GitLab

Introduce nvte_memset to provide a fill kernel that is faster than cudaMemsetAsync for small sizes (#1716)

* nvte_memset fills single float value
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Support larger sizes than a single value and add tests
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

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Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

Revert "Allow NVTEShape to own data. (#1674)"

This reverts commit e61ce77c

.
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Allow NVTEShape to own data.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Convert repeated copy paths to nvte_make_shape calls.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Apply suggestions from code review
Signed-off-by: Tim Moon <4406448+timmoon10@users.noreply.github.com>

* Build fixes.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* MR feedback.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

---------
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* Add a flag to support computing zero-centered gamma in weight dtype or compute dtype for CuDNN
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Address comments
Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

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Signed-off-by: Jeremy Berchtold <jberchtold@nvidia.com>

* Add GEMM logic for blockwise quantized tensors.

GEMM test cases included in pytorch integration.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update NVTE_BLOCK_SCALING for GEMM.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Gate feature on CUDA 12.9
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Gemm typo.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Remove unecessary type converter change.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Reflect epilogue availability and test supported epilogues.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* GEMM simplifications from recipe branch.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Format py code.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update GEMM DGelu tests to match support depending on output dtype.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Force pow2Scales in GEMM
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Add GEMM test to pytorch test suite.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Add copyright to GEMM test.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update import for GEMM test.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Add license.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update test gemm supported predicate.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Use sgemm like interfaces and naming.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Rewrite GEMM comment.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* MR Feedback.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Recipe setup for Linear modules.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Use 12.9 feature test.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Run against tensor dumps from internal library.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update FIXME to TODO with linked issue.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update full recompute feature to save recipe.

The recompute context uses the same recipe
and fp8 settings as the original fwd pass.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* MR Feedback. Avoid reusing quantizer objects.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update logic in module.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Format py.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update for PP bug.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update test numerics.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update force_power_of_2 scales in the recipe.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update usage method to satisfy upstream changes.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* fix subchannel recipe in distributed test with bf16 gather
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* Edit and cleanup BF16 gather code.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update test import.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* support columnwise only mode to 1D quantize kernel
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* Format and move enum
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Skip alloc.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* try async bf16 gather
Signed-off-by: zhongboz <zhongboz@nvidia.com>

* Format python code.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Document and type code.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Update pytorch lint errors.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Dont set high precision dtype.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Add test for sanity and CG; fix CG for sequential?
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Keep make_quantizers API stable

Update num_quantizers instead to pass cuda_graph tests.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Fix import name.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Rename recipe method.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Skip grouped linear sanity test.
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* Set usage before BF16 gather.
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* refactor for nvte_quantize_v2
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* Format code.
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* Cleanup nvte_quantize_v2
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* Test fp32 scales.
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* Disable CUDA graph.
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* Simplify layernorm linear
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* Cleanup layernorm linear.
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* LayerNorm linear bwd gather logic.
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* Communication updates.
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* Update transformer_engine/pytorch/ops/op.py

Apply MR comment change.
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* Lint fix.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* MR feedback.
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* Enable cuda graph tests.
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* Reduce chance of spurious failure and reword.
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* Review suggestions from @timmoon10
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* Update CPP tests.
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* Update test_float8blockwisetensor.py
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* Blockwise float8 quantizer and quantized tensor class.

The classes are configurable for 128x128 blocksize
and 1x128 blocksize via setting block_scaling_dim == 2,1 respectively.

Scale tensors are stored in a format emenable for matrix multiplication,
however the integration of matmul is deferred as a separate story.

Fusions of quantization and DBIAS or activation functions are not yet
implemented, and the dequantization is currently implemented in torch.

Tests for quantization are included in C++ and pytorch layers, with
exact comparison to reference quantizer behavior as well as an attempt
to hit interesting branches through the API such as tensor creation
in pytorch and CPP and dequantization of row and columnwise usage.

