Hyper-Threading Technology is a form of simultaneous multithreading technology introduced by Intel.
These resources include the execution engine, caches, and system bus interface; the sharing of resources allows two logical processors to work with each other more efficiently, and allows a stalled logical processor to borrow resources from the other one.
In the Intel CPU with Hyper-Threading, one CPU-Core (with several ALUs) can execute instructions from 2 threads at the same clock. And both 2 threads share: store-buffer, caches L1/L2 and system bus.
But if two thread execute simultaneous on one Core, thread-1 stores atomic value and thread-2 loads this value, what will be used for this exchange: shared store-buffer, shared cache L1 / L2 or as usual cache L3?
What will be happen if both 2 threads from one the same process (the same virtual address space) and if from two different processes (the different virtual address space)?
Sandy Bridge Intel CPU - cache L1:
32 KB - cache size
64 B - cache line size
512 - lines (512 = 32 KB / 64 B)
8-way
64 - number sets of ways (64 = 512 lines / 8-way)
6 bits [11:6] - of virtual address (index) defines current set number (this is tag)
4 K - each the same (virtual address / 4 K) compete for the same set (32 KB / 8-way)
low 12 bits - significant for determining the current set number
4 KB - standard page size
low 12 bits - the same in virtual and physical addresses for each address
A single CPU core can have up-to 2 threads per core. For example, if a CPU is dual core (i.e., 2 cores) it will have 4 threads. And if a CPU is Octal core (i.e., 8 core) it will have 16 threads and vice-versa.
Concurrency and Parallelism In a multithreaded process on a single processor, the processor can switch execution resources between threads, resulting in concurrent execution. Concurrency indicates that more than one thread is making progress, but the threads are not actually running simultaneously.
In short: yes, a thread can run on different cores.
Cores increase the amount of work accomplished at a time, whereas threads improve throughput, computational speed-up. Cores is an actual hardware component whereas thread is a virtual component that manages the tasks. Cores use content switching while threads use multiple CPUs for operating numerous processes.
I think you'll get a round-trip to L1. (Not the same thing as store->load forwarding within a single thread, which is even faster than that.)
Intel's optimization manual says that store and load buffers are statically partitioned between threads, which tells us a lot about how this will work. I haven't tested most of this, so please let me know if my predictions aren't matching up with experiment.
Update: See this Q&A for some experimental testing of throughput and latency.
A store has to retire in the writing thread, and then commit to L1 from the store buffer/queue some time after that. At that point it will be visible to the other thread, and a load to that address from either thread should hit in L1. Before that, the other thread should get an L1 hit with the old data, and the storing thread should get the stored data via store->load forwarding.
Store data enters the store buffer when the store uop executes, but it can't commit to L1 until it's known to be non-speculative, i.e. it retires. But the store buffer also de-couples retirement from the ROB (the ReOrder Buffer in the out-of-order core) vs. commitment to L1, which is great for stores that miss in cache. The out-of-order core can keep working until the store buffer fills up.
Two threads running on the same core with hyperthreading can see StoreLoad re-ordering if they don't use memory fences, because store-forwarding doesn't happen between threads. Jeff Preshing's Memory Reordering Caught in the Act code could be used to test for it in practice, using CPU affinity to run the threads on different logical CPUs of the same physical core.
An atomic read-modify-write operation has to make its store globally visible (commit to L1) as part of its execution, otherwise it wouldn't be atomic. As long as the data doesn't cross a boundary between cache lines, it can just lock that cache line. (AFAIK this is how CPUs do typically implement atomic RMW operations like lock add [mem], 1
or lock cmpxchg [mem], rax
.)
Either way, once it's done the data will be hot in the core's L1 cache, where either thread can get a cache hit from loading it.
I suspect that two hyperthreads doing atomic increments to a shared counter (or any other lock
ed operation, like xchg [mem], eax
) would achieve about the same throughput as a single thread. This is much higher than for two threads running on separate physical cores, where the cache line has to bounce between the L1 caches of the two cores (via L3).
movNT
(Non-Temporal) weakly-ordered stores bypass the cache, and put their data into a line-fill buffer. They also evict the line from L1 if it was hot in cache to start with. They probably have to retire before the data goes into a fill buffer, so a load from the other thread probably won't see it at all until it enters a fill-buffer. Then probably it's the same as an movnt store followed by a load inside a single thread. (i.e. a round-trip to DRAM, a few hundred cycles of latency). Don't use NT stores for a small piece of data you expect another thread to read right away.
