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Before this patch, loads and stores were only tracked by their corresponding
queues in the LSUnit from dispatch until execute stage. In practice we should be
more conservative and assume that memory opcodes leave their queues at
retirement stage.
Basically, loads should leave the load queue only when they have completed and
delivered their data. We conservatively assume that a load is completed when it
is retired. Stores should be tracked by the store queue from dispatch until
retirement. In practice, stores can only leave the store queue if their data can
be written to the data cache.
This is mostly a mechanical change. With this patch, the retire stage notifies
the LSUnit when a memory instruction is retired. That would triggers the release
of LDQ/STQ entries. The only visible change is in memory tests for the bdver2
model. That is because bdver2 is the only model that defines the load/store
queue size.
This patch partially addresses PR39830.
Differential Revision: https://reviews.llvm.org/D68266
llvm-svn: 374034
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Now that we've moved to C++14, we no longer need the llvm::make_unique
implementation from STLExtras.h. This patch is a mechanical replacement
of (hopefully) all the llvm::make_unique instances across the monorepo.
llvm-svn: 369013
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InstrBuilder is not required to construct the default pipeline.
llvm-svn: 368275
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This patch adds an experimental stage named MicroOpQueueStage.
MicroOpQueueStage can be used to simulate a hardware micro-op queue (basically,
a decoupling queue between 'decode' and 'dispatch'). Users can specify a queue
size, as well as a optional MaxIPC (which - in the absence of a "Decoders" stage
- can be used to simulate a different throughput from the decoders).
This stage is added to the default pipeline between the EntryStage and the
DispatchStage only if PipelineOption::MicroOpQueue is different than zero. By
default, llvm-mca sets PipelineOption::MicroOpQueue to the value of hidden flag
-micro-op-queue-size.
Throughput from the decoder can be simulated via another hidden flag named
-decoder-throughput. That flag allows us to quickly experiment with different
frontend throughputs. For targets that declare a loop buffer, flag
-decoder-throughput allows users to do multiple runs, each time simulating a
different throughput from the decoders.
This stage can/will be extended in future. For example, we could add a "buffer
full" event to notify bottlenecks caused by backpressure. flag
-decoder-throughput would probably go away if in future we delegate to another
stage (DecoderStage?) the simulation of a (potentially variable) throughput from
the decoders. For now, flag -decoder-throughput is "good enough" to run some
simple experiments.
Differential Revision: https://reviews.llvm.org/D59928
llvm-svn: 357248
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This patch adds a new flag named -bottleneck-analysis to print out information
about throughput bottlenecks.
MCA knows how to identify and classify dynamic dispatch stalls. However, it
doesn't know how to analyze and highlight kernel bottlenecks. The goal of this
patch is to teach MCA how to correlate increases in backend pressure to backend
stalls (and therefore, the loss of throughput).
From a Scheduler point of view, backend pressure is a function of the scheduler
buffer usage (i.e. how the number of uOps in the scheduler buffers changes over
time). Backend pressure increases (or decreases) when there is a mismatch
between the number of opcodes dispatched, and the number of opcodes issued in
the same cycle. Since buffer resources are limited, continuous increases in
backend pressure would eventually leads to dispatch stalls. So, there is a
strong correlation between dispatch stalls, and how backpressure changed over
time.
This patch teaches how to identify situations where backend pressure increases
due to:
- unavailable pipeline resources.
- data dependencies.
Data dependencies may delay execution of instructions and therefore increase the
time that uOps have to spend in the scheduler buffers. That often translates to
an increase in backend pressure which may eventually lead to a bottleneck.
Contention on pipeline resources may also delay execution of instructions, and
lead to a temporary increase in backend pressure.
Internally, the Scheduler classifies instructions based on whether register /
memory operands are available or not.
An instruction is marked as "ready to execute" only if data dependencies are
fully resolved.
Every cycle, the Scheduler attempts to execute all instructions that are ready
to execute. If an instruction cannot execute because of unavailable pipeline
resources, then the Scheduler internally updates a BusyResourceUnits mask with
the ID of each unavailable resource.
ExecuteStage is responsible for tracking changes in backend pressure. If backend
pressure increases during a cycle because of contention on pipeline resources,
then ExecuteStage sends a "backend pressure" event to the listeners.
That event would contain information about instructions delayed by resource
pressure, as well as the BusyResourceUnits mask.
Note that ExecuteStage also knows how to identify situations where backpressure
increased because of delays introduced by data dependencies.
The SummaryView observes "backend pressure" events and prints out a "bottleneck
report".
Example of bottleneck report:
```
Cycles with backend pressure increase [ 99.89% ]
Throughput Bottlenecks:
Resource Pressure [ 0.00% ]
Data Dependencies: [ 99.89% ]
- Register Dependencies [ 0.00% ]
- Memory Dependencies [ 99.89% ]
```
A bottleneck report is printed out only if increases in backend pressure
eventually caused backend stalls.
About the time complexity:
Time complexity is linear in the number of instructions in the
Scheduler::PendingSet.
The average slowdown tends to be in the range of ~5-6%.
For memory intensive kernels, the slowdown can be significant if flag
-noalias=false is specified. In the worst case scenario I have observed a
slowdown of ~30% when flag -noalias=false was specified.
We can definitely recover part of that slowdown if we optimize class LSUnit (by
doing extra bookkeeping to speedup queries). For now, this new analysis is
disabled by default, and it can be enabled via flag -bottleneck-analysis. Users
of MCA as a library can enable the generation of pressure events through the
constructor of ExecuteStage.
This patch partially addresses https://bugs.llvm.org/show_bug.cgi?id=37494
Differential Revision: https://reviews.llvm.org/D58728
llvm-svn: 355308
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to reflect the new license.
We understand that people may be surprised that we're moving the header
entirely to discuss the new license. We checked this carefully with the
Foundation's lawyer and we believe this is the correct approach.
Essentially, all code in the project is now made available by the LLVM
project under our new license, so you will see that the license headers
include that license only. Some of our contributors have contributed
code under our old license, and accordingly, we have retained a copy of
our old license notice in the top-level files in each project and
repository.
llvm-svn: 351636
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Summary: See PR38731.
Reviewers: andreadb
Subscribers: mgorny, javed.absar, tschuett, gbedwell, andreadb, RKSimon, llvm-commits
Differential Revision: https://reviews.llvm.org/D55557
llvm-svn: 349332
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