What's the difference between InterlockedCompareExchangeRelease() and InterlockedCompareExchangeAcquire()?
When I try to learn the synchronization functions with WIN32 API, I find there are two functions named differently but seems to do the same thing:
LONG __cdecl InterlockedCompareExchangeRelease(
__inout LONG volatile *Destination,
__in LONG Exchange,
__in LONG Comparand
);
and
LONG __cdecl InterlockedCompareExchangeAcquire(
__inout LONG volatile *Destination,
__in LONG Exchange,
__in LONG Comparand
);
I check the MSDN, it says those functions are:
Performs an atomic compare-and-exchange operation on the specified
values. The function compares two specified 32-bit values and
exchanges with another 32-bit value based on the outcome of the
comparison.
but for InterlockedCompareExchangeAcquire(),
The operation is performed with acquire memory access semantics.
and for InterlockedCompareExchangeRelease(),
The exchange is performed with release memory access semantics.
So I'm curious about the difference between these two functions.
When to use the acquire memory access semantics or release memory access semantics?
Are there any examples?
Thanks!
The plain version uses a full barrier while the suffixed versions only deals with loads or stores, this can be faster on some CPUs (Itanium-based processors etc)
MSDN has a article about Acquire and Release Semantics and the Interlocked* API as well as this great blog post. The Linux memory barrier documentation might also be useful...
I found this and this on MSDN:
Acquire memory semantics specify that the memory operation being performed by the current thread will be visible before any other memory operations are attempted. Release memory semantics specify that the memory operation being performed by the current thread will be visible after all other memory operations have been completed. These semantics allow you to force memory operations to be performed in a specific order. Use acquire semantics when entering a protected region and release semantics when leaving it.
Related
Which ecosystems allow to create multiple heaps right now?
Is it possible to have multiple heaps in java?
garbage collection and memory management in Erlang
Is there any benefit to use multiple heaps for memory management purposes?
AppDomains don't create new heaps (there is still one heap for all domains). So, what one need to do to launch several different GC inside the single process?
Which syntactic primitives does one need to create? How a runtime should support that primitives?
Which ecosystems allow to create multiple heaps right now?
One obvious answer would be "C++" (feel free to fill in surrounding pieces as you see fit, if you don't consider a language to be an "ecosystem" in itself).
C++ allows you to specify heaps along a few different axes. One is by the type of an object--you can specify allocation for a particular type by overloading operator new and operator delete for that type:
class Foo {
static void *operator new(size_t size);
static void operator delete(void *block, size_t size);
};
It's then up to you to connect these heap management functions to an actual source of memory. You might allocate that via ::operator new, or you might (for example) go directly to the OS, such as with something like GlobalAlloc or VirtualAlloc on Windows, sbrk on UNIX-like systems, or just have pre-specified blocks of memory on a bare-metal embedded system.
Along a somewhat different axis, all the containers in the C++ standard library allocate and free memory via Allocator classes. The Allocator for any particular collection is specified as a template parameter, so (for example) a declaration for std::vector looks something like this:
template <class T, class Alloc=std::allocator<T>>
class vector {
// ...
};
This lets you specify a heap that will be used to allocate objects in that collection. Much as with operator new and operator delete, this really only specifies the interface by which the collection will allocate and free memory--it's up to you to connect that to code that actually manages the heap.
Garbage Collection
As far as garbage collection goes: I personally find it annoying, and advise against its use as a general rule. The problem is that it while it can (at least from one perspective) fix some types of problems with memory management, it does nothing to help management of other resources--and (unfortunately) I haven't seen anything like a tracing collector for file handles, network sockets, database connections, and so on. RAII provides a uniform method for dealing with resource management in general.
That said, if you really insist on using GC, C++ does support that as well. Prior to C++11, GC was entirely usable on a practical level, but led to what was technically undefined behavior under a few obscure circumstances, such as:
storing a pointer in a file, and reading it back in, or
modifying the bits of a pointer, later un-doing that modification
...and later taking the re-constituted pointer and dereferencing it. Obviously, while the pointer wasn't visible to the CPU, the pointed-to block of memory became eligible for GC, so the later dereference caused problems. C++11 defined these circumstances, and added a few library calls (e.g., declare_reachable, undeclare_reachable) to deal with them (e.g., if you call decalare_reachable(block);, that block is not eligible for collection, regardless of whether a pointer to it is visible). As such, if you want to use GC with C++ you can, and the bounds of defined behavior are thoroughly specified. The only problem is that essentially no code ever calls declare_reachable and/or undeclare_reachable, so in real use they're likely to be of little or no help (but pointer swizzling and/or storage in a file are sufficiently rare that this is unlikely to pose a real problem).
