This moves the registry higher in the LLVM library dependency stack.
Every client of the target registry needs to link against MC anyway to
actually use the target, so we might as well move this out of Support.
This allows us to ensure that Support doesn't have includes from MC/*.
Differential Revision: https://reviews.llvm.org/D111454
Currently native clusterization simply groups all benchmarks
by the opcode of key instruction, but that is suboptimal in certain cases,
e.g. where we can already tell that the particular instructions
already resolve into different sched classes.
This makes it possible for targets to define their own MCObjectFileInfo.
This MCObjectFileInfo is then used to determine things like section alignment.
This is a follow up to D101462 and prepares for the RISCV backend defining the
text section alignment depending on the enabled extensions.
Reviewed By: MaskRay
Differential Revision: https://reviews.llvm.org/D101921
Summary:
It doesn't need anything from Analysis::SchedClassCluster class,
and takes ResolvedSchedClass as param, so this seems rather fitting.
Reviewers: courbet, gchatelet
Reviewed By: courbet
Subscribers: tschuett, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D59994
llvm-svn: 357263
Summary:
`ResolvedSchedClass` will need to be used outside of `Analysis`
(before `InstructionBenchmarkClustering` even), therefore promote
it into a non-private top-level class, and while there also
move all of the functions that are only called by `ResolvedSchedClass`
into that same new file.
Reviewers: courbet, gchatelet
Reviewed By: courbet
Subscribers: mgorny, tschuett, mgrang, jdoerfert, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D59993
llvm-svn: 357259
Summary:
The diff looks scary but it really isn't:
1. I moved the check for the number of measurements into `SchedClassClusterCentroid::validate()`
2. While there, added a check that we can only have a single inverse throughput measurement. I missed that when adding it initially.
3. In `Analysis::SchedClassCluster::measurementsMatch()` is called with the current LLVM values from schedule class and the values from Centroid.
3.1. The values from centroid we can already get from `SchedClassClusterCentroid::getAsPoint()`.
This isn't 100% a NFC, because previously for inverse throughput we used `min()`. I have asked whether i have done that correctly in
https://reviews.llvm.org/D57647?id=184939#inline-510384 but did not hear back. I think `avg()` should be used too, thus it is a fix.
3.2. Finally, refactor the computation of the LLVM-specified values into `Analysis::SchedClassCluster::getSchedClassPoint()`
I will need that function for [[ https://bugs.llvm.org/show_bug.cgi?id=41275 | PR41275 ]]
Reviewers: courbet, gchatelet
Reviewed By: courbet
Subscribers: tschuett, jdoerfert, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D59951
llvm-svn: 357245
Summary:
This is an alternative to D59539.
Let's suppose we have measured 4 different opcodes, and got: `0.5`, `1.0`, `1.5`, `2.0`.
Let's suppose we are using `-analysis-clustering-epsilon=0.5`.
By default now we will start processing the `0.5` point, find that `1.0` is it's neighbor, add them to a new cluster.
Then we will notice that `1.5` is a neighbor of `1.0` and add it to that same cluster.
Then we will notice that `2.0` is a neighbor of `1.5` and add it to that same cluster.
So all these points ended up in the same cluster.
This may or may not be a correct implementation of dbscan clustering algorithm.
But this is rather horribly broken for the reasons of comparing the clusters with the LLVM sched data.
Let's suppose all those opcodes are currently in the same sched cluster.
If i specify `-analysis-inconsistency-epsilon=0.5`, then no matter
the LLVM values this cluster will **never** match the LLVM values,
and thus this cluster will **always** be displayed as inconsistent.
The solution is obviously to split off some of these opcodes into different sched cluster.
But how do i do that? Out of 4 opcodes displayed in the inconsistency report,
which ones are the "bad ones"? Which ones are the most different from the checked-in data?
I'd need to go in to the `.yaml` and look it up manually.
The trivial solution is to, when creating clusters, don't use the full dbscan algorithm,
but instead "pick some unclustered point, pick all unclustered points that are it's neighbor,
put them all into a new cluster, repeat". And just so as it happens, we can arrive
at that algorithm by not performing the "add neighbors of a neighbor to the cluster" step.
But that won't work well once we teach analyze mode to operate in on-1D mode
(i.e. on more than a single measurement type at a time), because the clustering would
depend on the order of the measurements.
Instead, let's just create a single cluster per opcode, and put all the points of that opcode into said cluster.
And simultaneously check that every point in that cluster is a neighbor of every other point in the cluster,
and if they are not, the cluster (==opcode) is unstable.
This is //yet another// step to bring me closer to being able to continue cleanup of bdver2 sched model..
Fixes [[ https://bugs.llvm.org/show_bug.cgi?id=40880 | PR40880 ]].
Reviewers: courbet, gchatelet
Reviewed By: courbet
Subscribers: tschuett, jdoerfert, RKSimon, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D59820
llvm-svn: 357152
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
Summary:
This allows simplifying references of llvm::foo with foo when the needs
come in the future.
Reviewers: courbet, gchatelet
Reviewed By: gchatelet
Subscribers: javed.absar, tschuett, llvm-commits
Differential Revision: https://reviews.llvm.org/D53455
llvm-svn: 344922
Summary:
On hover, the whole asm snippet is displayed, including operands.
This requires the actual assembly output instead of just the MCInsts:
This is because some pseudo-instructions get lowered to actual target
instructions during codegen (e.g. ABS_Fp32 -> SSE or X87).
Reviewers: gchatelet
Subscribers: mgorny, tschuett, llvm-commits
Differential Revision: https://reviews.llvm.org/D48164
llvm-svn: 334805
Summary:
We now highlight any sched classes whose measurements do not match the
LLVM SchedModel. "bad" clusters are marked in red.
Screenshot in phabricator diff.
Reviewers: gchatelet
Subscribers: tschuett, mgrang, RKSimon, llvm-commits
Differential Revision: https://reviews.llvm.org/D47639
llvm-svn: 333884
Summary: This makes the report much more readable.
Reviewers: gchatelet
Subscribers: tschuett, mgrang, craig.topper, RKSimon, llvm-commits
Differential Revision: https://reviews.llvm.org/D47189
llvm-svn: 332979
Summary:
Warn on instructions that should have the same performance
characteristics according to the sched model but actually
differ in their benchmarks.
Next step: Make the display nicer to browse, I was thinking maybe html.
Reviewers: gchatelet
Subscribers: tschuett, llvm-commits
Differential Revision: https://reviews.llvm.org/D46945
llvm-svn: 332601
Summary:
The analysis mode gives the user a clustered view of the measurement results.
Next steps are (requires the split ok AsmTemplate.Name into {mnemonic, mode}):
- Show the sched class.
- Highlight any inconsistencies with the checked-in data.
Reviewers: gchatelet
Subscribers: mgorny, llvm-commits, tschuett
Differential Revision: https://reviews.llvm.org/D46865
llvm-svn: 332344
The analysis mode gives the user a clustered view of the measurement results and
highlights any inconsistencies with the checked-in data.
llvm-svn: 332229
Reid Kleckner