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[XLA] Rework dot() sharding propagation to lookahead instructions sharding to choose a sharding for dot() that agrees with the users if possible.

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Small collectives might be better off when sinked and there are other potnential use cases
Also fix a bug, where we were accepting reuse of the data that we were storing and changing the tests using that pattern to match the fix.

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instructions through control dependence.

This is because the generated HLO program is correct even without the control
dependence chaining. The purpose of the control dependence chaining is to
support a scheduler, such as the latency hiding scheduler, and thus will be
added to the latency hiding scheduler preparation pass. Not producing the
control dependence chaining while decomposing collective-permute can also
simplify the implementation of collective-pipeliner in pipelining Send and
Recv instructions.

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Updates LLVM usage to match
[8ebe1d1cc1e4](https://github.com/llvm/llvm-project/commit/8ebe1d1cc1e4)

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Without this additional bazelrc file TSL will be built with the system compiler which happens to be GCC.

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This change was merged upstream in https://github.com/openai/triton/pull/2068 but hasn't made it to the OpenXLA fork yet.

Improves build time in OSS by not building a number of MLIR dialects/passes that are not needed.

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Unify iterator names to *_it;
Use auto* instead of auto if the type is a pointer type.

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This is another prefactoring to make Triton fusions compatible with
FusionInterface and partially fused HLO. For the former, we need
the LaunchDimension computation to be a separate function. For the
latter, we change the launch dimension function signatures to no longer
take an HloComputation, because we don't yet have that during fusion (at
least not a complete one). For now, this change is a no-op, since we do
not yet have any boundary functions for non-fusion ops.

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that the corresponding FlatBuffer C API type can also be used instead of
the FlatBuffer C++ API type for the TFLiteSettings FlatBuffer parameter.

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From the original code at commit 03d304b, we are only supposed to scale the reduction
tile size of dimX by the unroll factor for column reductions, so the check when creating
`ReductionCodegenInfo` is only valid for column reductions.

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Add a comparison operator for fragments, improve encapsulation, fix comments.

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LaunchDimensions are being decoupled from codegen. Shared memory requirements
are only known after codegen.

Currently, this feature is only used for Triton fusions. All other
fusions that use shared memory allocate it within the kernel.

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The upcoming CUDA-12 upgrades requires TensorRT 8.6 and this version
has a new set of headers which requires an update to the bazel configure script.

I also had to change `find_cuda_config.py` because previously it has only
been reporting the major version of TensorRT back to the configure script. But
we will also need the minor version to distinguish between TensorRT 8.5 and below,
and TensorRT 8.6+.

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GCC is missing some intrinsics, expand them by hand.

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Create metrics:
1) '/pjrt/compiler/is_compiling_computation' to record if pjrt compiler is compiling computations.
2) '/pjrt/compiler/is_compiling_module' to record if pjrt compiler is compiling modules.

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This is for internal error logging only.

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