Atomically clearing lowest non-zero bit of an unsigned integer - c++

Question:
I'm looking for the best way to clear the lowest non-zero bit of a unsigned atomic like std::atomic_uint64_t in a threadsafe fashion without using an extra mutex or the like. In addition, I also need to know, which bit got cleared.
Example:
Lets say, if the current value stored is 0b0110 I want to know that the lowest non-zero bit is bit 1 (0-indexed) and set the variable to 0b0100.
The best version I came up with is this:
#include <atomic>
#include <cstdint>
inline uint64_t with_lowest_non_zero_cleared(std::uint64_t v){
return v-1 & v;
}
inline uint64_t only_keep_lowest_non_zero(std::uint64_t v){
return v & ~with_lowest_non_zero_cleared(v);
}
uint64_t pop_lowest_non_zero(std::atomic_uint64_t& foo)
{
auto expected = foo.load(std::memory_order_relaxed);
while(!foo.compare_exchange_weak(expected,with_lowest_non_zero_cleared(expected), std::memory_order_seq_cst, std::memory_order_relaxed))
{;}
return only_keep_lowest_non_zero(expected);
}
is there a better solution?
Notes:
It doesn't have to be the lowest non-zero bit - I'd also be happy with a solution that clears the highest bit or sets the highest/lowest "zero bit" if that makes a difference
I'd very much prefer a standard c++ (17) version, but would acccept an answer that uses intrinsics for clang and msvc
It should be portable (compiling with clang or msvc for x64 and AArch64), but I'm most interested in the performance on recent intel and AMD x64 architectures when compiled with clang.
EDIT: The update has to be atomic and global progress must be guaranteed, but just as with solution above, it doesn't have to be a wait free algorithm (of course I'd be very happy if you can show me one).

There is no direct hardware support for atomic clear-lowest-bit on x86. BMI1 blsr is only available in memory-source form, not memory-destination form; lock blsr [shared_var] does not exist. (Compilers know how to optimize (var-1) & (var) into blsr for local vars when you compile with -march=haswell or otherwise enable code-gen that assumes BMI1 support.) So even if you can assume BMI1 support1, it doesn't let you do anything fundamentally different.
The best you can do on x86 is the lock cmpxchg retry loop you propose in the question. This is a better option than finding the right bit in an old version of the variable and then using lock btr, especially if it would be a correctness problem to clear the wrong bit if a lower bit was set between the bit-scan and the lock btr. And you'd still need a retry loop in case another thread already cleared the bit you wanted.
CAS retry loops are not bad in practice: retry is quite rare
(Unless your program has very high contention for the shared variable, which would be problematic for performance even with lock add where there's no trying, just hardware arbitration for access to cache lines. If that's the case, you should probably redesign your lockless algorithm and/or consider some kind of OS-assisted sleep/wake instead of having a lot of cores spending a lot of CPU time hammering on the same cache line. Lockless is great in the low-contention case.)
The window for the CPU to lose the cache line between the load to get expected and running lock cmpxchg with the result of a couple instructions on that value is tiny. Usually it will succeed the first time through, because the cache line will still be present in L1d cache when the cmpxchg runs. When the cache line arrives, it will (hopefully) already be in MESI Exclusive state, if the CPU saw far enough ahead to do an RFO for it.
You can instrument your cmpxchg retry loops to see how much contention you actually get in your real program. (e.g. by incrementing a local inside the loop and using an atomic relaxed += into a shared counter once you succeed, or with thread-local counters.)
Remember that your real code (hopefully) does plenty of work between atomic operations on this bitmask, so it's very different from a microbenchmark where all the threads spend all their time hammering on that cache line.
EDIT: The update has to be atomic and global progress must be guaranteed, but just as with solution above, it doesn't have to be a wait free algorithm (of course I'd be very happy if you can show me one).
A CAS retry loop (even when compiled on a LL/SC machine, see below) is lock-free in the technical sense: you only have to retry if some other thread made progress.
CAS leaves the cache line unmodified if it fails. On x86 it dirties the cache line (MESI M state), but x86 cmpxchg doesn't detect ABA, it only compares, so one other thread that loaded the same expected will succeed. On LL/SC machines, hopefully an SC failure on one core doesn't cause surious SC failures on other cores, otherwise it could livelock. That's something you can assume CPU architects thought of.
It's not wait-free because a single thread can in theory have to retry an unbounded number of times.
Your code compiles with gcc8.1 -O3 -march=haswell to this asm (from the Godbolt compiler explorer)
# gcc's code-gen for x86 with BMI1 looks optimal to me. No wasted instructions!
# presumably you'll get something similar when inlining.
pop_lowest_non_zero(std::atomic<unsigned long>&):
mov rax, QWORD PTR [rdi]
.L2:
blsr rdx, rax # Bit Lowest Set Reset
lock cmpxchg QWORD PTR [rdi], rdx
jne .L2 # fall through on success: cmpxchg sets ZF on equal like regular cmp
blsi rax, rax # Bit Lowest Set Isolate
ret
Without BMI1, blsr and blsi become two instructions each. This is close to irrelevant for performance given the cost of a locked instruction.
clang and MSVC unfortunately are slightly more clunky, with a taken branch on the no-contention fast path. (And clang bloats the function by peeling the first iteration. IDK if this helps with branch prediction or something, or if it's purely a missed optimization. We can get clang to generate the fast path with no taken branches using an unlikely() macro. How do the likely/unlikely macros in the Linux kernel work and what is their benefit?).
Footnote 1:
Unless you're building binaries for a known set of machines, you can't assume BMI1 is available anyway. So the compiler will need to do something like lea rdx, [rax-1] / and rdx, rax instead of blsr rdx, rax. This makes a trivial difference for this function; the majority of the cost is the atomic operation even in the uncontended case, even for the hot-in-L1d cache no contention case, looking at the out-of-order execution throughput impact on surrounding code. (e.g. 10 uops for lock cmpxchg on Skylake (http://agner.org/optimize/) vs. saving 1 uop with blsr instead of 2 other instructions. Assuming the front-end is the bottleneck, rather than memory or something else. Being a full memory barrier has an impact on loads/stores in surrounding code, too, but fortunately not on out-of-order execution of independent ALU instructions.)
Non-x86: LL/SC machines
Most non-x86 machines do all their atomic operations with load-linked / store-conditional retry loops. It's a bit unfortunate that C++11 doesn't allow you to create custom LL/SC operations (e.g. with (x-1) & x inside an LL/SC instead of just the add that you'd get from using fetch_add), but CAS machines (like x86) can't give you the ABA detection that LL/SC provides. So it's not clear how you'd design a C++ class that could compile efficiently on x86 but also directly to a LL/SC retry loop on ARM and other LL/SC ISAs. (See this discussion.)
So you just have to write code using compare_exchange_weak if C++ doesn't provide the operation you want (e.g. fetch_or or fetch_and).
What you get in practice from current compilers is a compare_exchange_weak implemented with LL/SC, and your arithmetic operation separate from that. The asm actually does the relaxed load before the exclusive-load-acquire (ldaxr), instead of just basing the computation on the ldaxr result. And there's extra branching to check that expected from the last attempt matches the new load result before attempting the store.
The LL/SC window is maybe shorter than with 2 dependent ALU instructions between the load and store, in case that matters. The CPU has the desired value ready ahead of time, not dependent on the load result. (It depends on the previous load result.) Clang's code-gen puts the sub/and inside the loop, but dependent on the previous iteration's load, so with out of order execution they can still be ready ahead of time.
But if that was really the most efficient way to do things, compilers should be using it for fetch_add as well. They don't because it probably isn't. LL/SC retries are rare, just like CAS retries on x86. I don't know if it could make a different for very-high-contention situations. Maybe, but compilers don't slow down the fast path to optimize for that when compiling fetch_add.
I renamed your functions and re-formatted the while() for readability, because it was already too long for one line without wrapping it with unlikely().
This version compiles to maybe slightly nicer asm than your original, with clang. I also fixed your function names so it actually compiles at all; there's a mismatch in your question. I picked totally different names that are similar to x86's BMI instruction names because they succinctly describe the operation.
#include <atomic>
#include <cstdint>
#ifdef __GNUC__
#define unlikely(expr) __builtin_expect(!!(expr), 0)
#define likely(expr) __builtin_expect(!!(expr), 1)
#else
#define unlikely(expr) (expr)
#define likely(expr) (expr)
#endif
inline uint64_t clear_lowest_set(std::uint64_t v){
return v-1 & v;
}
inline uint64_t isolate_lowest_set(std::uint64_t v){
//return v & ~clear_lowest_set(v);
return (-v) & v;
// MSVC optimizes this better for ARM when used separately.
