I was going through Cache Write Policies paper by Norman P. Jouppi and I understand why write-invalidate (defined on page 193) works well with direct mapped caches which is because of the ability to write the data which checking the tag and if found to be miss, the cache line is invalidates as it is corrupted by the write. This can be done in one cycle.
But is there any benefit if write-invalidate is used for set-associative caches?
What is the usual configuration that is used for L1 caches in real processors? Do they use direct or set-associative and write-validate/write around/write invalidate/fetch-on-write policy?
TL:DR: for a non-blocking cache using write-invalidate, changing it from direct-mapped to set-associative could hurt the hit rate unless writes are very rare, or mean that you introduce the possibility of needing to block.
Write-invalidate only makes sense for a simple in-order pipeline with a simple cache that tries to avoid stalling the pipeline even without a store buffer, and go really fast at the expense of hit-rate. If you were going to change things to improve hit-rate, changing away from write-invalidate (usually to write-back + write-allocate + fetch-on-write) would be one of the first things. Write-invalidate with set-associative cache is possible with some ugly tradeoffs, but you wouldn't like the results.
The 1993 paper you linked is using that term to mean something other than the modern cache-coherence mechanism meaning. In the paper:
The combination of
write-before-hit, no-fetch-on-write, and no-write-allocate
we call write-invalidate
Yes, real-world caches these days are basically always set-associative; the more complex tag-comparator logic is worth the increased hit-rate for the same data size. Which cache mapping technique is used in intel core i7 processor? has some general stuff, not just x86. Modern examples of direct-mapped caches include the DRAM cache when a part of the persistent memory on an Intel platform operates in memory mode. Also many server-grade processors from multiple vendors support L3 way-wise partitioning, so you can, for example, allocate one way for a thread which would basically behave like a direct-mapped cache.
Write policy is usually write-allocate + fetch-on-write + no-write-before-hit for modern CPU caches; some ISAs offer methods such as special instructions to bypass cache for "non-temporal" stores that won't be re-read soon, to avoid cache pollution for those cases. Most workloads do re-load their stores with enough temporal locality that write-allocate is the only sane choice, especially when caches are larger and/or more associative so they're more likely to be able to hang onto a line until the next read or write.
It's also very common to do multiple small writes into the same line, making write-allocate very valuable, especially if a store buffer didn't manage to merge those writes.
But is there any benefit if write-invalidate is used for set-associative caches?
It doesn't seem so.
The only advantage it has is not stalling a simple in-order pipeline that lacks a store buffer ("write buffer" in the paper). It allows write in parallel with the tag-check, so you find out after modifying the line whether you hit or not. (Modern CPUs do use a store buffer to decouple store commit to L1d from store execution and hide store-miss latency. Even in-order CPUs typically have a store buffer to allow memory-level parallelism of RFOs (read-for-ownership). (e.g. ARM Cortex-A53 found in phones).
Anyway, in a set-associative cache, you need to check tags to know which "way" of the set to write into on a write hit. (Or detect a miss and pick one to evict according to some policy, like random or pseudo-LRU using some extra state bits, or write-around if no-write-allocate). If you wait until after the tag check to find the write way, you've lost the only benefit of write-invalidate.
Blindly writing to a random way could lead to a situation where there's a hit in a different way than the one you guessed. Way-prediction is a thing (and can do better than random), but the downside of an incorrect prediction for a write like this would be unnecessarily invalidating a line, instead of just a bit of extra latency. Way prediction in modern cache. I don't know what kind of success-rate way-prediction usually achieves. I'd guess not great, like maybe 80 to 90% at best. Probably spending transistors to do way-prediction would be better spent elsewhere, to do something that sucks less than write-invalidate! A store buffer with store forwarding probably costs more, but is a lot better.
The advantage of write-invalidate is to help make the cache non-blocking. But if you need to correct the situation when you do find a write-hit in a way other than the one you picked, you need to go back and correct the situation, updating the correct line. So you'd lose the non-blocking property. Never stalling is better than not usually stalling, because it means you don't even need to make the hardware handle that possible case at all. (Although you do need to be able to stall for memory.)
The write-in-one-way-hit-in-another situation can be avoided by writing in all of the ways. But there will be at most one hit and the rest will have to be invalidated. The negative impact on hit rate will significantly grow with associativity. (Unless writes are quite infrequent vs. reads, reducing the associativity would probably help hit rate with the write-all-ways strategy, so for a given total cache capacity, direct-mapped might be the best choice if you insist on fully-non-blocking write-invalidate.) Even for a direct-mapped cache, the experimental evaluation given in the paper itself shows that write-invalidate has higher miss rate compare to the other evaluated write policies. So it's win only if the benefits of reducing latency and bandwidth demand outweighs the damage of high miss rate.
