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performance - Understanding the impact of lfence on a loop with two long dependency chains, for increasing lengths

I was playing with the code in this answer, slightly modifying it:

BITS 64

GLOBAL _start

SECTION .text

_start:
 mov ecx, 1000000

.loop:

 ;T is a symbol defined with the CLI (-DT=...)

 TIMES T imul eax, eax
 lfence
 TIMES T imul edx, edx


 dec ecx
jnz .loop

 mov eax, 60           ;sys_exit
 xor edi, edi
 syscall

Without the lfence I the results I get are consistent with the static analysis in that answer.

When I introduce a single lfence I'd expect the CPU to execute the imul edx, edx sequence of the k-th iteration in parallel with the imul eax, eax sequence of the next (k+1-th) iteration.
Something like this (calling A the imul eax, eax sequence and D the imul edx, edx one):

|
| A
| D A
| D A
| D A
| ...
| D A
| D
|
V time

Taking more or less the same number of cycles but for one unpaired parallel execution.

When I measure the number of cycles, for the original and modified version, with taskset -c 2 ocperf.py stat -r 5 -e cycles:u '-x ' ./main-$T for T in the range below I get

T   Cycles:u    Cycles:u    Delta
    lfence      no lfence

10  42047564    30039060    12008504
15  58561018    45058832    13502186
20  75096403    60078056    15018347
25  91397069    75116661    16280408
30  108032041   90103844    17928197
35  124663013   105155678   19507335
40  140145764   120146110   19999654
45  156721111   135158434   21562677
50  172001996   150181473   21820523
55  191229173   165196260   26032913
60  221881438   180170249   41711189
65  250983063   195306576   55676487
70  281102683   210255704   70846979
75  312319626   225314892   87004734
80  339836648   240320162   99516486
85  372344426   255358484   116985942
90  401630332   270320076   131310256
95  431465386   285955731   145509655
100 460786274   305050719   155735555

Plotted data of above

How can the values of Cycles:u lfence be explained?
I would have expected them to be similar to those of Cycles:u no lfence since a single lfence should prevent only the first iteration from being executed in parallel for the two blocks.
I don't think it's due to the lfence overhead as I believe that should be constant for all Ts.

I'd like to fix what's wrong with my forma mentis when dealing with the static analysis of code.


Supporting repository with source files.

Question&Answers:os

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I think you're measuring accurately, and the explanation is microarchitectural, not any kind of measurement error.


I think your results for mid to low T support the conclusion that lfence stops the front-end from even issuing past the lfence until all earlier instructions retire, rather than having all the uops from both chains already issued and just waiting for lfence to flip a switch and let multiplies from each chain start to dispatch on alternating cycles.

(port1 would get edx,eax,empty,edx,eax,empty,... for Skylake's 3c latency / 1c throughput multiplier right away, if lfence didn't block the front-end, and overhead wouldn't scale with T.)

You're losing imul throughput when only uops from the first chain are in the scheduler because the front-end hasn't chewed through the imul edx,edx and loop branch yet. And for the same number of cycles at the end of the window when the pipeline is mostly drained and only uops from the 2nd chain are left.


The overhead delta looks linear up to about T=60. I didn't run the numbers, but the slope up to there looks reasonable for T * 0.25 clocks to issue the first chain vs. 3c-latency execution bottleneck. i.e. delta growing maybe 1/12th as fast as total no-lfence cycles.

So (given the lfence overhead I measured below), with T<60:

no_lfence cycles/iter ~= 3T                  # OoO exec finds all the parallelism
lfence    cycles/iter ~= 3T + T/4 + 9.3      # lfence constant + front-end delay
                delta ~=      T/4 + 9.3

@Margaret reports that T/4 is a better fit than 2*T / 4, but I would have expected T/4 at both the start and end, for a total of 2T/4 slope of the delta.


After about T=60, delta grows much more quickly (but still linearly), with a slope about equal to the total no-lfence cycles, thus about 3c per T. I think at that point, the scheduler (Reservation Station) size is limiting the out-of-order window. You probably tested on a Haswell or Sandybridge/IvyBridge, (which have a 60-entry or 54-entry scheduler respectively. Skylake's is 97 entry.

The RS tracks un-executed uops. Each RS entry holds 1 unfused-domain uop that's waiting for its inputs to be ready, and its execution port, before it can dispatch and leave the RS1.

After an lfence, the front-end issues at 4 per clock while the back-end executes at 1 per 3 clocks, issuing 60 uops in ~15 cycles, during which time only 5 imul instructions from the edx chain have executed. (There's no load or store micro-fusion here, so every fused-domain uop from the front-end is still only 1 unfused-domain uop in the RS2.)

For large T the RS quickly fills up, at which point the front-end can only make progress at the speed of the back-end. (For small T, we hit the next iteration's lfence before that happens, and that's what stalls the front-end). When T > RS_size, the back-end can't see any of the uops from the eax imul chain until enough back-end progress through the edx chain has made room in the RS. At that point, one imul from each chain can dispatch every 3 cycles, instead of just the 1st or 2nd chain.

Remember from the first section that time spent just after lfence only executing the first chain = time just before lfence executing only the second chain. That applies here, too.

We get some of this effect even with no lfence, for T > RS_size, but there's opportunity for overlap on both sides of a long chain. The ROB is at least twice the size of the RS, so the out-of-order window when not stalled by lfence should be able to keep both chains in flight constantly even when T is somewhat larger than the scheduler capacity. (Remember that uops leave the RS as soon as they've executed. I'm not sure if that means they have to finish executing and forward their result, or merely start executing, but that's a minor difference here for short ALU instructions. Once they're done, only the ROB is holding onto them until they retire, in program order.)