// The other way (in terms of clear_lowest_set) does still CSE to 2 instructions
// when the clear_lowest_set result is already available
}
uint64_t pop_lowest_non_zero(std::atomic_uint64_t& foo)
{
auto expected = foo.load(std::memory_order_relaxed);
while(unlikely(!foo.compare_exchange_weak(
expected, clear_lowest_set(expected),
std::memory_order_seq_cst, std::memory_order_relaxed)))
{}
return isolate_lowest_set(expected);
}
Clang -O3 for AArch64 (-target aarch64-linux-android -stdlib=libc++ -mcpu=cortex-a57 on Godbolt) makes some weird code. This is from clang6.0, but there is weirdness with older versions, too, creating a 0/1 integer in a register and then testing it instead of just jumping to the right place in the first place.
pop_lowest_non_zero(std::__1::atomic<unsigned long long>&): // #pop_lowest_non_zero(std::__1::atomic<unsigned long long>&)
ldr x9, [x0] # the relaxed load
ldaxr x8, [x0] # the CAS load (a=acquire, x=exclusive: pairs with a later stxr)
cmp x8, x9 # compare part of the CAS
b.ne .LBB0_3
sub x10, x9, #1
and x10, x10, x9 # clear_lowest( relaxed load result)
stlxr w11, x10, [x0] # the CAS store (sequential-release)
cbnz w11, .LBB0_4 # if(SC failed) goto retry loop
# else fall through and eventually reach the epilogue
# this looks insane. w10 = 0|1, then branch if bit[0] != 0. Always taken, right?
orr w10, wzr, #0x1
tbnz w10, #0, .LBB0_5 # test-bit not-zero will always jump to the epilogue
b .LBB0_6 # never reached
.LBB0_3:
clrex # clear the ldrx/stxr transaction
.LBB0_4:
# This block is pointless; just should b to .LBB0_6
mov w10, wzr
tbz w10, #0, .LBB0_6 # go to the retry loop, below the ret (not shown here)
.LBB0_5: # isolate_lowest_set and return
neg x8, x9
and x0, x9, x8
ret
.LBB0_6:
# the retry loop. Only reached if the compare or SC failed.
...
All this crazy branching might not be a real performance problem, but it's obvious this could be a lot more efficient (even without teaching clang how to use LL/SC directly instead of emulated CAS). Reported as clang/LLVM bug 38173
It seems MSVC doesn't know that AArch64's release-stores already have sequentially-consistent semantics wrt. ldar / ldaxr loads (not just regular release like x86): it's still using a dmb ish instruction (full memory barrier) after stlxr. It has fewer wasted instructions, but its x86 bias is showing or something: compare_exchange_weak compiles like compare_exchange_strong with a probably-useless retry loop that will try just the CAS again with the old expected/desired, on LL/SC failure. That will usually be because another thread modified the line, so expected will mismatch. (Godbolt doesn't have MSVC for AArch64 in any older versions, so perhaps support is brand new. That might explain the dmb)
## MSVC Pre 2018 -Ox
|pop_lowest_non_zero| PROC
ldr x10,[x0] # x10 = expected = foo.load(relaxed)
|$LL2#pop_lowest| # L2 # top of the while() loop
sub x8,x10,#1
and x11,x8,x10 # clear_lowest(relaxed load result)
|$LN76#pop_lowest| # LN76
ldaxr x8,[x0]
cmp x8,x10 # the compare part of CAS
bne |$LN77#pop_lowest|
stlxr w9,x11,[x0]
cbnz w9,|$LN76#pop_lowest| # retry just the CAS on LL/SC fail; this looks like compare_exchange_strong
# fall through on LL/SC success
|$LN77#pop_lowest| # LN77
dmb ish # full memory barrier: slow
cmp x8,x10 # compare again, because apparently MSVC wants to share the `dmb` instruction between the CAS-fail and CAS-success paths.
beq |$LN75#pop_lowest| # if(expected matches) goto epilogue
mov x10,x8 # else update expected
b |$LL2#pop_lowest| # and goto the top of the while loop
|$LN75#pop_lowest| # LN75 # function epilogue
neg x8,x10
and x0,x8,x10
ret
gcc6.3 for AArch64 makes weird code, too, storing expected to the stack. (Godbolt doesn't have newer AArch64 gcc).
Hand-written AArch64 version that sucks less
I'm very unimpressed with AArch64 compilers for this! IDK why they don't generate something clean and efficient like this, with no taken branches on the fast path, and only a bit of out-of-line code to set up for jumping back into the CAS to retry.
pop_lowest_non_zero ## hand written based on clang
# clang could emit this even without turning CAS into LL/SC directly
ldr x9, [x0] # x9 = expected = foo.load(relaxed)
.Lcas_retry:
ldaxr x8, [x0] # x8 = the CAS load (a=acquire, x=exclusive: pairs with a later stxr)
cmp x8, x9 # compare part of the CAS
b.ne .Lcas_fail
sub x10, x9, #1
and x10, x10, x9 # clear_lowest (relaxed load result)
stlxr w11, x10, [x0] # the CAS store (sequential-release)
cbnz w11, .Lllsc_fail
# LL/SC success: isolate_lowest_set and return
.Lepilogue:
neg x8, x9
and x0, x9, x8
ret
.Lcas_fail:
// clrex # We're about to start another ldaxr making clrex unnecessary
.Lllsc_fail:
mov x9, x8 # update expected
b .Lcas_retry # instead of duplicating the loop, jump back to the existing one with x9 = expected
Compare with .fetch_add:
Clang does make nice code for fetch_add():
mov x8, x0
.LBB1_1:
ldxr x0, [x8] # relaxed exclusive load: I used mo_release
add x9, x0, #1
stlxr w10, x9, [x8]
cbnz w10, .LBB1_1 # retry if LL/SC failed
ret
Instead of add #1, we'd like to have sub x9, x8, #1 / and x9, x9, x8, so we just get a LL/SC retry loop. This saves code-size, but it won't be significantly faster. Probably not even measurably faster in most cases, especially as part of a whole program where it's not used an insane amount.
Alternatives: Do you even need exactly this bitmap operation? Can you break it up to reduce contention?
Can you use an atomic counter instead of a bitmap, and map it to a bitmap when needed? Operations that want a bitmap can map the counter to a bitmap with uint64_t(~0ULL) << (64-counter) (for non-zero counter only). Or maybe tmp=1ULL << counter; tmp ^= tmp-1; (i.e. x86 xor eax,eax / bts rax, rdi (rax=1 set bit at position 0..63) / blsmsk rax, rax (rax=all bits set up to that position). Hmm, that still needs a special case for mask=0, because there are 65 possible states for a contiguous bitmask: highest (or lowest) bit at one of 64 positions, or no bits set at all.
Or if there's some pattern to the bitmap, x86 BMI2 pdep can scatter contiguous bits into that pattern. Get N contiguous set bits with (1ULL << counter) - 1, again for counter < 64.
Or maybe it has to be a bitmask, but doesn't need to be one single bitmask?
No idea what your use-case is, but this kind of idea might be useful:
Do you need a single atomic bitmap that all threads have to contend for? Perhaps you could break it into multiple chunks, each in a separate cache line. (But that makes it impossible to atomically snapshot the entire map.) Still, if each thread has a preferred chunk, and always tries that before moving on to look for a slot in another chunk, you might reduce contention in the average case.
In asm (or with horrible union hacks in C++), you could try to reduce cmpxchg failures without reducing contention by finding the right byte of the 64-bit integer to update, and then only lock cmpxchg on it. That's not actually helpful for this case because two threads that see the same integer will both try to clear the same bit. But it could reduce retries between this and something that sets other bits in the qword. Of course this only works if it's not a correctness problem for lock cmpxchg to succeed when other bytes of the qword have changed.

So basically the question is, do I do better to loop on compare_exchange_weak until I find / get what I want or should I just use a mutex? OK, at least I understand the question now so let's explore that a little bit.
So, everyone out there is probably screaming which is faster, which is faster? Well, I personally couldn't care much, unless it proves to be a problem in practise, but if you care then you should benchmark it. You can get a first order approximation over at the most excellent Wandbox.
But there's another, more subtle issue: locking. The first solution is lockless, but there's a busy loop. The second takes a lock, which can have side-effects.
The busy loop is probably pretty harmless. It only soaks up one core and it is unlikely to run for long but one would want to profile the code when running under real-world conditions if one suspected otherwise.
The lock, on the other hand, might not be so harmless because it can cause priority inversion, which can result in a lower priority thread pre-empting a higher priority one. This can be an issue in any application which runs cooperating threads at different priorities but it is particularly so for me because I write realtime audio code. It bit me on the Mac, that's how I know all this.
So, I hope that tells you some at least of what you wanted to know. With your rep, I should not be trying to tell you how to 'write the codez'.
Reference: https://en.m.wikipedia.org/wiki/Priority_inversion

Related

Why is ONE basic arithmetic operation in for loop body executed SLOWER THAN TWO arithmetic operations?

While I experimented with measuring time of execution of arithmetic operations, I came across very strange behavior. A code block containing a for loop with one arithmetic operation in the loop body was always executed slower than an identical code block, but with two arithmetic operations in the for loop body. Here is the code I ended up testing:
#include <iostream>
#include <chrono>
#define NUM_ITERATIONS 100000000
int main()
{
// Block 1: one operation in loop body
{
int64_t x = 0, y = 0;
auto start = std::chrono::high_resolution_clock::now();
for (long i = 0; i < NUM_ITERATIONS; i++) {x+=31;}
auto end = std::chrono::high_resolution_clock::now();
std::chrono::duration<double> diff = end-start;
std::cout << diff.count() << " seconds. x,y = " << x << "," << y << std::endl;
}
// Block 2: two operations in loop body
{
int64_t x = 0, y = 0;
auto start = std::chrono::high_resolution_clock::now();
for (long i = 0; i < NUM_ITERATIONS; i++) {x+=17; y-=37;}
auto end = std::chrono::high_resolution_clock::now();
std::chrono::duration<double> diff = end-start;
std::cout << diff.count() << " seconds. x,y = " << x << "," << y << std::endl;
}
return 0;
}
I tested this with different levels of code optimization (-O0,-O1,-O2,-O3), with different online compilers (for example onlinegdb.com), on my work machine, on my hame PC and laptop, on RaspberryPi and on my colleague's computer. I rearranged these two code blocks, repeated them, changed constants, changed operations (+, -, <<, =, etc.), changed integer types. But I always got similar result: the block with one line in loop is SLOWER than block with two lines:
1.05681 seconds. x,y = 3100000000,0
0.90414 seconds. x,y = 1700000000,-3700000000
I checked the assembly output on https://godbolt.org/ but everything looked like I expected: second block just had one more operation in assembly output.
