Understanding how atomic instructions work and their effect (or lack of) on the system is important for optimizations.
Ultimately, I'm basing my viewpoint from this PDF: the "Is parallel programming Hard" free online book.
https://www.kernel.org/pub/linux/kernel/people/paulmck/perfb...
> Line 1 defines an atomic variable, line 5 atomically increments it, and line 10 reads it out. Because this is atomic, it keeps perfect count. However, it is slower: on a Intel Core Duo laptop, it is about six times slower than non-atomic increment when a single thread is incrementing, and more than ten times slower if two threads are incrementing.
The PDF changes over time. But this line can be found on page 42 at the moment.
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So according to the tests done by the author here, atomic operations are CERTAINLY slower, even in single-threaded cases.
I can't say I understand why they're slower, but something is definitely going on.
[1] atomic stores and loads are extremely cheap on x86.
[2] you can see that from the cost: a RMW or membar is around 20-30 clock cycles, while cross core communication costs in the order of 100s cycles.
edit: s/buffer/barrier/
The extra penalty introduced by common atomic operations that make strong guarantees about ordering is waiting for the store buffer to flush all prior stores before the result of the atomic operation is flushed out of the store buffers to L1 and then the atomic operation is flushed.
I hesitate to make generalizations about memory visibility requirements and costs as it is very API and hardware specific. Weaker guarantees exist and would have different costs.
TL;DR The total memory overhead is the same the difference is the atomic operation stalls the CPU that is performing the atomic operation unless it can speculate past it.
Also blind stores can be resolved in the background and don't block the CPU from continuing as long as the cache line is never read from.