Also, as I said, write-allocate is very good for CPUs, especially when it's set-associative so you're spending more resources trying to get a higher hit-rate. You could maybe still implement write-allocate by triggering a fetch on miss, remembering where in the line you stored the data, and merging that with the old copy of the line when it arrives.
You don't want to defeat that by blowing away lines that didn't need to die.
Also, write-invalidate implies write-through even for write hits, because it could lose data if a line is ever dirty. But write-back is also very good in modern L1d caches to insulate larger/slower caches from the write bandwidth. (Especially if there's no per-core private L2 to separately reduce total traffic to shared caches.) However, AMD Bulldozer-family did have a write-through L1d with a small 4k write-buffer between it and a write-back L2. This was generally considered a failed experiment or weak point of the design, and they dropped it in favour of a standard write-back write-allocate L1d for Zen. When use write-through cache policy for pages.
So in summary, write-invalidate is incompatible with several things that modern mainstream CPU designs have settled on as the best options, that you'll find in most mainstream CPU designs
write-allocate write policy
write-back (not write-through). https://en.wikipedia.org/wiki/Cache_(computing)#Writing_policies
set-associative (huge downsides that can only be partially mitigated by way-prediction)
store buffer to decouple store miss from execution, and allow memory parallelism. (Not strictly incompatible, but a store buffer makes it pointless. Necessary for OoO exec and widely used for in-order)
write-invalidate in cache-coherent SMP systems
You'd never consider using it in a single-chip multi-core CPU; spend more transistors on each core to get more of the low-hanging fruit before you start building more cores. e.g. a proper store buffer. Use some flavour of SMT if you want high throughput for multiple low-IPC threads that stall a lot.
But for multi-socket SMP, this could have made sense historically if you want to use multiple of the biggest single-core chip you can build, and that was still not big enough to just have a store buffer instead of this.
I guess it could even make sense to use a really "thin" direct-mapped write-through L1d in front of a private medium-sized write-back set-associative L2 that's still pretty fast. (Maybe call this an L0d cache because it can act like an unordered store buffer. The next-level cache will still see a lot of reads and writes from the low hit-rate of this small direct-mapped cache.)
Normally all caches (including L1d) are part of the same global coherency domain so writing into L1d cache can't happen until you have exclusive ownership. (Which you check for as part of the tag check.) But if this L1d / L0d is not like that, then it's not coherent and is more like a store buffer.
Of course, you need to queue the write-throughs for L2, and eventually stall when it can't keep up, so you're just adding complexity. The write-through to L2 mechanism would also need to deal with waiting for L2 to gain exclusive ownership of the line before writing (MESI Exclusive or Modified state). So this is very much just an unordered store buffer.
The case of writing to a line that hadn't made it to L2 yet is interesting: if it's an L0d write hit you effectively get store merging for free. You'd need per-word or per-byte needs-writeback bits (aka dirty bits) for this. Normally write-through would be sending along the write while the offset within line is still available, but if L2 isn't ready to accept it yet (e.g. because of a write miss) then you can't do that. This is morphing it into a write-combining buffer. Marking the whole line as needing write-back doesn't work because the unwritten parts are still invalid.
But if it's a write miss (same cache line, different tag bits) on a line that still hasn't finished write-back to L2, you have a big problem because you'd be invalidating a line that's still "dirty" (has the only copy of some older store data). You can't detect that before writing; the whole point is to write in parallel with checking tags.
It might be possible to still make this work: if the cache access is a read+write exchange that keeps the previous value in a one-word buffer (or whatever the max write size is), you still have all the data. Stall everything (including writeback of this line so you don't make wrong data globally visible in coherent L2 cache). Then exchange back, wait for the old state of that L0d line to actually write back to that address, then store the tmp buffer into L0d and update the tag and needs-writeback bits to reflect this store. So aliasing between nearby stores becomes extra costly and stalls the pipeline. Or maybe you can let non-memory instructions continue and only stall execution at the next load or store. (If you have the transistor budget to do much of that stall-avoidance, you can probably just use a completely different strategy, like having a store buffer and a normal L1d.)
To be usable (assuming you work around the dirty-store-miss problem), you'd need some way to track relative order of stores (and loads). If that's as simplistic as making sure every entry in the entire L0d has finished its write-through process before allowing another write, then even store-store barriers will be very expensive. The less order-tracking a CPU does, the more expensive barriers have to be (flush more stuff to make sure).
Related
The Intel optimization manual talks about the number of store buffers that exist in many parts of the processor, but do not seem to talk about the size of the store buffers. Is this public information or is the size of a store buffer kept as a microarchitectural detail?