L1 hits are possible because of the way Intel CPUs share the L1 cache. Intel uses virtually indexed, physically tagged (VIPT) L1 caches in most (all?) of their designs. (e.g. the Sandybridge family.) But since the index bits (which select a set of 8 tags) are below the page-offset, it behaves exactly like a PIPT cache (think of it as translation of the low 12 bits being a no-op), but with the speed advantage of a VIPT cache: it can fetch the tags from a set in parallel with the TLB lookup to translate the upper bits. See the "L1 also uses speed tricks that wouldn't work if it was larger" paragraph in this answer.
Since L1d cache behaves like PIPT, and the same physical address really means the same memory, it doesn't matter whether it's 2 threads of the same process with the same virtual address for a cache line, or whether it's two separate processes mapping a block of shared memory to different addresses in each process. This is why L1d can be (and is) competitively by both hyperthreads without risk of false-positive cache hits. Unlike the dTLB, which needs to tag its entries with a core ID.
A previous version of this answer had a paragraph here based on the incorrect idea that Skylake had reduced L1 associativity. It's Skylake's L2 that's 4-way, vs. 8-way in Broadwell and earlier. Still, the discussion on a more recent answer might be of interest.
Intel's x86 manual vol3, chapter 11.5.6 documents that Netburst (P4) has an option to not work this way. The default is "Adaptive mode", which lets logical processors within a core share data.
There is a "shared mode":
In shared mode, the L1 data cache is competitively shared between logical processors. This is true even if the logical processors use identical CR3 registers and paging modes.
In shared mode, linear addresses in the L1 data cache can be aliased, meaning that one linear address in the cache can point to different physical locations. The mechanism for resolving aliasing can lead to thrashing. For this reason, IA32_MISC_ENABLE[bit 24] = 0 is the preferred configuration for processors based on the Intel NetBurst microarchitecture that support Intel Hyper-Threading Technology
It doesn't say anything about this for hyperthreading in Nehalem / SnB uarches, so I assume they didn't include "slow mode" support when they introduced HT support in another uarch, since they knew they'd gotten "fast mode" to work correctly in netburst. I kinda wonder if this mode bit only existed in case they discovered a bug and had to disable it with microcode updates.
The rest of this answer only addresses the normal setting for P4, which I'm pretty sure is also the way Nehalem and SnB-family CPUs work.
It would be possible in theory to build an OOO SMT CPU core that made stores from one thread visible to the other as soon as they retired, but before they leaves the store buffer and commit to L1d (i.e. before they become globally visible). This is not how Intel's designs work, since they statically partition the store queue instead of competitively sharing it.
Even if the threads shared one store-buffer, store forwarding between threads for stores that haven't retired yet couldn't be allowed because they're still speculative at that point. That would tie the two threads together for branch mispredicts and other rollbacks.
Using a shared store queue for multiple hardware threads would take extra logic to always forward to loads from the same thread, but only forward retired stores to loads from the other thread(s). Besides transistor count, this would probably have a significant power cost. You couldn't just omit store-forwarding entirely for non-retired stores, because that would break single-threaded code.
Some POWER CPUs may actually do this; it seems like the most likely explanation for not all threads agreeing on a single global order for stores. Will two atomic writes to different locations in different threads always be seen in the same order by other threads?.
As @BeeOnRope points out, this wouldn't work for an x86 CPU, only for an ISA that doesn't guarantee a Total Store Order, because this this would let the SMT sibling(s) see your store before it becomes globally visible to other cores.
TSO could maybe be preserved by treating data from sibling store-buffers as speculative, or not able to happen before any cache-miss loads (because lines that stay hot in your L1D cache can't contain new stores from other cores). IDK, I haven't thought this through fully. It seems way overcomplicated and probably not able to do useful forwarding while maintaining TSO, even beyond the complications of having a shared store-buffer or probing sibling store-buffers.
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