Optimization and multithreading in B.Stroustrup's new book - c++

Please refer to section 41.2.2 Instruction Reordering of "TCPL" 4th edition by B.Stroustrup, which I transcribe below:
To gain performance, compilers, optimizers, and hardware reorder
instructions. Consider:
// thread 1:
int x;
bool x_init;
void init()
{
x = initialize(); // no use of x_init in initialize()
x_init = true;
// ...
}
For this piece of code there is no stated reason to assign to x before
assigning to x_init. The optimizer (or the hardware instruction
scheduler) may decide to speed up the program by executing x_init =
true first. We probably meant for x_init to indicate whether x had
been initialized by initializer() or not. However, we did not say
that, so the hardware, the compiler, and the optimizer do not know
that.
Add another thread to the program:
// thread 2:
extern int x;
extern bool x_init;
void f2()
{
int y;
while (!x_init) // if necessary, wait for initialization to complete
this_thread::sleep_for(milliseconds{10});
y = x;
// ...
}
Now we have a problem: thread 2 may never wait and thus will assign an
uninitialized x to y. Even if thread 1 did not set x_init and x in
‘‘the wrong order,’’ we still may have a problem. In thread 2, there
are no assignments to x_init, so an optimizer may decide to lift the
evaluation of !x_init out of the loop, so that thread 2 either never
sleeps or sleeps forever.
Does the Standard allow the reordering in thread 1? (some quote from the Standard would be forthcoming) Why would that speed up the program?
Both answers in this discussion on SO seem to indicate that no such optimization occurs when there are global variables in the code, as x_init above.
What does the author mean by "to lift the evaluation of !x_init out of the loop"? Is this something like this?
if( !x_init ) while(true) this_thread::sleep_for(milliseconds{10});
y = x;

This is not so much a issue of the C++ compiler/standard, but that of modern CPUs. Have a look here. The compiler isn't going to emit memory barrier instructions between the assignments of x and x_init unless you tell it to.
For what it is worth, prior to C++11, the standard had no notion of multi threading in it's abstract machine model. Things are a bit nicer these days.

The C++11 standard does not "allow" or "prevent" reordering. It specifies some way to force a specific "barrier" that, it turns, prevent the compiler to move instructions before/after them. A compiler, in this example might reorder the assignment because it might be more efficient on a CPU with multiple computing unit (ALU/Hyperthreading/etc...) even with a single core. Typically, if your CPU has 2 ALU that can work in parallel, there is no reason the compiler would not try to feed them with as much work as it can.
I'm not speaking of out-of-order reordering of the CPU instructions that's done internally in Intel CPU (for example), but compile time ordering to ensure all the computing resources are busy doing some work.
I think it depends on the compiler compilation flags. Typically unless you tell it to, the compiler must assume that another compilation unit (say B.cpp, which is not visible at compile time) can have a "extern bool x_init", and can change it at any time. Then, the re-ordering optimization would break with the expected behavior (B can define the initialize() function). This example is trivial and unlikely to break. The linked SO answer are not related to this "optimization", but simply that, in their case, the compiler can not make the assumption that the global array is not modified externally, and as such can not make the optimization. This is not like your example.
Yes. It's a very common optimization trick, instead of:
// test is a bool
for (int i = 0; i < 345; i++) {
if (test) do_something();
}
The compiler might do:
if (test) for(int i = 0; i < 345; i++) { do_something(); }
And save 344 useless tests.

Related

Difference between Interlocked, InterlockedAcquire, and InterlockedRelease if single thread reordering is impossible