The processors I am looking into are primarily Broadwell and Skylake, but information about others would be nice as well.
Also, what do store buffers do, exactly?
Related: what is a store buffer? and a beginner-friendly (but detailed) intro to the concept of buffers in Can a speculatively executed CPU branch contain opcodes that access RAM? which I highly recommend reading for CPU-architecture background on why we need them and what they do (decouple execution from commit to L1d / cache misses, and allow speculative exec of stores without making speculation visible in coherent cache.)
Also How do the store buffer and Line Fill Buffer interact with each other? has a good description of the steps in executing a store instruction and how it eventually commits to L1d cache.
The store buffer as a whole is composed of multiple entries.
Each core has its own store buffer1 to decouple execution and retirement from commit into L1d cache. Even an in-order CPU benefits from a store buffer to avoid stalling on cache-miss stores, because unlike loads they just have to become visible eventually. (No practical CPUs use a sequential-consistency memory model, so at least StoreLoad reordering is allowed, even in x86 and SPARC-TSO).
For speculative / out-of-order CPUs, it also makes it possible roll back a store after detecting an exception or other mis-speculation in an older instruction, without speculative stores ever being globally visible. This is obviously essential for correctness! (You can't roll back other cores, so you can't let them see your store data until it's known to be non-speculative.)
When both logical cores are active (hyperthreading), Intel partitions the store buffer in two; each logical core gets half. Loads from one logical core only snoop its own half of the store buffer2. What will be used for data exchange between threads are executing on one Core with HT?
The store buffer commits data from retired store instructions into L1d as fast as it can, in program order (to respect x86's strongly-ordered memory model3). Requiring stores to commit as they retire would unnecessarily stall retirement for cache-miss stores. Retired stores still in the store buffer are definitely going to happen and can't be rolled back, so they can actually hurt interrupt latency. (Interrupts aren't technically required to be serializing, but any stores done by an IRQ handler can't become visible until after existing pending stores are drained. And iret is serializing, so even in the best case the store buffer drains before returning.)
It's a common(?) misconception that it has to be explicitly flushed for data to become visible to other threads. Memory barriers don't cause the store buffer to be flushed, full barriers make the current core wait until the store buffer drains itself, before allowing any later loads to happen (i.e. read L1d). Atomic RMW operations have to wait for the store buffer to drain before they can lock a cache line and do both their load and store to that line without allowing it to leave MESI Modified state, thus stopping any other agent in the system from observing it during the atomic operation.
To implement x86's strongly ordered memory model while still microarchitecturally allowing early / out-of-order loads (and later checking if the data is still valid when the load is architecturally allowed to happen), load buffer + store buffer entries collectively form the Memory Order Buffer (MOB). (If a cache line isn't still present when the load was allowed to happen, that's a memory-order mis-speculation.) This structure is presumably where mfence and locked instructions can put a barrier that blocks StoreLoad reordering without blocking out-of-order execution. (Although mfence on Skylake does block OoO exec of independent ALU instructions, as an implementation detail.)
movnt cache-bypassing stores (like movntps) also go through the store buffer, so they can be treated as speculative just like everything else in an OoO exec CPU. But they commit directly to an LFB (Line Fill Buffer), aka write-combining buffer, instead of to L1d cache.
Store instructions on Intel CPUs decode to store-address and store-data uops (micro-fused into one fused-domain uop). The store-address uop just writes the address (and probably the store width) into the store buffer, so later loads can set up store->load forwarding or detect that they don't overlap. The store-data uop writes the data.
Store-address and store-data can execute in either order, whichever is ready first: the allocate/rename stage that writes uops from the front-end into the ROB and RS in the back end also allocates a load or store buffer for load or store uops at issue time. Or stalls until one is available. Since allocation and commit happen in-order, that probably means older/younger is easy to keep track of because it can just be a circular buffer that doesn't have to worry about old long-lived entries still being in use after wrapping around. (Unless cache-bypassing / weakly-ordered NT stores can do that? They can commit to an LFB (Line Fill Buffer) out of order. Unlike normal stores, they commit directly to an LFB for transfer off-core, rather than to L1d.)
but what is the size of an entry?
Store buffer sizes are measured in entries, not bits.
Narrow stores don't "use less space" in the store buffer, they still use exactly 1 entry.
Skylake's store buffer has 56 entries (wikichip), up from 42 in Haswell/Broadwell, and 36 in SnB/IvB (David Kanter's HSW writeup on RealWorldTech has diagrams). You can find numbers for most earlier x86 uarches in Kanter's writeups on RWT, or Wikichip's diagrams, or various other sources.
SKL/BDW/HSW also have 72 load buffer entries, SnB/IvB have 64. This is the number of in-flight load instructions that either haven't executed or are waiting for data to arrive from outer caches.