Three operations always behaved as expected: they are slower than one and faster than four. So why two operations produce such an anomaly?
Edit:
Let me repeat: I have such behaviour on all of my Windows and Unix machines with code not optimized. I looked at assembly I execute (Visual Studio, Windows) and I see the instructions I want to test there. Anyway if the loop is optimized away, there is nothing I ask about in the code which left. I added that optimizations notice in the question to avoid "do not measure not optimized code" answers because optimizations is not what I ask about. The question is actually why my computers execute two operations faster than one, first of all in code where these operations are not optimized away. The difference in time of execution is 5-25% on my tests (quite noticeable).
This effect only happens at -O0 (or with volatile), and is a result of the compiler keeping your variables in memory (not registers). You'd expect that to just introduce a fixed amount of extra latency into a loop-carried dependency chains through i, x, and y, but modern CPUs are not that simple.
On Intel Sandybridge-family CPUs, store-forwarding latency is lower when the load uop runs some time after the store whose data it's reloading, not right away. So an empty loop with the loop counter in memory is the worst case. I don't understand what CPU design choices could lead to that micro-architectural quirk, but it's a real thing.
This is basically a duplicate of Adding a redundant assignment speeds up code when compiled without optimization, at least for Intel Sandybridge-family CPUs.
This is is one of the major reasons why you shouldn't benchmark at -O0: the bottlenecks are different than in realistically optimized code. See Why does clang produce inefficient asm with -O0 (for this simple floating point sum)? for more about why compilers make such terrible asm on purpose.
Micro-benchmarking is hard; you can only measure something properly if you can get compilers to emit realistically optimized asm loops for the thing you're trying to measure. (And even then you're only measuring throughput or latency, not both; those are separate things for single operations on out-of-order pipelined CPUs: What considerations go into predicting latency for operations on modern superscalar processors and how can I calculate them by hand?)
See #rcgldr's answer for measurement + explanation of what would happen with loops that keep variables in registers.
With clang, benchmark::DoNotOptimize(x1 += 31) also de-optimizes into keeping x in memory, but with GCC it does just stay in a register. Unfortunately #SashaKnorre's answer used clang on QuickBench, not gcc, to get results similar to your -O0 asm. It does show the cost of lots of short-NOPs being hidden by the bottleneck through memory, and a slight speedup when those NOPs delay the reload next iteration just long enough for store-forwarding to hit the lower latency good case. (QuickBench I think runs on Intel Xeon server CPUs, with the same microarchitecture inside each CPU core as desktop version of the same generation.)
Presumably all the x86 machines you tested on had Intel CPUs from the last 10 years, or else there's a similar effect on AMD. It's plausible there's a similar effect on whichever ARM CPU your RPi uses, if your measurements really were meaningful there. Otherwise, maybe another case of seeing what you expected (confirmation bias), especially if you tested with optimization enabled there.
I tested this with different levels of code optimization (-O0,-O1,-O2,-O3) [...] But I always got similar result
I added that optimizations notice in the question to avoid "do not measure not optimized code" answers because optimizations is not what I ask about.
(later from comments) About optimizations: yes, I reproduced that with different optimization levels, but as the loops were optimized away, the execution time was too fast to say for sure.
So actually you didn't reproduce this effect for -O1 or higher, you just saw what you wanted to see (confirmation bias) and mostly made up the claim that the effect was the same. If you'd accurately reported your data (measurable effect at -O0, empty timed region at -O1 and higher), I could have answered right away.
See Idiomatic way of performance evaluation? - if your times don't increase linearly with increasing repeat count, you aren't measuring what you think you're measuring. Also, startup effects (like cold caches, soft page faults, lazy dynamic linking, and dynamic CPU frequency) can easily lead to the first empty timed region being slower than the second.
I assume you only swapped the loops around when testing at -O0, otherwise you would have ruled out there being any effect at -O1 or higher with that test code.
The loop with optimization enabled:
As you can see on Godbolt, gcc fully removes the loop with optimization enabled. Sometimes GCC leaves empty loops alone, like maybe it thinks the delay was intentional, but here it doesn't even loop at all. Time doesn't scale with anything, and both timed regions look the same like this:
orig_main:
...
call std::chrono::_V2::system_clock::now() # demangled C++ symbol name
mov rbp, rax # save the return value = start
call std::chrono::_V2::system_clock::now()
# end in RAX
So the only instruction in the timed region is saving start to a call-preserved register. You're measuring literally nothing about your source code.
With Google Benchmark, we can get asm that doesn't optimize the work away, but which doesn't store/reload to introduce new bottlenecks:
#include <benchmark/benchmark.h>
static void TargetFunc(benchmark::State& state) {
uint64_t x2 = 0, y2 = 0;
// Code inside this loop is measured repeatedly
for (auto _ : state) {
benchmark::DoNotOptimize(x2 += 31);
benchmark::DoNotOptimize(y2 += 31);
}
}
// Register the function as a benchmark
BENCHMARK(TargetFunc);
# just the main loop, from gcc10.1 -O3
.L7: # do{
add rax, 31 # x2 += 31
add rdx, 31 # y2 += 31
sub rbx, 1
jne .L7 # }while(--count != 0)
I assume benchmark::DoNotOptimize is something like asm volatile("" : "+rm"(x) ) (GNU C inline asm) to make the compiler materialize x in a register or memory, and to assume the lvalue has been modified by that empty asm statement. (i.e. forget anything it knew about the value, blocking constant-propagation, CSE, and whatever.) That would explain why clang stores/reloads to memory while GCC picks a register: this is a longstanding missed-optimization bug with clang's inline asm support. It likes to pick memory when given the choice, which you can sometimes work around with multi-alternative constraints like "+r,m". But not here; I had to just drop the memory alternative; we don't want the compiler to spill/reload to memory anyway.
For GNU C compatible compilers, we can use asm volatile manually with only "+r" register constraints to get clang to make good scalar asm (Godbolt), like GCC. We get an essentially identical inner loop, with 3 add instructions, the last one being an add rbx, -1 / jnz that can macro-fuse.
static void TargetFunc(benchmark::State& state) {
uint64_t x2 = 0, y2 = 0;
// Code inside this loop is measured repeatedly
for (auto _ : state) {
x2 += 16;
y2 += 17;
asm volatile("" : "+r"(x2), "+r"(y2));
}
}
All of these should run at 1 clock cycle per iteration on modern Intel and AMD CPUs, again see #rcgldr's answer.
Of course this also disables auto-vectorization with SIMD, which compilers would do in many real use cases. Or if you used the result at all outside the loop, it might optimize the repeated increment into a single multiply.
You can't measure the cost of the + operator in C++ - it can compile very differently depending on context / surrounding code. Even without considering loop-invariant stuff that hoists work. e.g. x + (y<<2) + 4 can compile to a single LEA instruction for x86.
The question is actually why my computers execute two operations faster than one, first of all in code where these operations are not optimized away
TL:DR: it's not the operations, it's the loop-carried dependency chain through memory that stops the CPU from running the loop at 1 clock cycle per iteration, doing all 3 adds in parallel on separate execution ports.
Note that the loop counter increment is just as much of an operation as what you're doing with x (and sometimes y).
ETA: This was a guess, and Peter Cordes has made a very good argument about why it's incorrect. Go upvote Peter's answer.
I'm leaving my answer here because some found the information useful. Though this doesn't correctly explain the behavior seen in the OP, it highlights some of the issues that make it infeasible (and meaningless) to try to measure the speed of a particular instruction on a modern processor.
Educated guess:
It's the combined effect of pipelining, powering down portions of a core, and dynamic frequency scaling.
Modern processors pipeline so that multiple instructions can be executing at the same time. This is possible because the processor actually works on micro-ops rather than the assembly-level instructions we usually think of as machine language. Processors "schedule" micro-ops by dispatching them to different portions of the chip while keeping track of the dependencies between the instructions.
Suppose the core running your code has two arithmetic/logic units (ALUs). A single arithmetic instruction repeated over and over requires only one ALU. Using two ALUs doesn't help because the next operation depends on completion of the current one, so the second ALU would just be waiting around.
But in your two-expression test, the expressions are independent. To compute the next value of y, you do not have to wait for the current operation on x to complete. Now, because of power-saving features, that second ALU may be powered down at first. The core might run a few iterations before realizing that it could make use of the second ALU. At that point, it can power up the second ALU and most of the two-expression loop will run as fast as the one-expression loop. So you might expect the two examples to take approximately the same amount of time.
Finally, many modern processors use dynamic frequency scaling. When the processor detects that it's not running hard, it actually slows its clock a little bit to save power. But when it's used heavily (and the current temperature of the chip permits), it might increase the actual clock speed as high as its rated speed.
I assume this is done with heuristics. In the case where the second ALU stays powered down, the heuristic may decide it's not worth boosting the clock. In the case where two ALUs are powered up and running at top speed, it may decide to boost the clock. Thus the two-expression case, which should already be just about as fast as the one-expression case, actually runs at a higher average clock frequency, enabling it to complete twice as much work in slightly less time.
Given your numbers, the difference is about 14%. My Windows machine idles at about 3.75 GHz, and if I push it a little by building a solution in Visual Studio, the clock climbs to about 4.25GHz (eyeballing the Performance tab in Task Manager). That's a 13% difference in clock speed, so we're in the right ballpark.
I split up the code into C++ and assembly. I just wanted to test the loops, so I didn't return the sum(s). I'm running on Windows, the calling convention is rcx, rdx, r8, r9, the loop count is in rcx. The code is adding immediate values to 64 bit integers on the stack.
I'm getting similar times for both loops, less than 1% variation, same or either one up to 1% faster than the other.