In all likelihood, a lockless implementation is already overkill for the purposes of my application, but I wanted to look into memory barriers and lockless-ness anyways in case I ever actually need to use these concepts in the future.
From what I can tell:
an "InterlockedAcquire" function performs an atomic operation while preventing the compiler from moving code statements after the InterlockedAcquire to before the InterlockedAcquire.
an "InterlockedRelease" function performs an atomic operation while preventing the compiler from moving code statements before the InterlockedRelease to after the InterlockedRelease.
a vanilla "Interlocked" function performs an atomic operation while preventing the compiler from moving code statements in either direction across the Interlocked call.
My question is, if a function is structured such that the compiler can't reorder any of the code anyways because doing so would affect single-threaded behavior, is there a difference between any of the variants of an Interlocked function, or all they all effectively the same? Is the only difference between them how they interact with code reordering?
For a more concrete example, here's my current application - the produce() function as part of what will eventually be a multiple producer, single consumer queue built using a circular buffer:
template <typename T>
class Queue {
private:
long headIndex;
long tailIndex;
T* array[MAXQUEUESIZE];
public:
Queue() {
headIndex = 0;
tailIndex = 0;
memset(array, 0, MAXQUEUESIZE*sizeof(void*);
}
~Queue() {
}
bool produce(T value) {
//1) prevents concurrent calls to produce() from causing corruption:
long indexRetVal;
long reservedIndex;
do {
reservedIndex = tailIndex;
indexRetVal = InterlockedCompareExchange64(&tailIndex, (reservedIndex + 1) % MAXQUEUESIZE, reservedIndex);
} while (indexRetVal != reservedIndex);
//2) allocates the node.
T* newValPtr = (T*) malloc(sizeof(T));
if (newValPtr == null) {
OutputDebugString("Queue: malloc returned null");
return false;
}
*newValPtr = value;
//3) prevents a concurrent call to consume from causing corruption by atomically replacing the old pointer:
T* valPtrRetVal = InterlockedCompareExchangePointer(array + reservedIndex, newValPtr, null);
//if the previous value wasn't null, then our circular buffer overflowed:
if (valPtrRetVal != null) {
OutputDebugString("Queue: circular buffer overflowed");
free(newValPtr); //as pointed out by RbMm
return false;
}
//otherwise, everything worked fine
return true;
}
};
As I understand it, 3) will occur after 1) and 2) regardless of what I do anyways, but I should change 1) to an InterlockedRelease because I don't care whether it occurs before or after 2) and I should let the compiler decide.
My question is, if a function is structured such that the compiler can't reorder any of the code anyways because doing so would affect single-threaded behavior, is there a difference between any of the variants of an Interlocked function, or all they all effectively the same? Is the only difference between them how they interact with code reordering?
You may be confusing C++ statements with instructions. Your question isn't CPU specific, so you have to pretend you have no idea what the CPU instructions look like.
Consider this code:
if (a == 2)
{
b = 5;
}
Now, here's an example of a re-ordering of this code that doesn't affect a single thread:
int c = b;
b = 5;
if (a != 2)
b = c;
This performs the same operations but in a different order. It has no effect on single-threaded code. But, of course, if another thread was accessing b, it could see a value of 5 from this code even if a was never 2.
Thus it could also see a value of 5 from the original code even if a is never 2!
Why, because the two bits of code perform the same from the point of view of a single thread. And unless you use operations with guaranteed threading semantics, that's all the compiler, CPU, caches, and other platform components need to preserve.
So most likely, your belief that reordering any of the code would affect single-threaded behavior is probably incorrect. There's lots of ways to reorder and optimize code that doesn't affect single-threaded behavior.
There is an document on the msdn Explained the difference: Acquire and Release Semantics.
For the sample:
a++;
b++;
c++;
If we use acquire semantics to increment a, other processors would always see the increment of a before the increments of b and c;
If we use release semantics to increment c, other processors would always see the increments of a and b before the increment of c;
the InterlockedXxx routines perform, have both acquire and release semantics by default.
More specific, for 4 values:
a++;
b++;
c++;
d++;
If we use acquire semantics to increment b, other processors would always see the increment of b before the increments of c and d;
The order may be a->b->c,d or b->a,c,d.
If we use release semantics to increment c, other processors would always see the increments of a and b before the increment of c;
The order may be a,b->c->d or a,b,d->c.
To quote from this answer of #antiduh:
Acquire says "only worry about stuff after me". Release says "only
worry about stuff before me". Combining those both is a full memory
barrier.
All three versions prevent the compiler from moving code across the function call, but the compiler is not the only place that reordering takes place.
Modern CPUs have "out-of-order execution" and even "speculative execution". Acquire and release semantics cause the code to compiler to instructions with flags or prefixes controlling reordering within the CPU.

Optimization barrier for microbenchmarks in MSVC: tell the optimizer you clobber memory?