The size in bits of each entry is an implementation detail that has zero impact on how you optimize software. Similarly, we don't know the size in bits of of a uop (in the front-end, in the ROB, in the RS), or TLB implementation details, or many other things, but we do know how many ROB and RS entries there are, and how many TLB entries of different types there are in various uarches.
Intel doesn't publish circuit diagrams for their CPU designs and (AFAIK) these sizes aren't generally known, so we can't even satisfy our curiosity about design details / tradeoffs.
Write coalescing in the store buffer:
Back-to-back narrow stores to the same cache line can (probably?) be combined aka coalesced in the store buffer before they commit, so it might only take one cycle on a write port of L1d cache to commit multiple stores.
We know for sure that some non-x86 CPUs do this, and we have some evidence / reason to suspect that Intel CPUs might do this. But if it happens, it's limited. #BeeOnRope and I currently think Intel CPUs probably don't do any significant merging. And if they do, the most plausible case is that entries at the end of the store buffer (ready to commit to L1d) that all go to the same cache line might merge into one buffer, optimizing commit if we're waiting for an RFO for that cache line. See discussion in comments on Are two store buffer entries needed for split line/page stores on recent Intel?. I proposed some possible experiments but haven't done them.
Earlier stuff about possible store-buffer merging:
See discussion starting with this comment: Are write-combining buffers used for normal writes to WB memory regions on Intel?
And also Unexpectedly poor and weirdly bimodal performance for store loop on Intel Skylake may be relevant.
We know for sure that some weakly-ordered ISAs like Alpha 21264 did store coalescing in their store buffer, because the manual documents it, along with its limitations on what it can commit and/or read to/from L1d per cycle. Also PowerPC RS64-II and RS64-III, with less detail, in docs linked from a comment here: Are there any modern CPUs where a cached byte store is actually slower than a word store?
People have published papers on how to do (more aggressive?) store coalescing in TSO memory models (like x86), e.g. Non-Speculative Store Coalescing in Total Store Order
Coalescing could allow a store-buffer entry to be freed before its data commits to L1d (presumably only after retirement), if its data is copied to a store to the same line. This could only happen if no stores to other lines separate them, or else it would cause stores to commit (become globally visible) out of program order, violating the memory model. But we think this can happen for any 2 stores to the same line, even the first and last byte.
A problem with this idea is that SB entry allocation is probably a ring buffer, like the ROB. Releasing entries out of order would mean hardware would need to scan every entry to find a free one, and then if they're reallocated out of order then they're not in program order for later stores. That could make allocation and store-forwarding much harder so it's probably not plausible.
As discussed in
Are two store buffer entries needed for split line/page stores on recent Intel?, it would make sense for an SB entry to hold all of one store even if it spans a cache-line boundary. Cache line boundaries become relevant when committing to L1d cache on leaving the SB. We know that store-forwarding can work for stores that split across a cache line. That seems unlikely if they were split into multiple SB entries in the store ports.
Terminology: I've been using "coalescing" to talk about merging in the store buffer, vs. "write combining" to talk about NT stores that combine in an LFB before (hopefully) doing a full-line write with no RFO. Or stores to WC memory regions which do the same thing.
This distinction / convention is just something I made up. According to discussion in comments, this might not be standard computer architecture terminology.
Intel's manuals (especially the optimization manual) are written over many years by different authors, and also aren't consistent in their terminology. Take most parts of the optimization manual with a grain of salt especially if it talks about Pentium4. The new sections about Sandybridge and Haswell are reliable, but older parts might have stale advice that's only / mostly relevant for P4 (e.g. inc vs. add 1), or the microarchitectural explanations for some optimization rules might be confusing / wrong. Especially section 3.6.10 Write Combining. The first bullet point about using LFBs to combine stores while waiting for lines to arrive for cache-miss stores to WB memory just doesn't seem plausible, because of memory-ordering rules. See discussion between me and BeeOnRope linked above, and in comments here.
Footnote 1:
A write-combining cache to buffer write-back (or write-through) from inner caches would have a different name. e.g. Bulldozer-family uses 16k write-through L1d caches, with a small 4k write-back buffer. (See Why do L1 and L2 Cache waste space saving the same data? for details and links to even more details. See Cache size estimation on your system? for a rewrite-an-array microbenchmark that slows down beyond 4k on a Bulldozer-family CPU.)
Footnote 2: Some POWER CPUs let other SMT threads snoop retired stores in the store buffer: this can cause different threads to disagree about the global order of stores from other threads. Will two atomic writes to different locations in different threads always be seen in the same order by other threads?
