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
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---------
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* [JAX-Q] Single GPU current scaling for JAX
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* Fix scale check dtype for MXFP8 scales affecting tests using assert_bitwise_scaled_tensors
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* Address comments
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* Remove cast to fp32 for norm primitives now that zero-centered gamma dtype issue is fixed
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* Fix lint issue
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* Remove unnecessary cast to fp32
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* Lint
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---------
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Check CuDNN version and apply unfused norm if
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rm pax/praxis
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* Add a flag to support computing zero-centered gamma in weight dtype or compute dtype for CuDNN
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* Address comments
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---------
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* Add test cases for full coverage in jax/test_layer.py
- causal and window size None
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- no_mask and window size default (-1,1)
- no_mask and window size default (2,2)
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* Correct the condition where padding_causal_mask was being mapped to scaled upper triangle
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* Fix Issue #1524
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* Add experimental Shardy support.

Production use is not yet recommended.

---------
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* New GroupedGemmPrimitive using variadic args

* Remove squeeze() to reduce D2D memcpy

* Revert to the list append fashion to simplify code

---------
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* scaling enum abstract

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* fix norm sharding

---------
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---------
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* rename QuantizeAxis to QuantizeLayout, get_layout to get_data_layout, q_axis to q_layout

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* added gated act to test encoder

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MXFP8 flax layer tests
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* Blockwise float8 quantizer and quantized tensor class.

The classes are configurable for 128x128 blocksize
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* Save memory by dropping reference to saved tensors.

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* Merge conflict from rebase.
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* Add shape implementations for block scaling.

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* Move benchmark to te_playground
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* Remove amax_epsilon and pow_2_scales from tensor.

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* Lint changes.
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* Fixup MR changes that broke.
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* Safer ifdef in kernel.
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* Documentation prose.
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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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* Skip tests on Lovelace
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---------
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* refactor + mxfp8

* added grouped gemm

* rename linear to dense

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Add fast path for causal masking with segment IDs.
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* Fix softmax shape for THD format.
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flax module with compute dtype inferred from the inputs
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Fix issues when mask/sequence_descriptor is None
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