There is an apparent dependency factor here: each add to memory has to wait for the prior add to memory to the same location to complete, so two add to memories can be performed essentially in parallel.
Changing test2 to do 3 add to memories, ends up about 6% slower, 4 add to memories, 7.5% slower.
My system is Intel 3770K 3.5 GHz CPU, Intel DP67BG motherboard, DDR3 1600 9-9-9-27 memory, Win 7 Pro 64 bit, Visual Studio 2015.
.code
public test1
align 16
test1 proc
sub rsp,16
mov qword ptr[rsp+0],0
mov qword ptr[rsp+8],0
tst10: add qword ptr[rsp+8],17
dec rcx
jnz tst10
add rsp,16
ret
test1 endp
public test2
align 16
test2 proc
sub rsp,16
mov qword ptr[rsp+0],0
mov qword ptr[rsp+8],0
tst20: add qword ptr[rsp+0],17
add qword ptr[rsp+8],-37
dec rcx
jnz tst20
add rsp,16
ret
test2 endp
end
I also tested with add immediate to register, 1 or 2 registers within 1% (either could be faster, but we'd expect them both to execute at 1 iteration / clock on Ivy Bridge, given its 3 integer ALU ports; What considerations go into predicting latency for operations on modern superscalar processors and how can I calculate them by hand?).
3 registers 1.5 times as long, somewhat worse than the ideal 1.333 cycles / iterations from 4 uops (including the loop counter macro-fused dec/jnz) for 3 back-end ALU ports with perfect scheduling.
4 registers, 2.0 times as long, bottlenecked on the front-end: Is performance reduced when executing loops whose uop count is not a multiple of processor width?. Haswell and later microarchitectures would handle this better.
.code
public test1
align 16
test1 proc
xor rdx,rdx
xor r8,r8
xor r9,r9
xor r10,r10
xor r11,r11
tst10: add rdx,17
dec rcx
jnz tst10
ret
test1 endp
public test2
align 16
test2 proc
xor rdx,rdx
xor r8,r8
xor r9,r9
xor r10,r10
xor r11,r11
tst20: add rdx,17
add r8,-37
dec rcx
jnz tst20
ret
test2 endp
public test3
align 16
test3 proc
xor rdx,rdx
xor r8,r8
xor r9,r9
xor r10,r10
xor r11,r11
tst30: add rdx,17
add r8,-37
add r9,47
dec rcx
jnz tst30
ret
test3 endp
public test4
align 16
test4 proc
xor rdx,rdx
xor r8,r8
xor r9,r9
xor r10,r10
xor r11,r11
tst40: add rdx,17
add r8,-37
add r9,47
add r10,-17
dec rcx
jnz tst40
ret
test4 endp
end
#PeterCordes proved this answer to be wrong in many assumptions, but it could still be useful as some blind research attempt of the problem.
I set up some quick benchmarks, thinking it may somehow be connected to code memory alignment, truly a crazy thought.
But it seems that #Adrian McCarthy got it right with the dynamic frequency scaling.
Anyway benchmarks tell that inserting some NOPs could help with the issue, with 15 NOPs after the x+=31 in Block 1 leading to nearly the same performance as the Block 2. Truly mind blowing how 15 NOPs in single instruction loop body increase performance.
http://quick-bench.com/Q_7HY838oK5LEPFt-tfie0wy4uA
I also tried -OFast thinking compilers might be smart enough to throw away some code memory inserting such NOPs, but it seems not to be the case.
http://quick-bench.com/so2CnM_kZj2QEWJmNO2mtDP9ZX0
Edit: Thanks to #PeterCordes it was made clear that optimizations were never working quite as expected in benchmarks above (as global variable required add instructions to access memory), new benchmark http://quick-bench.com/HmmwsLmotRiW9xkNWDjlOxOTShE clearly shows that Block 1 and Block 2 performance is equal for stack variables. But NOPs could still help with single-threaded application with loop accessing global variable, which you probably should not use in that case and just assign global variable to local variable after the loop.
Edit 2: Actually optimizations never worked due to quick-benchmark macros making variable access volatile, preventing important optimizations. It is only logical to load the variable once as we are only modifying it in the loop, so it is volatile or disabled optimizations being the bottleneck. So this answer is basically wrong, but at least it shows how NOPs could speed-up unoptimized code execution, if it makes any sense in the real world (there are better ways like bucketing counters).
Processors are so complex these days that we can only guess.
The assembly emitted by your compiler is not what is really executed. The microcode/firmware/whatever of your CPU will interpret it and turn it into instructions for its execution engine, much like JIT languages such as C# or java do.
One thing to consider here is that for each loop, there is not 1 or 2 instructions, but n + 2, as you also increment and compare i to your number of iteration. In the vast majority of case it wouldn't matter, but here it does, as the loop body is so simple.
Let's see the assembly :
Some defines:
#define NUM_ITERATIONS 1000000000ll
#define X_INC 17
#define Y_INC -31
C/C++ :
for (long i = 0; i < NUM_ITERATIONS; i++) { x+=X_INC; }
ASM :
mov QWORD PTR [rbp-32], 0
.L13:
cmp QWORD PTR [rbp-32], 999999999
jg .L12
add QWORD PTR [rbp-24], 17
add QWORD PTR [rbp-32], 1
jmp .L13
.L12:
C/C++ :
for (long i = 0; i < NUM_ITERATIONS; i++) {x+=X_INC; y+=Y_INC;}
ASM:
mov QWORD PTR [rbp-80], 0
.L21:
cmp QWORD PTR [rbp-80], 999999999
jg .L20
add QWORD PTR [rbp-64], 17
sub QWORD PTR [rbp-72], 31
add QWORD PTR [rbp-80], 1
jmp .L21
.L20:
So both Assemblies look pretty similar. But then let's think twice : modern CPUs have ALUs which operate on values which are wider than their register size. So there is a chance than in the first case, the operation on x and i are done on the same computing unit. But then you have to read i again, as you put a condition on the result of this operation. And reading means waiting.
So, in the first case, to iterate on x, the CPU might have to be in sync with the iteration on i.
In the second case, maybe x and y are treated on a different unit than the one dealing with i. So in fact, your loop body runs in parallel than the condition driving it. And there goes your CPU computing and computing until someone tells it to stop. It doesn't matter if it goes too far, going back a few loops is still fine compared to the amount of time it just gained.
So, to compare what we want to compare (one operation vs two operations), we should try to get i out of the way.
One solution is to completely get rid of it by using a while loop:
C/C++:
while (x < (X_INC * NUM_ITERATIONS)) { x+=X_INC; }
ASM:
.L15:
movabs rax, 16999999999
cmp QWORD PTR [rbp-40], rax
jg .L14
add QWORD PTR [rbp-40], 17
jmp .L15
.L14:
An other one is to use the antequated "register" C keyword:
C/C++:
register long i;
for (i = 0; i < NUM_ITERATIONS; i++) { x+=X_INC; }
ASM:
mov ebx, 0
.L17:
cmp rbx, 999999999
jg .L16
add QWORD PTR [rbp-48], 17
add rbx, 1
jmp .L17
.L16:
Here are my results:
x1 for: 10.2985 seconds. x,y = 17000000000,0
x1 while: 8.00049 seconds. x,y = 17000000000,0
x1 register-for: 7.31426 seconds. x,y = 17000000000,0
x2 for: 9.30073 seconds. x,y = 17000000000,-31000000000
x2 while: 8.88801 seconds. x,y = 17000000000,-31000000000
x2 register-for :8.70302 seconds. x,y = 17000000000,-31000000000
Code is here: https://onlinegdb.com/S1lAANEhI

C/С++. Why could a simple integer addition on a volatile be translated to a different asm instruction on gcc and clang?

I wrote a simple loop:
int volatile value = 0;
void loop(int limit) {
for (int i = 0; i < limit; ++i) {
++value;
}
}
I compiled this with gcc and clang(-O3 -fno-unroll-loops) and got different outputs. They differ in ++value part:
clang:
add dword ptr [rip + value], 1 # ++value
add edi, -1 # --limit
jne .LBB0_1 # if limit > 0 then continue looping
gcc:
mov eax, DWORD PTR value[rip] # copy value to a register
add edx, 1 # ++i
add eax, 1 # increment a copy of value
mov DWORD PTR value[rip], eax # store incremented copy to value, i. e. ++value
cmp edi, edx # compare i < limit
jne .L3 # if i < limit then continue looping
C and C++ versions are same on each compiler(https://gcc.godbolt.org/z/5x5jGP)
So my questions are:
1) Is gcc doing something wrong? What is the point of copying the value?
2) I have benchmarked that code and for some reason the profiler shows that in gcc's version 73% of time is wasted on instruction add edx, 1, 13% on mov DWORD PTR value[rip], eax and 13% on cmp edi, edx. Am I interpreting this results wrong? Why other addition and move instructions take less than 1% of the time?
3) Why can performance differ on gcc/clang in such a primitive code?
This is all because you used volatile and GCC doesn't optimize it as aggressively
Without volatile, e.g. for a single ++*int_ptr, you get a memory-destination add. (And hopefully not inc when tuning for Intel CPUs; inc reg is fine but inc mem costs an extra uop vs. add 1. Unfortunately gcc and clang both get this wrong and use inc mem with -march=skylake: https://godbolt.org/z/_1Ri20)
clang knows that it can fold the volatile read / write accesses into the load and store portions of a memory-destination add.
GCC does not know how to do this optimization for volatile. Using volatile in GCC typically results in separate mov loads and stores, avoiding x86's ability to save code-size by using CISC memory operands for ALU instructions. On a load/store machine (like any RISC) you'd need separate load and store instructions anyway so it would be non-issue.
TL:DR: different compiler internals around volatile, specifically a GCC missed-optimization.