Chandler Carruth introduced two functions in his CppCon2015 talk that can be used to do some fine-grained inhibition of the optimizer. They are useful to write micro-benchmarks that the optimizer won't simply nuke into meaninglessness.
void clobber() {
asm volatile("" : : : "memory");
}
void escape(void* p) {
asm volatile("" : : "g"(p) : "memory");
}
These use inline assembly statements to change the assumptions of the optimizer.
The assembly statement in clobber states that the assembly code in it can read and write anywhere in memory. The actual assembly code is empty, but the optimizer won't look into it because it's asm volatile. It believes it when we tell it the code might read and write everywhere in memory. This effectively prevents the optimizer from reordering or discarding memory writes prior to the call to clobber, and forces memory reads after the call to clobber†.
The one in escape, additionally makes the pointer p visible to the assembly block. Again, because the optimizer won't look into the actual inline assembly code that code can be empty, and the optimizer will still assume that the block uses the address pointed by the pointer p. This effectively forces whatever p points to be in memory and not not in a register, because the assembly block might perform a read from that address.
(This is important because the clobber function won't force reads nor writes for anything that the compilers decides to put in a register, since the assembly statement in clobber doesn't state that anything in particular must be visible to the assembly.)
All of this happens without any additional code being generated directly by these "barriers". They are purely compile-time artifacts.
These use language extensions supported in GCC and in Clang, though. Is there a way to have similar behaviour when using MSVC?
† To understand why the optimizer has to think this way, imagine if the assembly block were a loop adding 1 to every byte in memory.
Given your approximation of escape(), you should also be fine with the following approximation of clobber() (note that this is a draft idea, deferring some of the solution to the implementation of the function nextLocationToClobber()):
// always returns false, but in an undeducible way
bool isClobberingEnabled();
// The challenge is to implement this function in a way,
// that will make even the smartest optimizer believe that
// it can deliver a valid pointer pointing anywhere in the heap,
// stack or the static memory.
volatile char* nextLocationToClobber();
const bool clobberingIsEnabled = isClobberingEnabled();
volatile char* clobberingPtr;
inline void clobber() {
if ( clobberingIsEnabled ) {
// This will never be executed, but the compiler
// cannot know about it.
clobberingPtr = nextLocationToClobber();
*clobberingPtr = *clobberingPtr;
}
}
UPDATE
Question: How would you ensure that isClobberingEnabled returns false "in an undeducible way"? Certainly it would be trivial to place the definition in another translation unit, but the minute you enable LTCG, that strategy is defeated. What did you have in mind?
Answer: We can take advantage of a hard-to-prove property from the number theory, for example, Fermat's Last Theorem:
bool undeducible_false() {
// It took mathematicians more than 3 centuries to prove Fermat's
// last theorem in its most general form. Hardly that knowledge
// has been put into compilers (or the compiler will try hard
// enough to check all one million possible combinations below).
// Caveat: avoid integer overflow (Fermat's theorem
// doesn't hold for modulo arithmetic)
std::uint32_t a = std::clock() % 100 + 1;
std::uint32_t b = std::rand() % 100 + 1;
std::uint32_t c = reinterpret_cast<std::uintptr_t>(&a) % 100 + 1;
return a*a*a + b*b*b == c*c*c;
}
I have used the following in place of escape.
#ifdef _MSC_VER
#pragma optimize("", off)
template <typename T>
inline void escape(T* p) {
*reinterpret_cast<char volatile*>(p) =
*reinterpret_cast<char const volatile*>(p); // thanks, #milleniumbug
}
#pragma optimize("", on)
#endif
It's not perfect but it's close enough, I think.
Sadly, I don't have a way to emulate clobber.

Why doesn't my C++ compiler optimize these memory writes away?

