[llvm-dev] top-down vs. bottom-up list scheduling

[Matthias Braun via llvm-dev]

Some comments:
- It's all heuristics, so you may be lucky/unlycky in any configuration. I assume you know how to read -debug-only=machine-scheduler output and the GenericScheduler::tryCandidate() code to figure out how most decisions are made.
- In my experience bottom-up works better when optimizing for register pressure while top-down tends to work better when optimizing for latencies/stall reduction.
- The scheduler has a couple rules dealing with pressure. Hitting any of these limits will make it pick pressure reducing nodes more aggressively (look for tryPressure() in the tryCandidate() code)
    - Hitting the target limits (number of available registers)
    - Hitting the maximum of the region before scheduling
    - Generally attempt to minimmize pressure (this has lower priority though)

In the past I looked at some crypto code that also was carefully tuned by a human and that turned out to be very tricky for the heuristics to get right because most values had multiple users.
At the time I had a patch that would revert all scheduling decisions if it turned out that the scheduler couldn't find a solution with better or equal register pressure. It wasn't received too enthusiastically and I ended up tweaking some heuristics instead. But we may start that discussion again if you cannot find a know to tune the heuristic for your case.

- Matthias

> 
> Hello List!
> 
> I am looking at top-down vs. bottom-up list scheduling for simple(r) in-order
> cores. First, for some context, below is a fairly representative pseudo-code
> example of the sort of DSP-like codes I am looking at:
> 
>  uint64_t foo(int *pA, int *pB, unsigned N, unsigned C) {
>    uint64_t sum = 0;
>    while (N-- > 0) {
>      A1 = *pA++;
>      A2 = *pA++;
>      B1 = *pB++;
>      B2 = *pB++;
>      ...
>      sum += ((uint64_t) A1 * B1) >> C;
>      sum += ((uint64_t) A2 * B2) >> C;
>      ...
>    }
>    return sum;
>  }
> 
> These kernels are very tight loops. In this sort of legacy codes it's not
> uncommon that loops are manually tuned and unrolled with the available
> registers in mind, so that all values just about fit in registers. In the
> example above, we read from input streams A and B, and do 2 multiply-accumulate
> operations.  The loop is unrolled 2 times in this example, but 4, 8 or 16 would
> more realistic, resulting in very high register pressure.
> 
> But legacy apps written in this way are not the only culprit; we see that with
> (aggressive) loop unrolling we can end up in exactly the same situation: the
> loopunroller does exactly what it needs to do, but it results in very high
> register pressure.
> 
> Here's the (obvious) problem: all live values in these loops should just about
> fit in registers, but suboptimal/wrong decisions are made resulting in a lot of
> spills/reloads; the machine scheduler is making the life of the register allocator
> very difficult. I am looking at regressions of about 30 - 40% for more
> than a handful of kernels, and am thus very interested in what I could do about
> this.
> 
> The first observation is that it looks like we default to bottom-up scheduling.
> Starting bottom-up, all these "sum" variables are scheduled first, and after
> that the loads (this is simplifying things a bit). And thus it looks like we
> create a lot of very long live-ranges, causing the problems mentioned above.
> When instead we start top-down, the loads are picked up first, then the MAC, and
> this repeated for all MACs. The result is a sequence LD, MAC, LD, MAC, etc.,
> which is let's say a sequence more in program-order, also with shorter
> live-ranges. This does exactly what I want for these sort of kernels, it generates
> exactly the code we want.
> 
> While playing with this bottom-up/top-down order, it didn't take long to see
> that the top-down approach is excellent for these kind of codes, but not for
> some other benchmarks, and so solving this issue not just a matter of
> defaulting to a new scheduling policy.
> 
> I am thinking about prototyping an approach where we start with the bottom-up
> approach (under a new misched option), but when a register-pressure/live-range
> trashhold value is reached, we bail and fall back to the top-down approach.
> This is my first rough idea, but I haven't looked at this problem for very
> long. My first few data points is suggesting this might be benificial, but I
> could be missing a lot here. And also I am sure that I am looking at an
> old/classic problem here and I'm sure others have looked at this problem
> before. Thus I am wondering if people have experiences/opinions on this.
> 
> Cheers,
> Sjoerd.
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