GitLab

* [CPU, Parallel] Rewriting omp pragmas with parallel_for

* [CPU, Parallel] Decrease number of calls to task function

* c[CPU, Parallel] Modify calls to new interface of parallel_for

Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

[Feature] Add a HINT for the per edge type sampler of heterogeneous DistGraph that highlighting the etypes are sorted already. (#3260)

* pass cpp test

* distgraph use sorted edge flag.

* lint

* triger

* update test
Co-authored-by: Ubuntu <ubuntu@ip-172-31-2-66.ec2.internal>

* Optimize sampling

* Stop initialization of array

* Fix includes for linting

* Move comment

* Fix replace
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* Implement range based NDArrayPartition

* Finish implement range based partition support

* Add unit test

* Fix whitepace

* Add Kernel suffix

* Fix argument passing

* Add doxygen docs and improve variable naming

* Add unit test

* Add function for converting a partition book

* Add example to partition_op docs

* Fix dtype conversion for mxnet and tensorflow

* Update filter code

* Add unit tests

* Fixes

* Switch to indices

* Rename functions

* Fix linting

* Fix whitespace

* Add doc

* Fix heterograph

* Change workspace allocation

* Fix linting

* Fix docs in filter.py

* Add todo
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>

* Add pytorch-direct version

* remove

* add documentation for UnifiedTensor

* Revert "add documentation for UnifiedTensor"

This reverts commit 63ba42644d4aba197c1cb4ea4b85fa1bc43b8849.

* alignment fix for UnifiedTensor access

* fix linting issue
Co-authored-by: shhssdm <shhssdm@gmail.com>
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* Only link tensordispatcher against pytorch

* Only modify libraries when not using MSVC

* Split out separate generators for each thread

* Amortize cost of curand_init

* Improve readability
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>

* fix.

* fix.

* fix.

* fix.

* Fix test

* Deprecate old DistEmbedding impl, use synchronized embedding impl

* Basic imple of heterogeneous on homogenenous sampling

* make pass

* Pass C++ test

* Add python test code

* lint

* lint

* Add MultiLayerEtypeNeighborSampler

* Add unitest for single machine dataloader

* Add dist dataloader test for edge type sampler

* Fix lint

* fix

* support for per etype sample

* Fix some bug and enable distributed training with per edge sample

* fix

* Now distributed training works

* turn off some mxnet

* turn off mxnet for some dist test

* fix

* upd

* upd according to the comments

* Fix

* Fix test and now distributed works.

* upd

* upd

* Fix

* Fix bug

* remove dead code.

* upd

* Fix

* upd

* Fix
Co-authored-by: Ubuntu <ubuntu@ip-172-31-71-112.ec2.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-2-66.ec2.internal>
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

Co-authored-by: JingchengYu94 <jingchengyu94@gmail.com>
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* remove redundant fill

* trigger ci

Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

[Feature][Performance][GPU] Introducing UnifiedTensor for efficient zero-copy host memory access from GPU (#3086)

* Add pytorch-direct version

* Initial commit of unified tensor

* Merge branch 'master' of https://github.com/davidmin7/dgl



* Remove unnecessary things

* Fix error message

* Fix/Add descriptions

* whitespace fix

* add unpin

* disable IndexSelectCPUFromGPU with no CUDA

* add a newline for unified_tensor.py

* Apply changes based on feedback

* add 'os' module

* skip unified tensor unit test for cpu only

* Update tests/pytorch/test_unified_tensor.py
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* reflect feedback
Co-authored-by: shhssdm <shhssdm@gmail.com>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* optimizations of spmm for CPU

* Added names of contributors

* Minor code cleanup

* Moved the spmm optimization code to a new header file

* Moved to DGL's logging method

* removed duplicate code between SpMMSumCsr and SpMMCmpCsr

* Changes made to follow Google coding style

* Fixed lint errors in spmm.h

* Fixed some lint errors from spmm_blocking_libxsmm.h

* Fixed lint errors from spmm_blocking_libxsmm.h

* Added comments to SpMMCreateLibxsmmKernel

* to enable building of tests, and other cosmetic changes

* disabling libxsmm on windows

* Put a condition to avoid opt impl for FP64 as libxsmm does not have FP64 support yet