For a practical example, you might want to look at the Boehm-Demers-Weiser collector (if you haven't already).
What is the actual difference between monitors and other synchronization primitives like mutexes, WinAPI events and critical sections? It looks for me that it's quite the same thing -- one thread at the time can lock the monitor, while other threads should wait for it to become free, much like in the case of events and critical sections.
So, what is the difference? Where am I wrong?
All these synchronization primitives under Windows have similar operations(wait and signal), but slightly different behaviour of these operations. So primitives' usage is usually differs.
Critical section has owner thread, so it can be released(signaled) only by the owner.
Also, unlike to other primitives, operations for critical section use pointer instead of HANDLE, so critical sections cannot be used by WaitForMultipleObjects and similar functions.
Mutexes are very similar to critical sections, but they are identified by a HANDLE, so they can be waited for together with other objects (using WaitForMultipleObjects).
SignalObjectAndWait function can also be used for mutexes.
Events support manually-reset mode, when successfull waiting on event doesn't reset it. So several waiters can bypass waiting for single event at the same time.
Semaphores (WinAPI variant for monitors) allows usage limit above 1, that is code section protected by semaphore is no longer exclusive, like with critical section and mutexes.
Also, semaphores has no owner semantic, so they can be signalled by any thread. This feature is critical for some algorithms.
I am porting a lock free queue from c++11 to go and i came across things such as
auto currentRead = writeIndex.load(std::memory_order_relaxed);
and in some cases std::memory_order_release and std::memory_order_aqcuire
also the equivelent for the above in c11 is something like
unsigned long currentRead = atomic_load_explicit(&q->writeIndex,memory_order_relaxed);
the meaning of those is described here
is there an equivalent to such thing in go or do i just use something like
var currentRead uint64 = atomic.LoadUint64(&q.writeIndex)
after porting i benchmarked and just using LoadUint64 it seems to work as expected but orders of magnitude slower and i wonder how much effect dose those specialized ops have on performance.
further info from the link i attached
memory_order_relaxed:Relaxed operation: there are no synchronization
or ordering constraints, only atomicity is required of this operation.
memory_order_consume:A load operation with this memory order performs
a consume operation on the affected memory location: no reads in the
current thread dependent on the value currently loaded can be
reordered before this load. This ensures that writes to data-dependent
variables in other threads that release the same atomic variable are
visible in the current thread. On most platforms, this affects
compiler optimizations only.
memory_order_acquire:A load operation with this memory order performs the acquire operation on the affected memory location: no
memory accesses in the current thread can be reordered before this
load. This ensures that all writes in other threads that release the
same atomic variable are visible in the current thread.
memory_order_release:A store operation with this memory order performs the release operation: no memory accesses in the current
thread can be reordered after this store. This ensures that all writes
in the current thread are visible in other threads that acquire or the
same atomic variable and writes that carry a dependency into the
atomic variable become visible in other threads that consume the same
atomic.
You need to read The Go Memory Model
You'll discover that Go has nothing like the control that you have in C++ - there isn't a direct translation of the C++ features in your post. This is a deliberate design decision by the Go authors - the Go motto is Do not communicate by sharing memory; instead, share memory by communicating.
Assuming that the standard go channel isn't good enough for what you want to do, you'll have 2 choices for each memory access, using the facilities in sync/atomic or not, and whether you need to use them or not will depend on a careful reading of the Go Memory Model and analysis of your code which only you can do.
It's my understanding of atomicity that it's used to make sure a value will be read/written in whole rather than in parts. For example, a 64-bit value that is really two 32-bit DWORDs (assume x86 here) must be atomic when shared between threads so that both DWORDs are read/written at the same time. That way one thread can't read half variable that's not updated. How do you guarantee atomicity?
Furthermore it's my understanding that volatility does not guarantee thread safety at all. Is that true?
