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Co-authored-by: Ubuntu <ubuntu@ip-172-31-28-63.ap-northeast-1.compute.internal>

Co-authored-by: Hongzhi (Steve), Chen <chenhongzhi.nkcs@gmail.com>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-28-63.ap-northeast-1.compute.internal>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-28-63.ap-northeast-1.compute.internal>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-28-63.ap-northeast-1.compute.internal>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-28-63.ap-northeast-1.compute.internal>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-28-63.ap-northeast-1.compute.internal>

Co-authored-by: xiny <xiny@nvidia.com>

Co-authored-by: Hongzhi (Steve), Chen <chenhongzhi.nkcs@gmail.com>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-28-63.ap-northeast-1.compute.internal>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-28-63.ap-northeast-1.compute.internal>

Co-authored-by: Rhett Ying <85214957+Rhett-Ying@users.noreply.github.com>

Co-authored-by: Ubuntu <ubuntu@ip-172-31-25-242.ap-northeast-1.compute.internal>

Co-authored-by: Hongzhi (Steve), Chen <chenhongzhi.nkcs@gmail.com>

* cleanup unused cmake options

* disable BUILD_TORCH for cugraph

* resolve comments

* Enable AVX by default

* Fix linting errors

* Fix win64 build (libxsmm not linked)

Libxsmm on Win64 is not linked, should be disabled by default

* Fix clang format issues

* Change lower supported cpu version to LIBXSMM_X86_AVX2

Change lower supported cpu version to LIBXSMM_X86_AVX2 to address https://github.com/dmlc/dgl/issues/3459

 issue

* Fix unit test

Remove assumption that libxsmm is enabled in the config by default (only true for intel CPUs with AVX2 instructions)

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Co-authored-by: Ubuntu <ubuntu@ip-172-31-15-137.us-west-2.compute.internal>
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>

* expose GeneratePermutation

* add sparse_all_to_all_push

* add sparse_all_to_all_pull

* add unit test

* handle world_size=1

* remove python nccl wrapper

* remove the nccl dependency

* use pinned memory to speedup D2H copy

* fix lint

* resolve comments

* fix lint

* fix ut

* resolve comments

* Fix ubuntu 22 build

* Add one more flag

This reverts commit a5e31391.

* Set USE_LIBXSMM default to OFF.

* update

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Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>

* enable dgl sparse build in default

* disable sparse build on cugraph

* update

* initial commit

* Update build.sh

* [Sparse] Support SpMM and SDDMM

* Add SDDMMAutoGrad

* Rename SpMMImpl and SDDMMImpl and move them to dgl_sparse/src/matmul.h

* Update comments

* Update

* Minor fix

* Revert "[Sparse] Add SpMM and SDDMM. (#4999)"

This reverts commit 15365d78.

* lint

* [Sparse] Add SpMM and SDDMM

* Update

* Add CSR and CSC SpMM tests

* replace dgl PRNG with pcg32

* remove pcg submodule, add a simple implementation

* replace pcg32 with std::mt19937_64

* fix include order

* change RandomEngine to pcg32

* Remove custom pcg32 implementation, use the submodule provided by the original author.

* minor bug

* move include for linting

* include pcg for tests too
Co-authored-by: Hongzhi (Steve), Chen <chenhongzhi.nkcs@gmail.com>

* adding LABOR sampling

* add ladies and pladies samplers

* fix compile error after rebase

* add reference for ladies sampler

* Improve ladies implementation.

* weighted labor sampling initial implementation draft
fix indentation and small bug in ladies script

* importance_sampling currently doesn't work with weights

* fix weighted importance sampling

* move labor example into its own folder

* lint fixes

* Improve documentation

* remove examples from the main PR

* fix linting by not using c++17 features

* fix documentation of labor_sampler.py

* update documentation for labor.py

* reformat the labor.py file with black

* fix linting errors

* replace exception use with if

* fix typo in error comment

* fixing win64 build for ci

* fixing weighted implementation, works now.

* fix bug in the weighted case and importance_sampling==0

* address part of the reviews

* remove unused code paths from cuda

* remove unused code path from cpu side

* remove extra features of labor making use of random seed.

* fix exclude_edges bug

* remove pcg and seed logic from cpu implementation, seed logic should still work for cuda.

* minor style change

* refactor CPU implementation, take out the importance_sampling probability computation into a function.

* improve CUDAWorkspaceAllocator

* refactor importance_sampling part out to a function

* minor optimization

* fix linting issue

* Revert "remove pcg and seed logic from cpu implementation, seed logic should still work for cuda."

This reverts commit c250e07ac6d7e13f57e79e8a2c2f098d777378c2.

* Revert "remove extra features of labor making use of random seed."

This reverts commit 7f99034353080308f4783f27d9a08bea343fb796.

* fix the documentation

* disable NIDs

* improve the documentation in the code

* use the stream argument in pcg32 instead of skipping ahead t times, can discard the use of hashmap now since it is faster this way.

* fix linting issue

* address another round of reviews

* further optimize CPU LABOR sampling implementation

* fix linting error

* update the comment

* reformat

* rename and rephrase comment

* fix formatting according to new linting specs

* fix compile error due to renaming, fix linting.

* lint

* rename DGLHeteroGraph to DGLGraph to match master

* replace other occurrences of DGLHeteroGraph to DGLGraph
Co-authored-by: Muhammed Fatih BALIN <m.f.balin@gmail.com>
Co-authored-by: Kaan Sancak <kaansnck@gmail.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>