# std::atomic vs volatile, disassembled

This came up during a code review and the code was using volatile to ensure the access to the pointer variable is atomic and serialized, and we were sort of debating whether it is sufficient, in particular:

1. Is it safer to switch to std::atomic<T>, and if so, why?
2. Is volatile sufficiently safe for a strong memory model CPU like x86?

Most of us can probably agree that std::atomic<T> would be safer, but we need to dig a bit deeper to see why is it safer, and even for x86.

## What is the difference?

std::atomic provides atomic access to variables and provides different memory model access for store/load as well as bunch of multi-threading primitives. The default load and store provides sequential memory order guarantees.

volatile only prevents compiler optimization (it may do more depending on compilers) so a read / write cannot be optimized away in case another thread might modify it. But it provides no gaurantees in the hardware level, and no barrier is guaranteed. In some compilers (such as Visual C++) might insert barrier for you, but it isn’t guaranteed - for example gcc gives you no barriers.

## Is std::atomic still required if you have volatile?

To answer this question we need to understand the concept of memory model. If all access to memory were seqential in nature and exactly done as written in code, we wouldn’t be having this discussion. However, in practice, reordering can happen in two levels:

• compiler - compiler can reorder / delay / cache variables in registers
• hardware - CPU can reorder read/write as long as the end result should be the same

volatile only prevents compiler optimizations but CPU might still reorder operations and/or cache the reads/writes, so the end result is still hardware dependent.

Memory model is how hardware models memory access and what kind of ordering and visibility guarantee it provides. CPUs are typically either strong memory model (x86, etc) or weak memory model (ARM, etc). This blog has one of the best description of weak memory model vs strong memory model. In particular, x86 CPU falls in the strong memory model category, which means usually load implies acquire semantics and load implies release semantics, but there is no ordering guarantee with #StoreLoad ordering, as observed in this example. To better understand acquire/release semantics, you can refer to this post.

So in short if you want your code to be correct and portable, and even in x86, the short answer is it’s best to not take any chances and use std::atomic. It’s better to be correct than fast and wrong.

## std::atomic under the hood for x86

But you might wonder - what does std::atomic<T> do for x86 anyway? What is the magic?

It’d be easier to look into this by writing code using std::atomic<T> and looking at the disassembly code.

Suppose we have following code:

#include <atomic>
#include <stdio.h>

using namespace std;

std::atomic<int> x(0);
int main(void) {
x.store(2);
x.store(3, std::memory_order_release);

printf("%d", y);

printf("%d", y);

return 0;
}


And let’s compile it with optimization and dump out the disassembly:

g++ atomic.cc --std=c++11 -O3
objdump --all -d ./a.out > a


And the output of main looks as follows:

0000000000401040 <main>:
401040:       48 83 ec 08             sub    $0x8,%rsp 401044: b8 02 00 00 00 mov$0x2,%eax
401049:       87 05 d9 2f 00 00       xchg   %eax,0x2fd9(%rip)        # 404028 <x>
40104f:       bf 10 20 40 00          mov    $0x402010,%edi 401054: 31 c0 xor %eax,%eax 401056: c7 05 c8 2f 00 00 03 movl$0x3,0x2fc8(%rip)        # 404028 <x>
40105d:       00 00 00
401060:       8b 35 c2 2f 00 00       mov    0x2fc2(%rip),%esi        # 404028 <x>
401066:       e8 c5 ff ff ff          callq  401030 <[email protected]>
40106b:       8b 35 b7 2f 00 00       mov    0x2fb7(%rip),%esi        # 404028 <x>
401071:       bf 10 20 40 00          mov    $0x402010,%edi 401076: 31 c0 xor %eax,%eax 401078: e8 b3 ff ff ff callq 401030 <[email protected]> 40107d: 31 c0 xor %eax,%eax 40107f: 48 83 c4 08 add$0x8,%rsp
401083:       c3                      retq


For the first store(2, std::memory_order_seq_cst) (the default) in x86, gcc made it a full barrier using xchg instruction which has a implicit lock prefix:

  401049:       87 05 d9 2f 00 00       xchg   %eax,0x2fd9(%rip)        # 404028 <x>


Here the source is %eax = 2, the target of the move is address rip (=next instruction 0x40104f) + 0x2fd9 offset = 0x404028, which is the location of the global variable x.

