GitLab

[PyTorch] Missing intra-domain ranks list when initializing Userbuffers with data parallelism (#1305)

added missing list of intra-domain ranks when num_domains > 1 in initialize_ub
Signed-off-by: Alp Dener <adener@nvidia.com>

* moved userbuffers code to TE/common
Signed-off-by: Alp Dener <adener@nvidia.com>

* moved comm+GEMM overlap code to TE/common
Signed-off-by: Alp Dener <adener@nvidia.com>

* removed PyTorch depdency from comm+GEMM overlap in TE/common
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* added TE/PyTorch wrappers for refactored comm+GEMM overlap code in TE/common
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* updated TE/PyTorch Python API to match the refactored comm+GEMM overlap code
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* updated unit tests to work with refactored comm+GEMM overlap code
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* added a pylint exception to comm+GEMM overlap test runner
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* fixing linting errors
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* added documentation for te.initialize_ub
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* fixed compile errors when building with NVTE_UB_WITH_MPI=1
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* fixed default bootstrap backend
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* switched default bootstrap backend priority to MPI > Gloo > NCCL
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* updated bootstrap backend documentation
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* close UB bootstrap socket to avoid interfering with CUDA Multicast shareable file handle send/recv
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* added torch::Tensor wrappers for communication buffer and atomic counters so PyTorch can factor externally allocated memory into its garbage collection threshold
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* automated handling of world, local and node ranks/sizes within C++ CommOverlapHelper to simplify Python function signatures
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* fixed incorrect read of environment variables
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* corrected priority for _SOCKET_IFNAME environment variables in UB bootstrapping
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* moved multicast support check to cuda_runtime.h and replaced cudaDeviceGetProp call with cached sm_count()
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* removed commented out old code and replaced external collective function type defines with aliases
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* compile-time CUDA version guard for CUDA Driver Multicast attribute
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* added compile-time CUDA version guards to Multicast code in Userbuffers
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* condensed UB docs, corrected const violations
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* fixed autodoc rst for UB calls, added CUDA version guard on Multicast UB kernels
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* fixed incorrect UB type reporting for P2P overlaps, comment reformatting
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* add docstring to tex.ubuf_built_with_mpi()
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* Add fallback for fast param getter
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* Remove fast param getter
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* Fix linter warning
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Fix wgrad for GroupedLinear when weights doesn't require grad
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Fix FP8 activation recompute
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* Upgrade pylint and first round formatting
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* round 2
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* round 3
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* Format and fixes
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* FIxes
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* More linting
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* Fixes
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* CPU perf optimization in linear autograd function

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* CPU perf optimization in prepare_forward function

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* Reuse tensor dims in linear autograd func
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* Apply optimizations to grouped linear
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* Debug test failures
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* Fix linter warnings
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* Avoid deepcopy in tests
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* Move _fast_setattr logic to __setattr__ method
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* Removing the unused options from GroupedLinear docs and fixing the bug
with offsets
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* offsets -> fp8_meta_offsets
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* Docs fixes
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* docs fix
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* docs fix
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* Check if network interface name is valid and show useful warning message when initializing Userbuffers
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* Fix formatting issue in warning message.
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* Add base class for tensor proxies
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* Move tensor detaching logic to tensor proxy base class
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* Use Python wrappers to PyTorch extensions
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* Include transpose caching logic in proxy encode function
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* Debug dimension mismatch with amax history
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* Rename to "QuantizedTensor"
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* Rename "proxy_detach" to "detach"
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* Include transpose cache in detach and clone funcs
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* Fix linter warnings
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* Update FP8 workspaces with QuantizedTensor functions
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* Move logic for FP8 transpose cache in FP8 workspaces to base class
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* Remove cast-transpose logic from linear op
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* Remove unnecessary args for Float8Tensor when using FP8 attr dict
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* Fix linter warnings
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* propagate scale_inv modification to GroupedLinear
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* optimization for separate scale_inv of weights and single output
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* let grouped gemm support different input combinations
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* fix type
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* add contiguous check
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* use len() instead of isinstance
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* fix ut
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* [TE/PyTorch][MoE] Add FP8 padding and unpadding module 

 1. Add multi-tensor padding kernel for FP8 with padding size = 16.
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* fp8 mha with rope
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* resolve comments
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* move transpose to backward for fp8 input
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* fix for FA3
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* remove unnecessary copy of scale_inv
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* skip fp8 dpa/mha tests when fa3 is not available
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* Perform scale-inv update in cast-transpose kernels
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feat(pytorch): Allow TransformerLayer and MultiheadAttention to accept sequence length parameters (#1066)

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* Move THD logic in shape calculation, add missing optional in params
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* DGRAD-RS overlap bug fix

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* use fused_multi_cast_transpose
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[C/PyTorch] Fixed incorrect use of `torch.distributed.new_group()` when creating intra-node group in `initialize_ub()` (#1087)

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* fix logging in attention
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* remove redundant imports
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* fix workspaces and unfused bias in multi-stream cuBLAS

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* Fix C-compatibility

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[PyTorch] Fixing hang in `initialize_ub()` for multi-node runs after PR901 removal of MPI-dependence (#986)

* Re-implementing PR901 (removing MPI-dependence in Userbuffers) with multi-node fixes

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* corrected example problem to set device by local ordinal instead of global process rank
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* double-free fix in userbuffers destructor
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* removed unnecessary and incorrect torch.cuda.set_device(...)
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