I've seen it implied many places that simply being atomic/volatile is thread-safe. I don't see how that is. Won't I need a memory barrier as well to ensure that any values, atomic or otherwise, are read/written before they can actually be guaranteed to be read/written in the other thread?
So for example let's say I create a thread suspended, do some calculations to change some values to a struct available to the thread and then resume, for example:
HANDLE hThread = CreateThread(NULL, 0, thread_entry, (void *)&data, CREATE_SUSPENDED, NULL);
data->val64 = SomeCalculation();
ResumeThread(hThread);
I suppose this would depend on any memory barriers in ResumeThread? Should I do an interlocked exchange for val64? What if the thread were running, how does that change things?
I'm sure I'm asking a lot here but basically what I'm trying to figure out is what I asked in the title: a good explanation for atomicity, volatility and thread safety in Windows. Thanks
it's used to make sure a value will be read/written in whole
That's just a small part of atomicity. At its core it means "uninterruptible", an instruction on a processor whose side-effects cannot be interleaved with another instruction. By design, a memory update is atomic when it can be executed with a single memory-bus cycle. Which requires the address of the memory location to be aligned so that a single cycle can update it. An unaligned access requires extra work, part of the bytes written by one cycle and part by another. Now it is not uninterruptible anymore.
Getting aligned updates is pretty easy, it is a guarantee provided by the compiler. Or, more broadly, by the memory model implemented by the compiler. Which simply chooses memory addresses that are aligned, sometimes intentionally leaving unused gaps of a few bytes to get the next variable aligned. An update to a variable that's larger than the native word size of the processor can never be atomic.
But much more important are the kind of processor instructions you need to make threading work. Every processor implements a variant of the CAS instruction, compare-and-swap. It is the core atomic instruction you need to implement synchronization. Higher level synchronization primitives, like monitors (aka condition variables), mutexes, signals, critical sections and semaphores are all built on top of that core instruction.
That's the minimum, a processor usually provide extra ones to make simple operations atomic. Like incrementing a variable, at its core an interruptible operation since it requires a read-modify-write operation. Having a need for it be atomic is very common, most any C++ program relies on it for example to implement reference counting.
volatility does not guarantee thread safety at all
It doesn't. It is an attribute that dates from much easier times, back when machines only had a single processor core. It only affects code generation, in particular the way a code optimizer tries to eliminate memory accesses and use a copy of the value in a processor register instead. Makes a big, big difference to code execution speed, reading a value from a register is easily 3 times faster than having to read it from memory.
Applying volatile ensures that the code optimizer does not consider the value in the register to be accurate and forces it to read memory again. It truly only matters on the kind of memory values that are not stable by themselves, devices that expose their registers through memory-mapped I/O. It has been abused heavily since that core meaning to try to put semantics on top of processors with a weak memory model, Itanium being the most egregious example. What you get with volatile today is strongly dependent on the specific compiler and runtime you use. Never use it for thread-safety, always use a synchronization primitive instead.
simply being atomic/volatile is thread-safe
Programming would be much simpler if that was true. Atomic operations only cover the very simple operations, a real program often needs to keep an entire object thread-safe. Having all its members updated atomically and never expose a view of the object that is partially updated. Something as simple as iterating a list is a core example, you can't have another thread modifying the list while you are looking at its elements. That's when you need to reach for the higher-level synchronization primitives, the kind that can block code until it is safe to proceed.
Real programs often suffer from this synchronization need and exhibit Amdahls' law behavior. In other words, adding an extra thread does not actually make the program faster. Sometimes actually making it slower. Whomever finds a better mouse-trap for this is guaranteed a Nobel, we're still waiting.
In general, C and C++ don't give any guarantees about how reading or writing a 'volatile' object behaves in multithreaded programs. (The 'new' C++11 probably does since it now includes threads as part of the standard, but tradiationally threads have not been part of standard C or C++.) Using volatile and making assumptions about atomicity and cache-coherence in code that's meant to be portable is a problem. It's a crap-shoot as to whether a particular compiler and platform will treat accesses to 'volatile' objects in a thread-safe way.
The general rule is: 'volatile' is not enough to ensure thread safe access. You should use some platform-provided mechanism (usually some functions or synchronisation objects) to access thread-shared values safely.
Now, specifically on Windows, specifically with the VC++ 2005+ compiler, and specifically on x86 and x64 systems, accessing a primitive object (like an int) can be made thread-safe if:
On 64- and 32-bit Windows, the object has to be a 32-bit type, and it has to be 32-bit aligned.