This missed optimization barely matter because volatile is rarely used. But feel free to report it on GCC's bugzilla if you want.
Without volatile, the loop would of course optimize away. But you can see a single memory-destination add from GCC or clang for a function that just does ++*p.
1) Is gcc doing something wrong? What is the point of copying the value?
It's only copying it to a register. We don't normally call this "copying", just bringing it into a register where it can operate on it.
Note that gcc and clang also differ in how they implement the loop condition, with clang optimizing to just dec/jnz (actually add -1, but it would use dec with -march=skylake or something with efficient dec, i.e. not Silvermont).
GCC spends an extra uop on the loop condition (on Intel CPUs where add/jnz can macro-fuse into a single uop). IDK why it compiles it naively like that.
73% of time is wasted on instruction add edx, 1
perf counters typically blame the instruction that's waiting for a slow result, not the instruction that's actually slow to produce it.
add edx,1 is waiting for the reload of value. With 4 to 5 cycle store-forwarding latency, this is the major bottleneck in your loop.
(Whether it's between the multiple uops of a memory-destination add or between separate instructions makes essentially no difference. There are no other memory accesses in your loop so none of the weird effects of store-forwarding latency being lower if you don't try too soon come into play:
Adding a redundant assignment speeds up code when compiled without optimization or Loop with function call faster than an empty loop )
Why other addition and move instructions take less than 1% of the time?
Because out-of-order execution hides them under the latency of the critical path. They are very rarely the instruction that gets blamed when statistical sampling has to pick one out of the many that are in flight at once in any given cycle.
3) Why can performance differ on gcc/clang in such a primitive code?
I'd expect both those loops run at the same speed. Did you just mean performance as in how well the compilers themselves performed in making code that's both fast and compact?

Does any of current C++ compilers ever emit "rep movsb/w/d"?

This question made me wonder, if current modern compilers ever emit REP MOVSB/W/D instruction.
Based on this discussion, it seems that using REP MOVSB/W/D could be beneficial on current CPUs.
But no matter how I tried, I cannot made any of the current compilers (GCC 8, Clang 7, MSVC 2017 and ICC 18) to emit this instruction.
For this simple code, it could be reasonable to emit REP MOVSB:
void fn(char *dst, const char *src, int l) {
for (int i=0; i<l; i++) {
dst[i] = src[i];
}
}
But compilers emit a non-optimized simple byte-copy loop, or a huge unrolled loop (basically an inlined memmove). Do any of the compilers use this instruction?
GCC has x86 tuning options to control string-ops strategy and when to inline vs. library call. (See https://gcc.gnu.org/onlinedocs/gcc/x86-Options.html). -mmemcpy-strategy=strategy
takes alg:max_size:dest_align triplets, but the brute-force way is -mstringop-strategy=rep_byte
I had to use __restrict to get gcc to recognize the memcpy pattern, instead of just doing normal auto-vectorization after an overlap check / fallback to a dumb byte loop. (Fun fact: gcc -O3 auto-vectorizes even with -mno-sse, using the full width of an integer register. So you only get a dumb byte loop if you compile with -Os (optimize for size) or -O2 (less than full optimization)).
Note that if src and dst overlap with dst > src, the result is not memmove. Instead, you'll get a repeating pattern with length = dst-src. rep movsb has to correctly implement the exact byte-copy semantics even in case of overlap, so it would still be valid (but slow on current CPUs: I think microcode would just fall back to a byte loop).
gcc only gets to rep movsb via recognizing a memcpy pattern and then choosing to inline memcpy as rep movsb. It doesn't go directly from byte-copy loop to rep movsb, and that's why possible aliasing defeats the optimization. (It might be interesting for -Os to consider using rep movs directly, though, when alias analysis can't prove it's a memcpy or memmove, on CPUs with fast rep movsb.)
void fn(char *__restrict dst, const char *__restrict src, int l) {
for (int i=0; i<l; i++) {
dst[i] = src[i];
}
}
This probably shouldn't "count" because I would probably not recommend those tuning options for any use-case other than "make the compiler use rep movs", so it's not that different from an intrinsic. I didn't check all the -mtune=silvermont / -mtune=skylake / -mtune=bdver2 (Bulldozer version 2 = Piledriver) / etc. tuning options, but I doubt any of them enable that. So this is an unrealistic test because nobody using -march=native would get this code-gen.
But the above C compiles with gcc8.1 -xc -O3 -Wall -mstringop-strategy=rep_byte -minline-all-stringops on the Godbolt compiler explorer to this asm for x86-64 System V:
fn:
test edx, edx
jle .L1 # rep movs treats the counter as unsigned, but the source uses signed
sub edx, 1 # what the heck, gcc? mov ecx,edx would be too easy?
lea ecx, [rdx+1]
rep movsb # dst=rdi and src=rsi
.L1: # matching the calling convention
ret
Fun fact: the x86-64 SysV calling convention being optimized for inlining rep movs is not a coincidence (Why does Windows64 use a different calling convention from all other OSes on x86-64?). I think gcc favoured that when the calling convention was being designed, so it saved instructions.
rep_8byte does a bunch of setup to handle counts that aren't a multiple of 8, and maybe alignment, I didn't look carefully.
I also didn't check other compilers.
Inlining rep movsb would be a poor choice without an alignment guarantee, so it's good that compilers don't do it by default. (As long as they do something better.) Intel's optimization manual has a section on memcpy and memset with SIMD vectors vs. rep movs. See also http://agner.org/optimize/, and other performance links in the x86 tag wiki.
(I doubt that gcc would do anything differently if you did dst=__builtin_assume_aligned(dst, 64); or any other way of communicating alignment to the compiler, though. e.g. alignas(64) on some arrays.)
Intel's IceLake microarchitecture will have a "short rep" feature that presumably reduces startup overhead for rep movs / rep stos, making them much more useful for small counts. (Currently rep string microcode has significant startup overhead: What setup does REP do?)
memmove / memcpy strategies:
BTW, glibc's memcpy uses a pretty nice strategy for small inputs that's insensitive to overlap: Two loads -> two stores that potentially overlap, for copies up to 2 registers wide. This means any input from 4..7 bytes branches the same way, for example.
Glibc's asm source has a nice comment describing the strategy: https://code.woboq.org/userspace/glibc/sysdeps/x86_64/multiarch/memmove-vec-unaligned-erms.S.html#19.
For large inputs, it uses SSE XMM registers, AVX YMM registers, or rep movsb (after checking an internal config variable that's set based on CPU-detection when glibc initializes itself). I'm not sure which CPUs it will actually use rep movsb on, if any, but support is there for using it for large copies.
rep movsb might well be a pretty reasonable choice for small code-size and non-terrible scaling with count for a byte loop like this, with safe handling for the unlikely case of overlap.
Microcode startup overhead is a big problem with using it for copies that are usually small, though, on current CPUs.
It's probably better than a byte loop if the average copy size is maybe 8 to 16 bytes on current CPUs, and/or different counts cause branch mispredicts a lot. It's not good, but it's less bad.
Some kind of last-ditch peephole optimization for turning a byte-loop into a rep movsb might be a good idea, if compiling without auto-vectorization. (Or for compilers like MSVC that make a byte loop even at full optimization.)
It would be neat if compilers knew about it more directly, and considered using it for -Os (optimize for code-size more than speed) when tuning for CPUs with the Enhanced Rep Movs/Stos Byte (ERMSB) feature. (See also Enhanced REP MOVSB for memcpy for lots of good stuff about x86 memory bandwidth single threaded vs. all cores, NT stores that avoid RFO, and rep movs using an RFO-avoiding cache protocol...).
On older CPUs, rep movsb wasn't as good for large copies, so the recommended strategy was rep movsd or movsq with special handling for the last few counts. (Assuming you're going to use rep movs at all, e.g. in kernel code where you can't touch SIMD vector registers.)
The -mno-sse auto-vectorization using integer registers is much worse than rep movs for medium sized copies that are hot in L1d or L2 cache, so gcc should definitely use rep movsb or rep movsq after checking for overlap, not a qword copy loop, unless it expects small inputs (like 64 bytes) to be common.
The only advantage of a byte loop is small code size; it's pretty much the bottom of the barrel; a smart strategy like glibc's would be much better for small but unknown copy sizes. But that's too much code to inline, and a function call does have some cost (spilling call-clobbered registers and clobbering the red zone, plus the actual cost of the call / ret instructions and dynamic linking indirection).
Especially in a "cold" function that doesn't run often (so you don't want to spend a lot of code size on it, increasing your program's I-cache footprint, TLB locality, pages to be loaded from disk, etc). If writing asm by hand, you'd usually know more about the expected size distribution and be able to inline a fast-path with a fallback to something else.
Remember that compilers will make their decisions on potentially many loops in one program, and most code in most programs is outside of hot loops. It shouldn't bloat them all. This is why gcc defaults to -fno-unroll-loops unless profile-guided optimization is enabled. (Auto-vectorization is enabled at -O3, though, and can create a huge amount of code for some small loops like this one. It's quite silly that gcc spends huge amounts of code-size on loop prologues/epilogues, but tiny amounts on the actual loop; for all it knows the loop will run millions of iterations for each one time the code outside runs.)
Unfortunately it's not like gcc's auto-vectorized code is very efficient or compact. It spends a lot of code size on the loop cleanup code for the 16-byte SSE case (fully unrolling 15 byte-copies). With 32-byte AVX vectors, we get a rolled-up byte loop to handle the leftover elements. (For a 17 byte copy, this is pretty terrible vs. 1 XMM vector + 1 byte or glibc style overlapping 16-byte copies). With gcc7 and earlier, it does the same full unrolling until an alignment boundary as a loop prologue so it's twice as bloated.