Two CUDA kernels for quantization are included, and are direct ports
of equivalents in the kitchen repository, where a subchannel recipe
has been used for end to end training.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Apply linting changes.
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* Alignment for 1D scaling for GEMM edge case.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* MR feedback.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Change API name.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Fix merge conflict with name change.
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* Use common tensor map API.
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* Change API to use two scaling mode enums.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Fix typo.
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* Update some call sites.
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* Tests for torch tensor API surface.

Since the quantized tensor is a tensor
subclass, these tests exercise torch hooks.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Reuse scale calculation between quantizer refs.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Save memory by dropping reference to saved tensors.

Issues previously observed are solved.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Remove constexpr parameters from kernel.

Code size is reduced with fewer constexpr params.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Merge conflict from rebase.
Signed-off-by: Keith Wyss <kwyss@nvidia.com>

* Add shape implementations for block scaling.

nvte_shape was added upstream. Logic added
for block scaled fp8.
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* Move benchmark to te_playground
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* Remove amax_epsilon and pow_2_scales from tensor.

Hardcodes the default values.
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* Lint changes.
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* Reuse compute_scale function from Current Scaling.
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* Bugfix on inf_value scale refactor.
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* Remove qopt calls from test.
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* Update pytest list.
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* Add copyright to reference scale calc.
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* Use ptx.cuh functions instead of cde.
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* Update shape logic with allocation and reuse shape.
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* Usage defaults MR feedback.
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* Use TypeInfo
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* MR feedback.
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* Skip tests on Lovelace
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enable layernormlinear with current scaling, pass bitwise test
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bug fix: use cached fp8 recipe in backward
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fix layernorm_mlp with current scaling, fix activation_helper with current scaling
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support detailed numerical settings from recipe to quantization kernel
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* [TE/PyTorch][MoE] Add FP8 padding and unpadding module 

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Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Move scale inverse calculation to framework
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* cleanup
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix RMSNorm
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix tests
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Fix gated kernel/geglu
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Add GeGLU and DGeGLU
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add DGeGLUCT
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Update copyright year
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Refine shape check
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Code refine
Signed-off-by: Reese Wang <rewang@nvidia.com>
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add rmsnorm kernels
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add rmsnorm cpp unit test
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Apply new Tensor struct
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Move scale/scale_inv/amax into the TE Tensor struct
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Add document
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Separate rmsnorm kernels from the layernorm
Signed-off-by: Reese Wang <rewang@nvidia.com>

* fix indent
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Update rmsnorm test cases
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Update copyright year
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Fix the support matrix on the document
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Move register macro out of utils.cuh
Signed-off-by: Reese Wang <rewang@nvidia.com>
Signed-off-by: Reese Wang <rewang@nvidia.com>

Signed-off-by: Przemek Tredak <ptredak@nvidia.com>
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Use -O2 for the test_operator
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Increase test parallelism
Signed-off-by: Reese Wang <rewang@nvidia.com>
Signed-off-by: Reese Wang <rewang@nvidia.com>

* Move the amax/scale/scale_inv into the TE Tensor struct.
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Handle multi_cast_transpose
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Changed softmax to new Tensor
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* First pass at the cpp tests
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Round of fixes
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Fix multi_cast_transpose
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>

* Fix cast_to_fp8
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>
Signed-off-by: Przemyslaw Tredak <ptrendx@gmail.com>
Signed-off-by: Przemek Tredak <ptredak@nvidia.com>
Signed-off-by: Przemyslaw Tredak <ptrendx@gmail.com>
Co-authored-by: Kirthi Shankar Sivamani <ksivamani@nvidia.com>

* Add kernel for multi-tensor cast-transpose
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Fix incorrect test function in multi-tensor cast-transpose unit test
Signed-off-by: Tim Moon <tmoon@nvidia.com>

* Remove std::vector from multi-tensor cast-transpose function signature

Makes sure the main header is C-compatible.
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Signed-off-by: Tim Moon <tmoon@nvidia.com>
Co-authored-by: Przemyslaw Tredak <ptredak@nvidia.com>