I created this program. It does nothing of interest but use processing power.
Looking at the output with objdump -d, I can see the three rand calls and corresponding mov instructions near the end even when compiling with O3 .
Why doesn't the compiler realize that memory isn't going to be used and just replace the bottom half with while(1){}? I'm using gcc, but I'm mostly interested in what is required by the standard.
/*
* Create a program that does nothing except slow down the computer.
*/
#include <cstdlib>
#include <unistd.h>
int getRand(int max) {
return rand() % max;
}
int main() {
for (int thread = 0; thread < 5; thread++) {
fork();
}
int len = 1000;
int *garbage = (int*)malloc(sizeof(int)*len);
for (int x = 0; x < len; x++) {
garbage[x] = x;
}
while (true) {
garbage[getRand(len)] = garbage[getRand(len)] - garbage[getRand(len)];
}
}
Because GCC isn't smart enough to perform this optimization on dynamically allocated memory. However, if you change garbageto be a local array instead, GCC compiles the loop to this:
.L4:
call rand
call rand
call rand
jmp .L4
This just calls rand repeatedly (which is needed because the call has side effects), but optimizes out the reads and writes.
If GCC was even smarter, it could also optimize out the randcalls, because its side effects only affect any later randcalls, and in this case there aren't any. However, this sort of optimization would probably be a waste of compiler writers' time.
It can't, in general, tell that rand() doesn't have observable side-effects here, and it isn't required to remove those calls.
It could remove the writes, but it may be the use of arrays is enough to suppress that.
The standard neither requires nor prohibits what it is doing. As long as the program has the correct observable behaviour any optimisation is purely a quality of implementation matter.
This code causes undefined behaviour because it has an infinite loop with no observable behaviour. Therefore any result is permissible.
In C++14 the text is 1.10/27:
The implementation may assume that any thread will eventually do one of the following:
terminate,
make a call to a library I/O function,
access or modify a volatile object, or
perform a synchronization operation or an atomic operation.
[Note: This is intended to allow compiler transformations such as removal of empty loops, even when termination cannot be proven. —end note ]
I wouldn't say that rand() counts as an I/O function.
Related question
Leave it a chance to crash by array overflow ! The compiler won't speculate on the range of outputs of getRand.

about spin lock

i have some questions in boost spinlock code :
class spinlock
{
public:
spinlock()
: v_(0)
{
}
bool try_lock()
{
long r = InterlockedExchange(&v_, 1);
_ReadWriteBarrier(); // 1. what this mean
return r == 0;
}
void lock()
{
for (unsigned k = 0; !try_lock(); ++k)
{
yield(k);
}
}
void unlock()
{
_ReadWriteBarrier();
*const_cast<long volatile*>(&v_) = 0;
// 2. Why don't need to use InterlockedExchange(&v_, 0);
}
private:
long v_;
};
A ReadWriteBarrier() is a "memory barrier" (in this case for both reads and writes), a special instruction to the processor to ensure that any instructions resulting in memory operations have completed (load & store operations - or in for example x86 processors, any opertion which has a memory operand at either side). In this particular case, to make sure that the InterlockedExchange(&v_,1) has completed before we continue.
Because an InterlockedExchange would be less efficient (takes more interaction with any other cores in the machine to ensure all other processor cores have 'let go' of the value - which makes no sense, since most likely (in correctly working code) we only unlock if we actually hold the lock, so no other processor will have a different value cached than what we're writing over anyway), and a volatile write to the memory will be just as good.
The barriers are there to ensure memory synchronization; without
them, different threads may see modifications of memory in
different orders.
And the InterlockedExchange isn't necessary in the second case
because we're not interested in the previous value. The role of
InterlockedExchange is doubtlessly to set the value and return
the previous value. (And why v_ would be long, when it can
only take values 0 and 1, is beyond me.)
There are three issues with atomic access to variables. First, ensuring that there is no thread switch in the middle of reading or writing a value; if this happens it's called "tearing"; the second thread can see a partly written value, which will usually be nonsensical. Second, ensuring that all processors see the change that is being made with a write, or that the processor reading a value sees any previous changes to that value; this is called "cache coherency". Third, ensuring that the compiler doesn't move code across the read or write; this is called "code motion". InterlockedExchange does the first two; although the MSDN documentation is rather muddled, _ReadWriteBarrier does the third, and possibly the second.

Strange C++ performance difference?