Footnote 3: non-x86 CPUs with weak memory models can commit retired stores in any order, allowing more aggressive coalescing of multiple stores to the same line, and making a cache-miss store not stall commit of other stores.
If one has a 64 byte buffer that is heavily read/written to then it's likely that it'll be kept in L1; but is there any way to force that behaviour?
As in, give one core exclusive access to those 64 bytes and tell it not to sync the data with other cores nor the memory controller so that those 64 bytes always live in one core's L1 regardless of whether or not the CPU thinks it's used often enough.
No, x86 doesn't let you do this. You can force evict with clfushopt, or (on upcoming CPUs) for just write-back without evict with clwb, but you can't pin a line in cache or disable coherency.
You can put the whole CPU (or a single core?) into cache-as-RAM (aka no-fill) mode to disable sync with the memory controller, and disable ever writing back the data. Cache-as-Ram (no fill mode) Executable Code. It's typically used by BIOS / firmware in early boot before configuring the memory controllers. It's not available on a per-line basis, and is almost certainly not practically useful here. Fun fact: leaving this mode is one of the use-cases for invd, which drops cached data without writeback, as opposed to wbinvd.
I'm not sure if no-fill mode prevents eviction from L1d to L3 or whatever; or if data is just dropped on eviction. So you'd just have to avoid accessing more than 7 other cache lines that alias the one you care about in your L1d, or the equivalent for L2/L3.
Being able to force one core to hang on to a line of L1d indefinitely and not respond to MESI requests to write it back / share it would make the other cores vulnerable to lockups if they ever touched that line. So obviously if such a feature existed, it would require kernel mode. (And with HW virtualization, require hypervisor privilege.) It could also block hardware DMA (because modern x86 has cache-coherent DMA).
So supporting such a feature would require lots of parts of the CPU to handle indefinite delays, where currently there's probably some upper bound, which may be shorter than a PCIe timeout, if there is such a thing. (I don't write drivers or build real hardware, just guessing about this).
As #fuz points out, a coherency-violating instruction (xdcbt) was tried on PowerPC (in the Xbox 360 CPU), with disastrous results from mis-speculated execution of the instruction. So it's hard to implement.
You normally don't need this.
If the line is frequently used, LRU replacement will keep it hot. And if it's lost from L1d at frequent enough intervals, then it will probably stay hot in L2 which is also on-core and private, and very fast, in recent designs (Intel since Nehalem). Intel's inclusive L3 on CPUs other than Skylake-AVX512 means that staying in L1d also means staying in L3.
All this means that full cache misses all the way to DRAM are very unlikely with any kind of frequency for a line that's heavily used by one core. So throughput shouldn't be a problem. I guess you could maybe want this for realtime latency, where the worst-case run time for one call of a function mattered. Dummy reads from the cache line in some other part of the code could be helpful in keeping it hot.
However, if pressure from other cores in L3 cache causes eviction of this line from L3, Intel CPUs with an inclusive L3 also have to force eviction from inner caches that still have it hot. IDK if there's any mechanism to let L3 know that a line is heavily used in a core's L1d, because that doesn't generate any L3 traffic.
I'm not aware of this being much of a problem in real code. L3 is highly associative (like 16 or 24 way), so it takes a lot of conflicts before you'd get an eviction. L3 also uses a more complex indexing function (like a real hash function, not just modulo by taking a contiguous range of bits). In IvyBridge and later, it also uses an adaptive replacement policy to mitigate eviction from touching a lot of data that won't be reused often. http://blog.stuffedcow.net/2013/01/ivb-cache-replacement/.
See also Which cache mapping technique is used in intel core i7 processor?
#AlexisWilke points out that you could maybe use vector register(s) instead of a line of cache, for some use-cases. Using ymm registers as a "memory-like" storage location. You could globally dedicate some vector regs to this purpose. To get this in gcc-generated code, maybe use -ffixed-ymm8, or declare it as a volatile global register variable. (How to inform GCC to not use a particular register)
Using ALU instructions or store-forwarding to get data to/from the vector reg will give you guaranteed latency with no possibility of data-cache misses. But code-cache misses are still a problem for extremely low latency.
There is no direct way to achieve that on Intel and AMD x86 processors, but you can get pretty close with some effort. First, you said you're worried that the cache line might get evicted from the L1 because some other core might access it. This can only happen in the following situations:
The line is shared, and therefore, it can be accessed by multiple agents in the system concurrently. If another agent attempts to read the line, its state will change from Modified or Exclusive to Shared. That is, it will state in the L1. If, on the other hand, another agent attempts to write to the line, it has to be invalidated from the L1.
The line can be private or shared, but the thread got rescheduled by the OS to run on another core. Similar to the previous case, if it attempts to read the line, its state will change from Modified or Exclusive to Shared in both L1 caches. If it attempts to write to the line, it has to be invalidated from the L1 of the previous core on which it was running.