The ROB and register-file shouldn't be limiting the out-of-order window size (http://blog.stuffedcow.net/2013/05/measuring-rob-capacity/) in this hypothetical situation, or in your real situation. They should both be plenty big.


Blocking the front-end is an implementation detail of lfence on Intel's uarches. The manual only says that later instructions can't execute. That wording would allow the front-end to issue/rename them all into the scheduler (Reservation Station) and ROB while lfence is still waiting, as long as none are dispatched to an execution unit.

So a weaker lfence would maybe have flat overhead up to T=RS_size, then the same slope as you see now for T>60. (And the constant part of the overhead might be lower.)

Note that guarantees about speculative execution of conditional/indirect branches after lfence apply to execution, not (as far as I know) to code-fetch. Merely triggering code-fetch is not (AFAIK) useful to a Spectre or Meltdown attack. Possibly a timing side-channel to detect how it decodes could tell you something about the fetched code...

I think AMD's LFENCE is at least as strong on actual AMD CPUs, when the relevant MSR is enabled. (Is LFENCE serializing on AMD processors?).


Extra lfence overhead:

Your results are interesting, but it doesn't surprise me at all that there's significant constant overhead from lfence itself (for small T), as well as the component that scales with T.

Remember that lfence doesn't allow later instructions to start until earlier instructions have retired. This is probably at least a couple cycles / pipeline-stages later than when their results are ready for bypass-fowarding to other execution units (i.e. the normal latency).

So for small T, it's definitely significant that you add extra latency into the chain by requiring the result to not only be ready, but also written back to the register file.

It probably takes an extra cycle or so for lfence to allow the issue/rename stage to start operating again after detecting retirement of the last instruction before it. The issue/rename process takes multiple stages (cycles), and maybe lfence blocks at the start of this, instead of in the very last step before uops are added into the OoO part of the core.

Even back-to-back lfence itself has 4 cycle throughput on SnB-family, according to Agner Fog's testing. Agner Fog reports 2 fused-domain uops (no unfused), but on Skylake I measure it at 6 fused-domain (still no unfused) if I only have 1 lfence. But with more lfence back-to-back, it's fewer uops! Down to ~2 uops per lfence with many back-to-back, which is how Agner measures.

lfence/dec/jnz (a tight loop with no work) runs at 1 iteration per ~10 cycles on SKL, so that might give us an idea of the real extra latency that lfence adds to the dep chains even without the front-end and RS-full bottlenecks.

Measuring lfence overhead with only one dep chain, OoO exec being irrelevant:

.loop:
    ;mfence                  ; mfence here:  ~62.3c (with no lfence)
    lfence                   ; lfence here:  ~39.3c
    times 10 imul eax,eax    ; with no lfence: 30.0c
    ; lfence                 ; lfence here:  ~39.6c
    dec   ecx
    jnz   .loop

Without lfence, runs at the expected 30.0c per iter. With lfence, runs at ~39.3c per iter, so lfence effectively added ~9.3c of "extra latency" to the critical path dep chain. (And 6 extra fused-domain uops).

With lfence after the imul chain, right before the loop-branch, it's slightly slower. But not a whole cycle slower, so that would indicate that the front-end is issuing the loop-branch + and imul in a single issue-group after lfence allows execution to resume. That being the case, IDK why it's slower. It's not from branch misses.


Getting the behaviour you were expecting:

Interleave the chains in program order, like @BeeOnRope suggests in comments, doesn't require out-of-order execution to exploit the ILP, so it's pretty trivial:

.loop:
    lfence      ; at the top of the loop is the lowest-overhead place.

%rep T
    imul   eax,eax
    imul   edx,edx
%endrep

    dec     ecx
    jnz    .loop

You could put pairs of short times 8 imul chains inside a %rep to let OoO exec have an easy time.


Footnote 1: How the front-end / RS / ROB interact

My mental model is that the issue/rename/allocate stages in the front-end add new uops to both the RS and the ROB at the same time.

Uops leave the RS after executing, but stay in the ROB until in-order retirement. The ROB can be large because it's never scanned out-of-order to find the first-ready uop, only scanned in-order to check if the oldest uop(s) have finished executing and thus are ready to retire.

(I assume the ROB is physically a circular buffer with start/end indices, not a queue which actually copies uops to the right every cycle. But just think of it as a queue / list with a fixed max size, where the front-end adds uops at the front, and the retirement logic retires/commits uops from the end as long as they're fully executed, up to some per-cycle per-hyperthread retirement limit which is not usually a bottleneck. Skylake did increase it for better Hyperthreading, maybe to 8 per clock per logical thread. Perhaps retirement also means freeing physical registers which helps HT, because the ROB itself is statically partitioned when both threads are active. That's why retirement limits are per logical thread.)

Uops like nop, xor eax,eax, or lfence, which are handled in the front-end (don't need any execution units on any ports) are added only to the ROB, in an already-executed state. (A ROB entry presumably has a bit that marks it as ready to retire vs. still waiting for execution to complete. This is the state I'm talking about. For uops that did need an execution port, I assume the ROB bit is set via a completion port from the execution unit. And that the same completion-port signal frees its RS entry.)

Uops stay in the ROB from issue to retirement.

Uops stay in the RS from issue to execution. The RS can replay uops in a few cases, e.g. <a href="https://stackoverflow.com/questions/45128763/how-can-i-ac


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