IDK if profile-guided optimization would optimize gcc's strategy here, e.g. favouring smaller / simpler code when the count is small on every call, so auto-vectorized code wouldn't be reached. Or change strategy if the code is "cold" and only runs once or not at all per run of the whole program. Or if the count is usually 16 or 24 or something, then scalar for the last n % 32 bytes is terrible so ideally PGO would get it to special case smaller counts. (But I'm not too optimistic.)
I might report a GCC missed-optimization bug for this, about detecting memcpy after an overlap check instead of leaving it purely up to the auto-vectorizer. And/or about using rep movs for -Os, maybe with -mtune=icelake if more info becomes available about that uarch.
A lot of software gets compiled with only -O2, so a peephole for rep movs other than the auto-vectorizer could make a difference. (But the question is whether it's a positive or negative difference)!

Is mfence for rdtsc necessary on x86_64 platform?

unsigned int lo = 0;
unsigned int hi = 0;
__asm__ __volatile__ (
"mfence;rdtsc" : "=a"(lo), "=d"(hi) : : "memory"
);
mfence in the above code, is it necessary?
Based on my test, cpu reorder is not found.
The fragment of test code is included below.
inline uint64_t clock_cycles() {
unsigned int lo = 0;
unsigned int hi = 0;
__asm__ __volatile__ (
"rdtsc" : "=a"(lo), "=d"(hi)
);
return ((uint64_t)hi << 32) | lo;
}
unsigned t1 = clock_cycles();
unsigned t2 = clock_cycles();
assert(t2 > t1);
What you need to perform a sensible measurement with rdtsc is a serializing instruction.
As it is well known, a lot of people use cpuid before rdtsc.
rdtsc needs to be serialized from above and below (read: all instructions before it must be retired and it must be retired before the test code starts).
Unfortunately the second condition is often neglected because cpuid is a very bad choice for this task (it clobbers the output of rdtsc).
When looking for alternatives people think that instructions that have a "fence" in their names will do, but this is also untrue. Straight from Intel:
MFENCE does not serialize the instruction stream.
An instruction that is almost serializing and will do in any measurement where previous stores don't need to complete is lfence.
Simply put, lfence makes sure that no new instructions start before any prior instruction completes locally. See this answer of mine for a more detailed explanation on locality.
It also doesn't drain the Store Buffer like mfence does and doesn't clobbers the registers like cpuid does.
So lfence / rdtsc / lfence is a better crafted sequence of instructions than mfence / rdtsc, where mfence is pretty much useless unless you explicitly want the previous stores to be completed before the test begins/ends (but not before rdstc is executed!).
If your test to detect reordering is assert(t2 > t1) then I believe you will test nothing.
Leaving out the return and the call that may or may not prevent the CPU from seeing the second rdtsc in time for a reorder, it is unlikely (though possible!) that the CPU will reorder two rdtsc even if one is right after the other.
Imagine we have a rdtsc2 that is exactly like rdtsc but writes ecx:ebx1.
Executing
rdtsc
rdtsc2
is highly likely that ecx:ebx > edx:eax because the CPU has no reason to execute rdtsc2 before rdtsc.
Reordering doesn't mean random ordering, it means look for other instruction if the current one cannot be executed.
But rdtsc has no dependency on any previous instruction, so it's unlikely to be delayed when encountered by the OoO core.
However peculiar internal micro-architectural details may invalidate my thesis, hence the likely word in my previous statement.
1 We don't need this altered instruction: register renaming will do it, but in case you are not familiar with it, this will help.
mfence is there to force serialization in CPU before rdtsc.
Usually you will find cpuid there (which is also serializing instruction).
Quote from Intel manuals about using rdtsc will make it clearer
Starting with the Intel Pentium processor, most Intel CPUs support
out-of-order execution of the code. The purpose is to optimize the
penalties due to the different instruction latencies. Unfortunately
this feature does not guarantee that the temporal sequence of the
single compiled C instructions will respect the sequence of the
instruction themselves as written in the source C file. When we call
the RDTSC instruction, we pretend that that instruction will be
executed exactly at the beginning and at the end of code being
measured (i.e., we don’t want to measure compiled code executed
outside of the RDTSC calls or executed in between the calls
themselves).
The solution is to call a serializing instruction before
calling the RDTSC one. A serializing instruction is an instruction
that forces the CPU to complete every preceding instruction of the C
code before continuing the program execution. By doing so we guarantee
that only the code that is under measurement will be executed in
between the RDTSC calls and that no part of that code will be executed
outside the calls.
TL;DR version - without serializing instruction before rdtsc you have no idea when that instruction started to execute making measurements possibly incorrect.
HINT - use rdtscp when possible.
Based on my test, cpu reorder is not found.
Still no guarantee that it may happen - that's why original code had "memory" to indicate possible memory clobber preventing compiler from reordering it.

How to get the CPU cycle count in x86_64 from C++?

I saw this post on SO which contains C code to get the latest CPU Cycle count:
CPU Cycle count based profiling in C/C++ Linux x86_64
Is there a way I can use this code in C++ (windows and linux solutions welcome)? Although written in C (and C being a subset of C++) I am not too certain if this code would work in a C++ project and if not, how to translate it?
I am using x86-64
EDIT2:
Found this function but cannot get VS2010 to recognise the assembler. Do I need to include anything? (I believe I have to swap uint64_t to long long for windows....?)
static inline uint64_t get_cycles()
{
uint64_t t;
__asm volatile ("rdtsc" : "=A"(t));
return t;
}
EDIT3:
From above code I get the error:
"error C2400: inline assembler syntax error in 'opcode'; found 'data
type'"
Could someone please help?
Starting from GCC 4.5 and later, the __rdtsc() intrinsic is now supported by both MSVC and GCC.
But the include that's needed is different:
#ifdef _WIN32
#include <intrin.h>
#else
#include <x86intrin.h>
#endif
Here's the original answer before GCC 4.5.
Pulled directly out of one of my projects:
#include <stdint.h>
// Windows
#ifdef _WIN32
#include <intrin.h>
uint64_t rdtsc(){
return __rdtsc();
}
// Linux/GCC
#else
uint64_t rdtsc(){
unsigned int lo,hi;
__asm__ __volatile__ ("rdtsc" : "=a" (lo), "=d" (hi));
return ((uint64_t)hi << 32) | lo;
}
#endif
This GNU C Extended asm tells the compiler:
volatile: the outputs aren't a pure function of the inputs (so it has to re-run every time, not reuse an old result).
"=a"(lo) and "=d"(hi) : the output operands are fixed registers: EAX and EDX. (x86 machine constraints). The x86 rdtsc instruction puts its 64-bit result in EDX:EAX, so letting the compiler pick an output with "=r" wouldn't work: there's no way to ask the CPU for the result to go anywhere else.
((uint64_t)hi << 32) | lo - zero-extend both 32-bit halves to 64-bit (because lo and hi are unsigned), and logically shift + OR them together into a single 64-bit C variable. In 32-bit code, this is just a reinterpretation; the values still just stay in a pair of 32-bit registers. In 64-bit code you typically get an actual shift + OR asm instructions, unless the high half optimizes away.
(editor's note: this could probably be more efficient if you used unsigned long instead of unsigned int. Then the compiler would know that lo was already zero-extended into RAX. It wouldn't know that the upper half was zero, so | and + are equivalent if it wanted to merge a different way. The intrinsic should in theory give you the best of both worlds as far as letting the optimizer do a good job.)
https://gcc.gnu.org/wiki/DontUseInlineAsm if you can avoid it. But hopefully this section is useful if you need to understand old code that uses inline asm so you can rewrite it with intrinsics. See also https://stackoverflow.com/tags/inline-assembly/info
Your inline asm is broken for x86-64. "=A" in 64-bit mode lets the compiler pick either RAX or RDX, not EDX:EAX. See this Q&A for more
You don't need inline asm for this. There's no benefit; compilers have built-ins for rdtsc and rdtscp, and (at least these days) all define a __rdtsc intrinsic if you include the right headers. But unlike almost all other cases (https://gcc.gnu.org/wiki/DontUseInlineAsm), there's no serious downside to asm, as long as you're using a good and safe implementation like #Mysticial's.
(One minor advantage to asm is if you want to time a small interval that's certainly going to be less than 2^32 counts, you can ignore the high half of the result. Compilers could do that optimization for you with a uint32_t time_low = __rdtsc() intrinsic, but in practice they sometimes still waste instructions doing shift / OR.)
Unfortunately MSVC disagrees with everyone else about which header to use for non-SIMD intrinsics.
Intel's intriniscs guide says _rdtsc (with one underscore) is in <immintrin.h>, but that doesn't work on gcc and clang. They only define SIMD intrinsics in <immintrin.h>, so we're stuck with <intrin.h> (MSVC) vs. <x86intrin.h> (everything else, including recent ICC). For compat with MSVC, and Intel's documentation, gcc and clang define both the one-underscore and two-underscore versions of the function.
Fun fact: the double-underscore version returns an unsigned 64-bit integer, while Intel documents _rdtsc() as returning (signed) __int64.
// valid C99 and C++
#include <stdint.h> // <cstdint> is preferred in C++, but stdint.h works.
#ifdef _MSC_VER
# include <intrin.h>
#else
# include <x86intrin.h>
#endif
// optional wrapper if you don't want to just use __rdtsc() everywhere
inline
uint64_t readTSC() {
// _mm_lfence(); // optionally wait for earlier insns to retire before reading the clock
uint64_t tsc = __rdtsc();
// _mm_lfence(); // optionally block later instructions until rdtsc retires
return tsc;
}
// requires a Nehalem or newer CPU. Not Core2 or earlier. IDK when AMD added it.
inline
uint64_t readTSCp() {
unsigned dummy;
return __rdtscp(&dummy); // waits for earlier insns to retire, but allows later to start
}
Compiles with all 4 of the major compilers: gcc/clang/ICC/MSVC, for 32 or 64-bit. See the results on the Godbolt compiler explorer, including a couple test callers.