There are other reasons why the line may get evicted from the L1 as I will discuss shortly.
If the line is shared, then you cannot disable coherency. What you can do, however, is make a private copy of it, which effectively does disable coherency. If doing that may lead to faulty behavior, then the only thing you can do is to set the affinity of all threads that share the line to run on the same physical core on a hyperthreaded (SMT) Intel processor. Since the L1 is shared between the logical cores, the line will not get evicted due to sharing, but it can still get evicted due to other reasons.
Setting the affinity of a thread does not guarantee though that other threads cannot get scheduled to run on the same core. To reduce the probability of scheduling other threads (that don't access the line) on the same core or rescheduling the thread to run on other physical cores, you can increase the priority of the thread (or all the threads that share the line).
Intel processors are mostly 2-way hyperthreaded, so you can only run two threads that share the line at a time. so if you play with the affinity and priority of the threads, performance can change in interesting ways. You'll have to measure it. Recent AMD processors also support SMT.
If the line is private (only one thread can access it), a thread running on a sibling logical core in an Intel processor may cause the line to be evicted because the L1 is competitively shared, depending on its memory access behavior. I will discuss how this can be dealt with shortly.
Another issue is interrupts and exceptions. On Linux and maybe other OSes, you can configure which cores should handle which interrupts. I think it's OK to map all interrupts to all other cores, except the periodic timer interrupt whose interrupt handler's behavior is OS-dependent and it may not be safe to play with it. Depending on how much effort you want to spend on this, you can perform carefully designed experiments to determine the impact of the timer interrupt handler on the L1D cache contents. Also you should avoid exceptions.
I can think of two reasons why a line might get invalidated:
A (potentially speculative) RFO with intent for modification from another core.
The line was chosen to be evicted to make space for another line. This depends on the design of the cache hierarchy:
The L1 cache placement policy.
The L1 cache replacement policy.
Whether lower level caches are inclusive or not.
The replacement policy is commonly not configurable, so you should strive to avoid conflict L1 misses, which depends on the placement policy, which depends on the microarchitecture. On Intel processors, the L1D is typically both virtually indexed and physically indexed because the bits used for the index don't require translation. Since you know the virtual addresses of all memory accesses, you can determine which lines would be allocated from which cache set. You need to make sure that the number of lines mapped to the same set (including the line you don't want it to be evicted) does not exceed the associativity of the cache. Otherwise, you'd be at the mercy of the replacement policy. Note also that an L1D prefetcher can also change the contents of the cache. You can disable it on Intel processors and measure its impact in both cases. I cannot think of an easy way to deal with inclusive lower level caches.
I think the idea of "pinning" a line in the cache is interesting and can be useful. It's a hybrid between caches and scratch pad memories. The line would be like a temporary register mapped to the virtual address space.
The main issue here is that you want to both read from and write to the line, while still keeping it in the cache. This sort of behavior is currently not supported.
If new CPUs had a cache buffer which was only committed to the actual CPU cache if the instructions are ever committed would attacks similar to Meltdown still be possible?
The proposal is to make speculative execution be able to load from memory, but not write to the CPU caches until they are actually committed.
TL:DR: yes I think it would solve Spectre (and Meltdown) in their current form (using a flush+read cache-timing side channel to copy the secret data from a physical register), but probably be too expensive (in power cost, and maybe also performance) to be a likely implementation.
But with hyperthreading (or more generally any SMT), there's also an ALU / port-pressure side-channel if you can get mis-speculation to run data-dependent ALU instructions with the secret data, instead of using it as an array index. The Meltdown paper discusses this possibility before focusing on the flush+reload cache-timing side-channel. (It's more viable for Meltdown than Spectre, because you have much better control of the timing of when the the secret data is used).
So modifying cache behaviour doesn't block the attacks. It would take away the reliable side-channel for getting the secret data into the attacking process, though. (i.e. ALU timing has higher noise and thus lower bandwidth to get the same reliability; Shannon's noisy channel theorem), and you have to make sure your code runs on the same physical core as the code under attack.
On CPUs without SMT (e.g. Intel's desktop i5 chips), the ALU timing side-channel is very hard to use with Spectre, because you can't directly use perf counters on code you don't have privilege for. (But Meltdown could still be exploited by timing your own ALU instructions with Linux perf, for example).
Meltdown specifically is much easier to defend against, microarchitecturally, with simpler and cheaper changes to the hard-wired parts of the CPU that microcode updates can't rewire.
You don't need to block speculative loads from affecting cache; the change could be as simple as letting speculative execution continue after a TLB-hit load that will fault if it reaches retirement, but with the value used by speculative execution of later instructions forced to 0 because of the failed permission check against the TLB entry.
