yes, there can be sync problems.
As an example of the possible issues, there is no guarantee that an increment itself is an atomic operation.
In other words, if one thread reads the value for increment then gets swapped out, the other thread could come in and change it, then the first thread will write back the wrong value:
+-----+
| 0 | Value stored in memory (0).
+-----+
| 0 | Thread 1 reads value into register (r1 = 0).
+-----+
| 0 | Thread 2 reads value into register (r2 = 0).
+-----+
| 1 | Thread 2 increments r2 and writes back.
+-----+
| 1 | Thread 1 increments r1 and writes back.
+-----+
So you can see that, even though both threads have tried to increment the value, it's only increased by one.
This is just one of the possible problems. It may also be that the write itself is not atomic and one thread may update only part of the value before being swapped out.
If you have atomic operations that are guaranteed to work in your implementation, you can use them. Otherwise, use mutexes, That's what pthreads provides for synchronisation (and guarantees will work) so is the safest approach.
I guess since the statement "count = count + 1" may break down into TWO assembly instructions, there is potential for the other thread to be swapped in between these two instructions? Not sure. What do you think?
Don't think like this. You're writing C code and pthreads code. You don't have to ever think about assembly code to know how your code will behave.
The pthreads standard does not define the behavior when one thread accesses an object while another thread is, or might be, modifying it. So unless you're writing platform-specific code, you should assume this code can do anything -- even crash.
The obvious pthreads fix is to use mutexes. If your platform has atomic operations, you can use those.
I strongly urge you not to delve into detailed discussions about how it might fail or what the assembly code might look like. Regardless of what you might or might not think compilers or CPUs might do, the behavior of the code is undefined. And it's too easy to convince yourself you've covered every way you can think of that it might fail and then you miss one and it fails.

When should the Win32 InterlockedExchange function be used?

I came across the function InterlockedExchange and was wondering when I should use this function. In my opinion, setting a 32 Bit value on an x86 processor should always be atomic?
In the case where I want to use the function, the new value does not depend on the old value (it is not an increment operation).
Could you provide an example where this method is mandatory (I'm not looking for InterlockedCompareExchange)
InterlockedExchange is both a write and a read -- it returns the previous value.
This is necessary to ensure another thread didn't write a different value just after you did. For example, say you're trying to increment a variable. You can read the value, add 1, then set the new value with InterlockedExchange. The value returned by InterlockedExchange must match the value you originally read, otherwise another thread probably incremented it at the same time, and you need to loop around and try again.
As well as writing the new value, InterlockedExchange also reads and returns the previous value; this whole operation is atomic. This is useful for lock-free algorithms.
(Incidentally, 32-bit writes are not guaranteed to be atomic. Consider the case where the write is unaligned and straddles a cache boundary, for instance.)
In a multi-processor or multi-core machine each core has it's own cache - so each core has each own potentially different "view" of what the content of the system memory is.
Thread synchronization mechanisms take care of synchronizing between cores, for more information look at http://blogs.msdn.com/oldnewthing/archive/2008/10/03/8969397.aspx or google for acquire and release semantics
Setting a 32-bit value is atomic, but only if you're setting a literal.
b = a is 2 operations:
mov eax,dword ptr [a]
mov dword ptr [b],eax
Theoretically there could be some interruption between the first and second operation.
Writing a value is never atomic by default. When you write a value to a variable, several machine instructions are generated. With modern, preemptive OSes, the OS might switch to another thread between the individual operations of the write.
This is even more a problem on multi-processor machines, where several threads could be executing at the same time, and trying to write to a single memory location simultaneously.
Interlocked operations avoid this by using specialized instructions to make the write (x86 has dedicated instructions for this kind of situation), which do the read-modify-write in one instruction. These instructions also lock the memory bus of all processors, to ensure that no other executing thread could be writing to the value at the same time.
InterlockedExchange makes sure that the change of a variable and the return of its original value are not interrupted by other threads.
So, if 'i' is an int, these calls (taken individually) do not need InterlockedExchange around 'i':
a = i;
i = 9;
i = a;
i = a + 9;
a = i + 9;
if(0 == i)
None of these statements rely upon BOTH the initial AND final values of 'i'. But these following calls DO need InterlockedExchange around 'i':
a = i++; //a = InterlockedExchange(&i, i + 1);
Without it, two threads running through this same code might get the same value of 'i' assigned to 'a' or 'a' may unexpectedly skip two or more numbers.
if(0 == i++) //if(0 == InterlockedExchange(&i, i + 1))
Two threads may both execute the code that is only supposed to happen once.
etc.
wow, so many conflicting answers. Hard to sift through who's right, who's wrong, and what information is misleading.
I'm unsure of the answer too, given the above half-answers, but I think it works like this, I may be wrong, and it will be interesting to find out if I am:
32-bit read & writes ARE atomic, but depending on your code, that may not mean much.
don't worry about non-aligned read/writes. ALL 32-bit writes to a 32-bit variable have to be aligned or the machine page-faults.
don't worry about a write wrapping around the end of a cached page, that can't happen.
If you need to write-then-read on one thread, and you're writing on another thread, then you need to use InterlockedExchange. If you're simply reading the value on one thread, and writing it on another, then you don't need to use it, but those values may be wiggly because of multithreading.

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