If you are wondering what is the behavior of std::atomic<T>::operator = - it is the equivalent of store(std::memory_order_seq_cst)

In some compilers you may get mfence which is the full barrier instruction in x86 CPU, so the end result is the same.

Now to the second store(3, std::memory_order_release). Recall under x86 all store has release semantics, so the code is just normal mov:

  401056:       c7 05 c8 2f 00 00 03    movl   $0x3,0x2fc8(%rip) # 404028 <x>  Now let’s look at reads. For the first load(std::memory_order_seq_cst) (the default), given that in a sequential memory order a write already would publish the results to all cores with a full memory barrier, there is nothing we need to do. It is just a regular read - reading a memory location into esi, which is the 2nd argument to printf as per linux SystemV x64 ABI:  401060: 8b 35 c2 2f 00 00 mov 0x2fc2(%rip),%esi # 404028 <x>  For the 2nd load(std::memory_order_acquire), again recall x86 every load is implicitly has acquire semantics, so again it is just a regular read:  40106b: 8b 35 b7 2f 00 00 mov 0x2fb7(%rip),%esi # 404028 <x>  ## What if this is volatile? If we replace the atomic to be a volatile: #include <atomic> #include <stdio.h> using namespace std; volatile int x(0); int main(void) { x = 2; x = 3; int y = x; printf("%d", y); return 0; }  The result code looks like this: 0000000000401040 <main>: 401040: 48 83 ec 08 sub$0x8,%rsp
401044:       bf 10 20 40 00          mov    $0x402010,%edi 401049: 31 c0 xor %eax,%eax 40104b: c7 05 d3 2f 00 00 02 movl$0x2,0x2fd3(%rip)        # 404028 <x>
401052:       00 00 00
401055:       c7 05 c9 2f 00 00 03    movl   $0x3,0x2fc9(%rip) # 404028 <x> 40105c: 00 00 00 40105f: 8b 35 c3 2f 00 00 mov 0x2fc3(%rip),%esi # 404028 <x> 401065: e8 c6 ff ff ff callq 401030 <[email protected]> 40106a: 31 c0 xor %eax,%eax 40106c: 48 83 c4 08 add$0x8,%rsp
401070:       c3                      retq


You can see the xchg becomes a simple movl as volatile doesn’t guarantee any ordering - it only prevents compiler optimization. What optimization, you might ask? Let’s see what happens when we remove the volatile.

## Taking out the volatile

Now let’s just take out the volatile keyword, and see what we would get:

0000000000401040 <main>:
401040:       48 83 ec 08             sub    $0x8,%rsp 401044: be 03 00 00 00 mov$0x3,%esi
401049:       bf 10 20 40 00          mov    $0x402010,%edi 40104e: 31 c0 xor %eax,%eax 401050: c7 05 ce 2f 00 00 03 movl$0x3,0x2fce(%rip)        # 404028 <x>
401057:       00 00 00
40105a:       e8 d1 ff ff ff          callq  401030 <[email protected]>
40105f:       31 c0                   xor    %eax,%eax
401061:       48 83 c4 08             add    $0x8,%rsp 401065: c3 retq  You might have already noticed two significant differences: • The assignment x=2 is completely gone. compiler knows there are no side effects to the x=2 assignment so it is free to optimize it away • The read is completely gone, instead we assign %esi = 3 for printf from the get go:  401044: be 03 00 00 00 mov$0x3,%esi


Again, compiler is free to optimize the load because no one else is going to change x in between, so it can simply replace x with 3 in the printf.

## Conclusion

Multi-threading, memory-model, barriers are complicated topics but hopefully this gives you a good starting point. Even seemingly question like what is the difference of volatile and atomic can be quite confusing, and the fact that different compilers does different things for volatile made this more confusing (VC++ for example offers stronger gaurantee for volatile making it a full barrier). If you are still hungry for more, there is Linux Kernel Memory Barrier Doc that has great details and every programmer does lock-free multi-thread programming or want to understand the details probably should read. At the end of the day, having good understanding of compilers, assembly code and computer/CPU architecture would go a long way for system programmers.