So the mis-speculated (after the faulting load of secret) touch array[secret*4096] load would always make the same cache line hot, with no secret-data-dependent behaviour. The secret data itself would enter cache, but not a physical register. (And this stops ALU / port-pressure side-channels, too.)
Stopping the faulting load from even bringing the "secret" line into cache in the first place could make it harder to tell the difference between a kernel mapping and an unmapped page, which could possibly help protect against user-space trying to defeat KASLR by finding which virtual addresses the kernel has mapped. But that's not Meltdown.
Spectre
Spectre is the hard one because the mis-speculated instructions that make data-dependent modifications to microarchitectural state do have permission to read the secret data. Yes, a "load queue" that works similarly to the store queue could do the trick, but implementing it efficiently could be expensive. (Especially given the cache coherency problem that I didn't think of when I wrote this first section.)
(There are other ways of implementing the your basic idea; maybe there's even a way that's viable. But extra bits on L1D lines to track their status has downsides and isn't obviously easier.)
The store queue tracks stores from execution until they commit to L1D cache. (Stores can't commit to L1D until after they retire, because that's the point at which they're known to be non-speculative, and thus can be made globally visible to other cores).
A load queue would have to store whole incoming cache lines, not just the bytes that were loaded. (But note that Skylake-X can do 64-byte ZMM stores, so its store-buffer entries do have to be the size of a cache line. But if they can borrow space from each other or something, then there might not be 64 * entries bytes of storage available, i.e. maybe only the full number of entries is usable with scalar or narrow-vector stores. I've never read anything about a limitation like this, so I don't think there is one, but it's plausible)
A more serious problem is that Intel's current L1D design has 2 read ports + 1 write port. (And maybe another port for writing lines that arrive from L2 in parallel with committing a store? There was some discussion about that on Unexpectedly poor and weirdly bimodal performance for store loop on Intel Skylake.)
If your loaded data can't enter L1D until after the loads retire, then they're probably going to be competing for the same write port that stores use.
Loads that hit in L1D can still come directly from L1D, though, and loads that hit in the memory-order-buffer could still be executed at 2 per clock. (The MOB would now include this new load queue as well as the usual store queue + markers for loads to maintain x86 memory ordering semantics). You still need both L1D read ports to maintain performance for code that doesn't touch a lot of new memory, and mostly is reloading stuff that's been hot in L1D for a while.
This would make the MOB about twice as large (in terms of data storage), although it doesn't need any more entries. As I understand it, the MOB in current Intel CPUs is composed of the individual load-buffer and store-buffer entries. (Haswell has 72 and 42 respectively).
Hmm, a further complication is that the load data in the MOB has to maintain cache coherency with other cores. This is very different from store data, which is private and hasn't become globally visible / isn't part of the global memory order and cache coherency until it commits to L1D.
So this proposed "load queue" implementation mechanism for your idea is probably not feasible without tweaks: it would have to be checked by invalidation-requests from other cores, so that's another read-port needed in the MOB.
Any possible implementation would have the problem of needing to later commit to L1D like a store. I think it would be a significant burden not to be able to evict + allocate a new line when it arrived from off-core.
(Even allowing speculative eviction but not speculative replacement from conflicts leaves open a possible cache-timing attack. You'd prime all the lines and then do a load that would evict one from one set of lines or another, and find which line was evicted instead of which one was fetched using a similar cache-timing side channel. So using extra bits in L1D to find / evict lines loaded during recovery from mis-speculation wouldn't eliminate this side-channel.)
Footnote: all instructions are speculative. This question is worded well, but I think many people reading about OoO exec and thinking about Meltdown / Spectre fall into this trap of confusing speculative execution with mis-speculation.
Remember that all instructions are speculative when they're executed. It's not known to be correct speculation until retirement. Meltdown / Spectre depend on accessing secret data and using it during mis-speculation. But the basis of current OoO CPU designs is that you don't know whether you've speculated correctly or not; everything is speculative until retirement.
Any load or store could potentially fault, and so can some ALU instructions (e.g. floating point if exceptions are unmasked), so any performance cost that applies "only when executing speculatively" actually applies all the time. This is why stores can't commit from the store queue into L1D until after the store uops have retired from the out-of-order CPU core (with the store data in the store queue).
However, I think conditional and indirect branches are treated specially, because they're expected to mis-speculate some of the time, and optimizing recovery for them is important. Modern CPUs do better with branches than just rolling back to the current retirement state when a mispredict is detected, I think using a checkpoint buffer of some sort. So out-of-order execution for instructions before the branch can continue during recovery.