On 64-bit Windows, the object may also be a 64-bit type, and it has to be 64-bit aligned.
It must be declared volatile.
If those are true, then accesses to the object will be volatile, atomic and be surrounded by instructions that ensure cache-coherency. The size and alignment conditions must be met so that the compiler makes code that performs atomic operations when accessing the object. Declaring the object volatile ensures that the compiler doesn't make code optimisations related to caching previous values it may have read into a register and ensures that code generated includes appropriate memory barrier instructions when it's accessed.
Even so, you're probably still better off using something like the Interlocked* functions for accessing small things, and bog standard synchronisation objects like Mutexes or CriticalSections for larger objects and data structures. Ideally, get libraries for and use data structures that already include appropriate locks. Let your libraries & OS do the hard work as much as possible!
In your example, I expect you do need to use a thread-safe access to update val64 whether the thread is started yet or not.
If the thread was already running, then you would definitely need some kind of thread-safe write to val64, either using InterchangeExchange64 or similar, or by acquiring and releasing some kind of synchronisation object which will perform appropriate memory barrier instructions. Similarly, the thread would need to use a thread-safe accessor to read it as well.
In the case where the thread hasn't been resumed yet, it's a bit less clear. It's possible that ResumeThread might use or act like a synchronisation function and do the memory barrier operations, but the documentation doesn't specify that it does, so it is better to assume that it doesn't.
References:
On atomicity of 32- and 64- bit aligned types... https://msdn.microsoft.com/en-us/library/windows/desktop/ms684122%28v=vs.85%29.aspx
On 'volatile' including memory fences... https://msdn.microsoft.com/en-us/library/windows/desktop/ms686355%28v=vs.85%29.aspx
Among the atomic operations provided by BSD (as given on the atomic(9) man page), there are atomic_load_acq_int() and atomic_store_rel_int(). In looking for the equivalent for other OSs (for example, by reading the atomic(3) man page for Mac OS X, the atomic_ops(3C) man page for Solaris, and the Interlocked*() functions for Windows), there don't seem to be any (obvious) equivalents for just atomically reading/writing an int.
Is this because that it's implied for those OSs that reads/writes for int are guaranteed to be atomic by default? (Or must you use declare them volatile in C/C++?)
If not, then how does one do atomic reads/writes of an int on those OSs?
(Atomic reads can be simulated by returning the result of an atomic add of 0, but there's no equivalent for doing atomic writes.)
I think you are mixing together atomic memory access with cache coherence. The former is the required hardware support for building synchronization primitives in software (spin-locks, semaphores, and mutexes), while the latter is the hardware support for multiple chips (several CPUs, and peripheral devices) working over the same bus, and having consistent view of the main memory.
Different compilers/libraries provide different utilities for the first. Here's, for example, GCC intrinsics for atomic memory access. They all boil down to generating either compare-and-swap or load-linked/store-conditional based instruction blocks depending on the platform support. Compile your source with, say, -S for GCC and see the assembler generated.
You don't have to do anything explicitly for cache coherency - it's all handled in hardware - but it definitely helps to understand how it works to avoid things like cache line ping-pong.
With all that, aligned single word reads and writes are atomic on all commodity platforms (somebody correct me if I'm wrong here). Since ints are less or equal to processor word in size, you are covered (see the GCC builtins link above).
It's the order of reads and writes that is important. Here's where architecture memory model is important. It dictates what operations can and cannot be re-ordered by the hardware. Example would be updating a linked list - you don't want other CPUs see a new item linked until the item itself is in consistent state. Explicit memory barriers (also often called "memory fences") might be required. Acquire barrier ensures that subsequent operations are not re-ordererd before the barrier (say you read the linked-list item pointer before the content of the item), Release barrier ensures that previous operations are not re-ordered after the barrier (you write the item content before writing the new link pointer).
volatile is often misunderstood as being related to all the above. In fact it is just an instruction to the compiler not to cache variable value in register, but read it from memory on each access. Many argue that it's "almost useless" for concurrent programming.
Apologies for lengthy reply. Hope this clears it a bit.
Edit:
Upcoming C++0x standard finally addresses concurrency, see Hans Boehm's C++ memory model papers for many details.