These intrinsics were new in gcc4.5 (from 2010) and clang3.5 (from 2014). gcc4.4 and clang 3.4 on Godbolt don't compile this, but gcc4.5.3 (April 2011) does. You might see inline asm in old code, but you can and should replace it with __rdtsc(). Compilers over a decade old usually make slower code than gcc6, gcc7, or gcc8, and have less useful error messages.
The MSVC intrinsic has (I think) existed far longer, because MSVC never supported inline asm for x86-64. ICC13 has __rdtsc in immintrin.h, but doesn't have an x86intrin.h at all. More recent ICC have x86intrin.h, at least the way Godbolt installs them for Linux they do.
You might want to define them as signed long long, especially if you want to subtract them and convert to float. int64_t -> float/double is more efficient than uint64_t on x86 without AVX512. Also, small negative results could be possible because of CPU migrations if TSCs aren't perfectly synced, and that probably makes more sense than huge unsigned numbers.
BTW, clang also has a portable __builtin_readcyclecounter() which works on any architecture. (Always returns zero on architectures without a cycle counter.) See the clang/LLVM language-extension docs
For more about using lfence (or cpuid) to improve repeatability of rdtsc and control exactly which instructions are / aren't in the timed interval by blocking out-of-order execution, see #HadiBrais' answer on clflush to invalidate cache line via C function and the comments for an example of the difference it makes.
See also Is LFENCE serializing on AMD processors? (TL:DR yes with Spectre mitigation enabled, otherwise kernels leave the relevant MSR unset so you should use cpuid to serialize.) It's always been defined as partially-serializing on Intel.
How to Benchmark Code Execution Times on Intel® IA-32 and IA-64
Instruction Set Architectures, an Intel white-paper from 2010.
rdtsc counts reference cycles, not CPU core clock cycles
It counts at a fixed frequency regardless of turbo / power-saving, so if you want uops-per-clock analysis, use performance counters. rdtsc is exactly correlated with wall-clock time (not counting system clock adjustments, so it's a perfect time source for steady_clock).
The TSC frequency used to always be equal to the CPU's rated frequency, i.e. the advertised sticker frequency. In some CPUs it's merely close, e.g. 2592 MHz on an i7-6700HQ 2.6 GHz Skylake, or 4008MHz on a 4000MHz i7-6700k. On even newer CPUs like i5-1035 Ice Lake, TSC = 1.5 GHz, base = 1.1 GHz, so disabling turbo won't even approximately work for TSC = core cycles on those CPUs.
If you use it for microbenchmarking, include a warm-up period first to make sure your CPU is already at max clock speed before you start timing. (And optionally disable turbo and tell your OS to prefer max clock speed to avoid CPU frequency shifts during your microbenchmark).
Microbenchmarking is hard: see Idiomatic way of performance evaluation? for other pitfalls.
Instead of TSC at all, you can use a library that gives you access to hardware performance counters. The complicated but low-overhead way is to program perf counters and use rdmsr in user-space, or simpler ways include tricks like perf stat for part of program if your timed region is long enough that you can attach a perf stat -p PID.
You usually will still want to keep the CPU clock fixed for microbenchmarks, though, unless you want to see how different loads will get Skylake to clock down when memory-bound or whatever. (Note that memory bandwidth / latency is mostly fixed, using a different clock than the cores. At idle clock speed, an L2 or L3 cache miss takes many fewer core clock cycles.)
Negative clock cycle measurements with back-to-back rdtsc? the history of RDTSC: originally CPUs didn't do power-saving, so the TSC was both real-time and core clocks. Then it evolved through various barely-useful steps into its current form of a useful low-overhead timesource decoupled from core clock cycles (constant_tsc), which doesn't stop when the clock halts (nonstop_tsc). Also some tips, e.g. don't take the mean time, take the median (there will be very high outliers).
std::chrono::clock, hardware clock and cycle count
Getting cpu cycles using RDTSC - why does the value of RDTSC always increase?
Lost Cycles on Intel? An inconsistency between rdtsc and CPU_CLK_UNHALTED.REF_TSC
measuring code execution times in C using RDTSC instruction lists some gotchas, including SMI (system-management interrupts) which you can't avoid even in kernel mode with cli), and virtualization of rdtsc under a VM. And of course basic stuff like regular interrupts being possible, so repeat your timing many times and throw away outliers.
Determine TSC frequency on Linux. Programatically querying the TSC frequency is hard and maybe not possible, especially in user-space, or may give a worse result than calibrating it. Calibrating it using another known time-source takes time. See that question for more about how hard it is to convert TSC to nanoseconds (and that it would be nice if you could ask the OS what the conversion ratio is, because the OS already did it at bootup).
If you're microbenchmarking with RDTSC for tuning purposes, your best bet is to just use ticks and skip even trying to convert to nanoseconds. Otherwise, use a high-resolution library time function like std::chrono or clock_gettime. See faster equivalent of gettimeofday for some discussion / comparison of timestamp functions, or reading a shared timestamp from memory to avoid rdtsc entirely if your precision requirement is low enough for a timer interrupt or thread to update it.
See also Calculate system time using rdtsc about finding the crystal frequency and multiplier.
CPU TSC fetch operation especially in multicore-multi-processor environment says that Nehalem and newer have the TSC synced and locked together for all cores in a package (along with the invariant = constant and nonstop TSC feature). See #amdn's answer there for some good info about multi-socket sync.
(And apparently usually reliable even for modern multi-socket systems as long as they have that feature, see #amdn's answer on the linked question, and more details below.)
CPUID features relevant to the TSC
Using the names that Linux /proc/cpuinfo uses for the CPU features, and other aliases for the same feature that you'll also find.
tsc - the TSC exists and rdtsc is supported. Baseline for x86-64.
rdtscp - rdtscp is supported.
tsc_deadline_timer CPUID.01H:ECX.TSC_Deadline[bit 24] = 1 - local APIC can be programmed to fire an interrupt when the TSC reaches a value you put in IA32_TSC_DEADLINE. Enables "tickless" kernels, I think, sleeping until the next thing that's supposed to happen.
constant_tsc: Support for the constant TSC feature is determined by checking the CPU family and model numbers. The TSC ticks at constant frequency regardless of changes in core clock speed. Without this, RDTSC does count core clock cycles.
nonstop_tsc: This feature is called the invariant TSC in the Intel SDM manual and is supported on processors with CPUID.80000007H:EDX[8]. The TSC keeps ticking even in deep sleep C-states. On all x86 processors, nonstop_tsc implies constant_tsc, but constant_tsc doesn't necessarily imply nonstop_tsc. No separate CPUID feature bit; on Intel and AMD the same invariant TSC CPUID bit implies both constant_tsc and nonstop_tsc features. See Linux's x86/kernel/cpu/intel.c detection code, and amd.c was similar.
Some of the processors (but not all) that are based on the Saltwell/Silvermont/Airmont even keep TSC ticking in ACPI S3 full-system sleep: nonstop_tsc_s3. This is called always-on TSC. (Although it seems the ones based on Airmont were never released.)
For more details on constant and invariant TSC, see: Can constant non-invariant tsc change frequency across cpu states?.
tsc_adjust: CPUID.(EAX=07H, ECX=0H):EBX.TSC_ADJUST (bit 1) The IA32_TSC_ADJUST MSR is available, allowing OSes to set an offset that's added to the TSC when rdtsc or rdtscp reads it. This allows effectively changing the TSC on some/all cores without desyncing it across logical cores. (Which would happen if software set the TSC to a new absolute value on each core; it's very hard to get the relevant WRMSR instruction executed at the same cycle on every core.)
constant_tsc and nonstop_tsc together make the TSC usable as a timesource for things like clock_gettime in user-space. (But OSes like Linux only use RDTSC to interpolate between ticks of a slower clock maintained with NTP, updating the scale / offset factors in timer interrupts. See On a cpu with constant_tsc and nonstop_tsc, why does my time drift?) On even older CPUs that don't support deep sleep states or frequency scaling, TSC as a timesource may still be usable
The comments in the Linux source code also indicate that constant_tsc / nonstop_tsc features (on Intel) implies "It is also reliable across cores and sockets. (but not across cabinets - we turn it off in that case explicitly.)"
The "across sockets" part is not accurate. In general, an invariant TSC only guarantees that the TSC is synchronized between cores within the same socket. On an Intel forum thread, Martin Dixon (Intel) points out that TSC invariance does not imply cross-socket synchronization. That requires the platform vendor to distribute RESET synchronously to all sockets. Apparently platform vendors do in practice do that, given the above Linux kernel comment. Answers on CPU TSC fetch operation especially in multicore-multi-processor environment also agree that all sockets on a single motherboard should start out in sync.
On a multi-socket shared memory system, there is no direct way to check whether the TSCs in all the cores are synced. The Linux kernel, by default performs boot-time and run-time checks to make sure that TSC can be used as a clock source. These checks involve determining whether the TSC is synced. The output of the command dmesg | grep 'clocksource' would tell you whether the kernel is using TSC as the clock source, which would only happen if the checks have passed. But even then, this would not be definitive proof that the TSC is synced across all sockets of the system. The kernel paramter tsc=reliable can be used to tell the kernel that it can blindly use the TSC as the clock source without doing any checks.
There are cases where cross-socket TSCs may NOT be in sync: (1) hotplugging a CPU, (2) when the sockets are spread out across different boards connected by extended node controllers, (3) a TSC may not be resynced after waking up from a C-state in which the TSC is powered-downed in some processors, and (4) different sockets have different CPU models installed.