But loop and other branches are very common, so most code executes "speculatively" in this sense, too, with at least one branch-rollback checkpoint not yet verified as correct speculation. Most of the time it's correct speculation, so no rollback happens.
Recovery for mis-speculation of memory ordering or faulting loads is a full pipeline-nuke, rolling back to the retirement architectural state. So I think only branches consume the branch checkpoint microarchitectural resources.
Anyway, all of this is what makes Spectre so insidious: the CPU can't tell the difference between mis-speculation and correct speculation until after the fact. If it knew it was mis-speculating, it would initiate rollback instead of executing useless instructions / uops. Indirect branches are not rare, either (in user-space); every DLL or shared library function call uses one in normal executables on Windows and Linux.
I suspect the overhead from buffering and committing the buffer would render the specEx/caching useless?
This is purely speculative (no pun intended) - I would love to see someone with a lower level background weigh in this!
Is there any benefit to use cache if there is read miss for every access?
My question aims at a better understanding of caches.
Read miss for every access can also happen during cold start, am I right?
If you are doing only reads and you miss all levels of cache on every read, then by definition caches didn't help. You paid extra in power and latency to check each level of cache, and extra power and (probably) latency to load a whole cache line of data which will never be used (by definition) except for the data you read since all your accesses miss.
You didn't say you are doing only reads though. So of course caches can help in the case that your reads all miss but some of your writes hit.
Perhaps you meant that the read-portion of all accesses, both reads and writes, misses - where the read-portion of a write is the read-for-ownership access present on most cache-based systems where a cache-line must be read into cache before (part of it) can be written. In that case, the cache probably also didn't help and probably hurt.
Read miss for every access can also happen during cold start, am I right?
No, almost never. Some reads will miss, but those will bring in adjacent data on the same cache line which will often result in later hits (spatial locality). Many reads will go back to the same location even in a cold start (temporal locality) which will also often hit. Even beyond the dynamics of a single cache line, modern CPUs often offer hardware prefetching which will recognize certain access patterns and will bring in data before you need it which can result in hits even the first time you access a cache line.
Finally, on most general purpose hardware there you usually cannot decide to simply "not use the caches" so as a practical matter you pay the built-in costs of caching even if your hit rate is low.
That said, sometimes, when you know your access pattern you can provide hints to the CPU. For example, x86 CPUs provide "non-temporal store" instructions which essentially bypass the caches when used - meaning that the stored cache line won't be cached. This is useful not necessarily to speed up the store itself (which still largely pays the price of the cache hierarchy which is baked into the hardware), but to avoid polluting the cache with data the developer knows will not soon be accessed.
I have encountered some Intel compiler intrinsic functions which I believe allow developers to bypass the cache?
http://software.intel.com/sites/products/documentation/doclib/stdxe/2013/composerxe/compiler/fortran-mac/GUID-AF42A867-B796-4D29-8FED-C20193FD87E0.htm
I have also come across the GCC compiler prefetch keyword, although I cannot admit to fully appreciating what this does.
With the above in mind I wondered if any members could either elaborate on the above (which I badly described) or provide other techniques which allow the developer to have close control over which data (or instructions) is/isn't loaded in the CPU cache?
This page contains a lot of information about all intrinsics:
Intel Intrinsics Guide
The series of instructions that will write data to memory, avoiding cache evictions are generally named _mm_stream_.... As the name implies, these are ideal for applications that write a large stream of data that is basically contiguous in memory and unlikely to be accessed again in the near future. So, for example, if you are mixing audio buffers and producing a single waveform output this would work well.
One of the keys to using these instructions effectively is taking advantage of write combining. If your write locations are scattered throughout memory, these instructions will stall as badly, or possibly worse than any other kind of memory storage instruction you attempt. Since these writes do not wind up in cache, if you're not filling an entire write buffer then essentially your operation becomes a write-through operation, requiring a stall until the write is completed. If you are writing contiguous memory locations then write combining will apply, and make your data writes much more efficient.
The flip side of that coin is prefetching. Prefetching tells the system to start pulling a memory address into the desired level of cache so that by the time the memory read is complete, you are ready to use the data. This is much harder to use, and requires an appropriate data "stride" which takes into account the cache sizes, cache line size, and the number of instructions which can execute before the memory read completes. Using the hinting parameter, you can "suggest" that the data goes into the L1, L2, or L3 cache, or that it is "non-temporal", meaning that you're just going to use it once and it should be evicted first before any other cache evictions. The hardware has its own prefetching heuristics that work well for most problems without explicit prefetching instructions, but the classic counter-example is a matrix transpose:
Prefetching examples
Prefetching is generally very difficult to use effectively except in some very specific cases like this. Without a more specific problem statement from you, this is about all I can provide.