I just stumbled upon a change that seems to have counterintuitive performance ramifications. Can anyone provide a possible explanation for this behavior?
Original code:
for (int i = 0; i < ct; ++i) {
// do some stuff...
int iFreq = getFreq(i);
double dFreq = iFreq;
if (iFreq != 0) {
// do some stuff with iFreq...
// do some calculations with dFreq...
}
}
While cleaning up this code during a "performance pass," I decided to move the definition of dFreq inside the if block, as it was only used inside the if. There are several calculations involving dFreq so I didn't eliminate it entirely as it does save the cost of multiple run-time conversions from int to double. I expected no performance difference, or if any at all, a negligible improvement. However, the perfomance decreased by nearly 10%. I have measured this many times, and this is indeed the only change I've made. The code snippet shown above executes inside a couple other loops. I get very consistent timings across runs and can definitely confirm that the change I'm describing decreases performance by ~10%. I would expect performance to increase because the int to double conversion would only occur when iFreq != 0.
Chnaged code:
for (int i = 0; i < ct; ++i) {
// do some stuff...
int iFreq = getFreq(i);
if (iFreq != 0) {
// do some stuff with iFreq...
double dFreq = iFreq;
// do some stuff with dFreq...
}
}
Can anyone explain this? I am using VC++ 9.0 with /O2. I just want to understand what I'm not accounting for here.
You should put the conversion to dFreq immediately inside the if() before doing the calculations with iFreq. The conversion may execute in parallel with the integer calculations if the instruction is farther up in the code. A good compiler might be able to push it farther up, and a not-so-good one may just leave it where it falls. Since you moved it to after the integer calculations it may not get to run in parallel with integer code, leading to a slowdown. If it does run parallel, then there may be little to no improvement at all depending on the CPU (issuing an FP instruction whose result is never used will have little effect in the original version).
If you really want to improve performance, a number of people have done benchmarks and rank the following compilers in this order:
1) ICC - Intel compiler
2) GCC - A good second place
3) MSVC - generated code can be quite poor compared to the others.
You may also want to try -O3 if they have it.
Maybe the result of getFreq is kept inside a register in the first case and written to memory in the second case? It might also be, that the performance decrease has to do with CPU mechanisms as pipelining and/or branch prediction.
You could check the generated assembly code.
This looks to me like a pipeline stall
int iFreq = getFreq(i);
double dFreq = iFreq;
if (iFreq != 0) {
Allows the conversion to double to happen in parallel with other code
since dFreq is not being used immediately. it gives the compiler something
to do between storing iFreq and using it, so this conversion is most likely
"free".
But
int iFreq = getFreq(i);
if (iFreq != 0) {
// do some stuff with iFreq...
double dFreq = iFreq;
// do some stuff with dFreq...
}
Could be hitting a store/reference stall after the conversion to double since you begin using the double value right away.
Modern processors can do multiple things per clock cycle, but only when the things are independent. Two consecutive instructions that reference the same register often result in a stall. The actual conversion to double may take 3 clocks, but all but the first clock can be done in parallel with other work, provided you don't refer to the result of the conversion for an instruction or two.
C++ compilers are getting pretty good at re-ordering instructions to take advantage of this, it looks like your change defeated some nice optimization.
One other (less likely) possibility is that when the conversion to float was before the branch, the compiler was able remove the branch entirely. Branchless code is often a major performance win in modern processors.
It would be interesting to see what instructions the compiler actually emitted for these two cases.
Try moving the definition of dFreq outside of the for loop but keep the assignment inside the for loop/if block.
Perhaps the creation of dFreq on the stack every for loop, inside the if, is causing issue (although the compiler should take care of that). Perhaps a regression in the compiler, if the dFreq var is in the four loop its created once, inside the if inside the for its created every time.
double dFreq;
int iFreq;
for (int i = 0; i < ct; ++i)
{
// do some stuff...
iFreq = getFreq(i);
if (iFreq != 0)
{
// do some stuff with iFreq...
dFreq = iFreq;
// do some stuff with dFreq...
}
}
maybe the compiler is optimizing it taking the definition outside the for loop. when you put it in the if the compiler optimizations aren't doing that.
There's a likelihood that this changed caused your compiler to disable some optimizations. What happens if you move the declarations above the loop?
Once I've read a document about optimization that said that as defining variables just before their usage and not even before was a good practice, the compilers could optimize code following that advice.
This article (a bit old but quite valid) say (with statistics) something similar : http://www.tantalon.com/pete/cppopt/asyougo.htm#PostponeVariableDeclaration
It's easy enough to find out. Just take 20 stackshots of the slow version, and of the fast version. In the slow version you will see on roughly 2 of the shots what it is doing that it is not doing in the fast version. You will see a subtle difference in where it halts in the assembly language.