An OS or hypervisor that changes the TSC directly instead of using the TSC_ADJUST offset can de-sync them, so in user-space it might not always be safe to assume that CPU migrations won't leave you reading a different clock. (This is why rdtscp produces a core-ID as an extra output, so you can detect when start/end times come from different clocks. It might have been introduced before the invariant TSC feature, or maybe they just wanted to account for every possibility.)
If you're using rdtsc directly, you may want to pin your program or thread to a core, e.g. with taskset -c 0 ./myprogram on Linux. Whether you need it for the TSC or not, CPU migration will normally lead to a lot of cache misses and mess up your test anyway, as well as taking extra time. (Although so will an interrupt).
How efficient is the asm from using the intrinsic?
It's about as good as you'd get from #Mysticial's GNU C inline asm, or better because it knows the upper bits of RAX are zeroed. The main reason you'd want to keep inline asm is for compat with crusty old compilers.
A non-inline version of the readTSC function itself compiles with MSVC for x86-64 like this:
unsigned __int64 readTSC(void) PROC ; readTSC
rdtsc
shl rdx, 32 ; 00000020H
or rax, rdx
ret 0
; return in RAX
For 32-bit calling conventions that return 64-bit integers in edx:eax, it's just rdtsc/ret. Not that it matters, you always want this to inline.
In a test caller that uses it twice and subtracts to time an interval:
uint64_t time_something() {
uint64_t start = readTSC();
// even when empty, back-to-back __rdtsc() don't optimize away
return readTSC() - start;
}
All 4 compilers make pretty similar code. This is GCC's 32-bit output:
# gcc8.2 -O3 -m32
time_something():
push ebx # save a call-preserved reg: 32-bit only has 3 scratch regs
rdtsc
mov ecx, eax
mov ebx, edx # start in ebx:ecx
# timed region (empty)
rdtsc
sub eax, ecx
sbb edx, ebx # edx:eax -= ebx:ecx
pop ebx
ret # return value in edx:eax
This is MSVC's x86-64 output (with name-demangling applied). gcc/clang/ICC all emit identical code.
# MSVC 19 2017 -Ox
unsigned __int64 time_something(void) PROC ; time_something
rdtsc
shl rdx, 32 ; high <<= 32
or rax, rdx
mov rcx, rax ; missed optimization: lea rcx, [rdx+rax]
; rcx = start
;; timed region (empty)
rdtsc
shl rdx, 32
or rax, rdx ; rax = end
sub rax, rcx ; end -= start
ret 0
unsigned __int64 time_something(void) ENDP ; time_something
All 4 compilers use or+mov instead of lea to combine the low and high halves into a different register. I guess it's kind of a canned sequence that they fail to optimize.
But writing a shift/lea in inline asm yourself is hardly better. You'd deprive the compiler of the opportunity to ignore the high 32 bits of the result in EDX, if you're timing such a short interval that you only keep a 32-bit result. Or if the compiler decides to store the start time to memory, it could just use two 32-bit stores instead of shift/or / mov. If 1 extra uop as part of your timing bothers you, you'd better write your whole microbenchmark in pure asm.
However, we can maybe get the best of both worlds with a modified version of #Mysticial's code:
// More efficient than __rdtsc() in some case, but maybe worse in others
uint64_t rdtsc(){
// long and uintptr_t are 32-bit on the x32 ABI (32-bit pointers in 64-bit mode), so #ifdef would be better if we care about this trick there.
unsigned long lo,hi; // let the compiler know that zero-extension to 64 bits isn't required
__asm__ __volatile__ ("rdtsc" : "=a" (lo), "=d" (hi));
return ((uint64_t)hi << 32) + lo;
// + allows LEA or ADD instead of OR
}
On Godbolt, this does sometimes give better asm than __rdtsc() for gcc/clang/ICC, but other times it tricks compilers into using an extra register to save lo and hi separately, so clang can optimize into ((end_hi-start_hi)<<32) + (end_lo-start_lo). Hopefully if there's real register pressure, compilers will combine earlier. (gcc and ICC still save lo/hi separately, but don't optimize as well.)
But 32-bit gcc8 makes a mess of it, compiling even just the rdtsc() function itself with an actual add/adc with zeros instead of just returning the result in edx:eax like clang does. (gcc6 and earlier do ok with | instead of +, but definitely prefer the __rdtsc() intrinsic if you care about 32-bit code-gen from gcc).
VC++ uses an entirely different syntax for inline assembly -- but only in the 32-bit versions. The 64-bit compiler doesn't support inline assembly at all.
In this case, that's probably just as well -- rdtsc has (at least) two major problem when it comes to timing code sequences. First (like most instructions) it can be executed out of order, so if you're trying to time a short sequence of code, the rdtsc before and after that code might both be executed before it, or both after it, or what have you (I am fairly sure the two will always execute in order with respect to each other though, so at least the difference will never be negative).
Second, on a multi-core (or multiprocessor) system, one rdtsc might execute on one core/processor and the other on a different core/processor. In such a case, a negative result is entirely possible.
Generally speaking, if you want a precise timer under Windows, you're going to be better off using QueryPerformanceCounter.
If you really insist on using rdtsc, I believe you'll have to do it in a separate module written entirely in assembly language (or use a compiler intrinsic), then linked with your C or C++. I've never written that code for 64-bit mode, but in 32-bit mode it looks something like this:
xor eax, eax
cpuid
xor eax, eax
cpuid
xor eax, eax
cpuid
rdtsc
; save eax, edx
; code you're going to time goes here
xor eax, eax
cpuid
rdtsc
I know this looks strange, but it's actually right. You execute CPUID because it's a serializing instruction (can't be executed out of order) and is available in user mode. You execute it three times before you start timing because Intel documents the fact that the first execution can/will run at a different speed than the second (and what they recommend is three, so three it is).
Then you execute your code under test, another cpuid to force serialization, and the final rdtsc to get the time after the code finished.
Along with that, you want to use whatever means your OS supplies to force this all to run on one process/core. In most cases, you also want to force the code alignment -- changes in alignment can lead to fairly substantial differences in execution spee.
Finally you want to execute it a number of times -- and it's always possible it'll get interrupted in the middle of things (e.g., a task switch), so you need to be prepared for the possibility of an execution taking quite a bit longer than the rest -- e.g., 5 runs that take ~40-43 clock cycles apiece, and a sixth that takes 10000+ clock cycles. Clearly, in the latter case, you just throw out the outlier -- it's not from your code.
Summary: managing to execute the rdtsc instruction itself is (almost) the least of your worries. There's quite a bit more you need to do before you can get results from rdtsc that will actually mean anything.
For Windows, Visual Studio provides a convenient "compiler intrinsic" (i.e. a special function, which the compiler understands) that executes the RDTSC instruction for you and gives you back the result:
unsigned __int64 __rdtsc(void);
Linux perf_event_open system call with config = PERF_COUNT_HW_CPU_CYCLES
This Linux system call appears to be a cross architecture wrapper for performance events.
This answer similar: Quick way to count number of instructions executed in a C program but with PERF_COUNT_HW_CPU_CYCLES instead of PERF_COUNT_HW_INSTRUCTIONS. This answer will focus on PERF_COUNT_HW_CPU_CYCLES specifics, see that other answer for more generic information.
Here is an example based on the one provided at the end of the man page.
perf_event_open.c
#define _GNU_SOURCE
#include <asm/unistd.h>
#include <linux/perf_event.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <sys/ioctl.h>
#include <unistd.h>
#include <inttypes.h>
#include <sys/types.h>
static long
perf_event_open(struct perf_event_attr *hw_event, pid_t pid,
int cpu, int group_fd, unsigned long flags)
{
int ret;
ret = syscall(__NR_perf_event_open, hw_event, pid, cpu,
group_fd, flags);
return ret;
}
int
main(int argc, char **argv)
{
struct perf_event_attr pe;
long long count;
int fd;
uint64_t n;
if (argc > 1) {
n = strtoll(argv[1], NULL, 0);
} else {
n = 10000;
}
memset(&pe, 0, sizeof(struct perf_event_attr));
pe.type = PERF_TYPE_HARDWARE;
pe.size = sizeof(struct perf_event_attr);
pe.config = PERF_COUNT_HW_CPU_CYCLES;
pe.disabled = 1;
pe.exclude_kernel = 1;
// Don't count hypervisor events.
pe.exclude_hv = 1;
fd = perf_event_open(&pe, 0, -1, -1, 0);
if (fd == -1) {
fprintf(stderr, "Error opening leader %llx\n", pe.config);
exit(EXIT_FAILURE);
}
ioctl(fd, PERF_EVENT_IOC_RESET, 0);
ioctl(fd, PERF_EVENT_IOC_ENABLE, 0);
/* Loop n times, should be good enough for -O0. */
__asm__ (
"1:;\n"
"sub $1, %[n];\n"
"jne 1b;\n"
: [n] "+r" (n)
:
:
);
ioctl(fd, PERF_EVENT_IOC_DISABLE, 0);
read(fd, &count, sizeof(long long));
printf("%lld\n", count);
close(fd);
}
The results seem reasonable, e.g. if I print cycles then recompile for instruction counts, we get about 1 cycle per iteration (2 instructions done in a single cycle) possibly due to effects such as superscalar execution, with slightly different results for each run presumably due to random memory access latencies.
You might also be interested in PERF_COUNT_HW_REF_CPU_CYCLES, which as the manpage documents:
Total cycles; not affected by CPU frequency scaling.
so this will give something closer to the real wall time if your frequency scaling is on. These were 2/3x larger than PERF_COUNT_HW_INSTRUCTIONS on my quick experiments, presumably because my non-stressed machine is frequency scaled now.