* cosmetic changes and documentation

* cosmetic changes

* to pass lint tests

* replaced multiple allocations for buffers of indices and edges with a single allocation
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

[Feature] Add Heterograph support on Python for builtin unary msg functions (copy_u, copy_e) (#2989)

* heterograph for binary func

* Added SDDMM support

* Added unittest

* added binary test cases

* unary mfuncs works

* Fixed lint err

* lint check and others

* link check

* fixed import *_hetero issue

* lint check

* replace torch with dgl backend

* lint cehck

* removed torch from test

* skip mxnet unittest

* skip gpu test

* Remove unused/duplicated code

* minor

* changed data structure of ndata and edata

* link check

* reorganized

* minor lint

* minor lint

* raise error for udf func

* lint check

* fix for CUDA 10.1

* add a note for future cross-type max/min reducing

* Add support CUDA < 11

* lint check

* tidied C code

* remove dummy GSDDMM_hetero backward implementation
Co-authored-by: Israt Nisa <nisisrat@amazon.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: Quan Gan <coin2028@hotmail.com>

Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* Add dgl.utils.is_sorted_srcdst

* Fix linting issues

* delete blank line

* Specify datatype to index tensor in test

* Force integer conversion
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>

* fix

* remove nvidiasmi

* fix

* fix docs

* fix

* fix

* 1

* fix

* remove

* skip deprecated kernel

* fix

* Revert "skip deprecated kernel"

This reverts commit c5ceb7f60dbbaf065b81cc3680757fd611d90ad3.

* fix

* csr and csc creation

* fix

* fix

* fixes to adj transpose

* fine

* raise error if indptr did not match number of nodes

* fix

* huh?

* oh
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* update

* update

* update

* update

* lint

* lint

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* lint

* update

* clone

* update

* update

* update

* update

* replace idarray with ndarray

* refactor cpp part

* refactor python part

* debug

* refactor interface

* test and doc

* lint and test

* lint

* fix

* fix

* fix

* const

* doc

* fix

* fix

* fix

* fix

* fix & doc

* fix

* fix

* update

* update

* update

* merge

* doc

* doc

* lint

* fix

* more tests

* doc

* fix

* fix

* update

* update

* update

* fix

* fix
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* add seal example

* 1. add paper infomation in examples/README
2. adjust codes
3. option test

* use latest `to_simple` to replace coalesce graph function

* remove outdated codes

* remove useless comment

* Node2vec
1.implement node2vec random walk c++ op
2.implement node2vec model
3.implement node2vec example

* add CMakeLists file modify

* refine c++ codes

* refine c++ codes

* add missing whitespace

* refine python codes

* add codes

* add node2vec_impl.h

* fix codes

* fix code style problem

* fixes

* remove

* lots of changes

* add benchmark

* fixes
Co-authored-by: smilexuhc <smile.xuhc@gmail.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* Added heterograph support SpMM, SDDMM

* bug fix cuda stream

* add cudaStrm destroy and fix whitespace

* Added heterograph support SpMM, SDDMM

* bug fix cuda stream

* add cudaStrm destroy and fix whitespace

* changed max stream = 1

* Fixed ctx

* using default stream

* Added heterograph support SpMM, SDDMM

* bug fix cuda stream

* add cudaStrm destroy and fix whitespace

* changed max stream = 1

* Fixed ctx

* using default stream

* fix bug in copy_rhs

* changed by mistake

* minor datatype change

* added datatype check
Co-authored-by: Israt Nisa <nisisrat@amazon.com>

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Fix

* Update

* Fix subgraph tests

* Capture stdout for distributed test

* Capture stdout for distributed test

* Update

* Update

* Update

* Update subgraph.cc
Co-authored-by: Ubuntu <ubuntu@ip-172-31-28-17.us-west-2.compute.internal>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

* add.

* fix.

* fix.

* fix.

* fix.

* add tests.

* support node split and edge split.

* support 1 partition.

* add tests.

* fix.

* fix test.

* use hierarchical partition.

* add check.
Co-authored-by: Zheng <dzzhen@3c22fba32af5.ant.amazon.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-22-57.us-west-2.compute.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-71-112.ec2.internal>

* add bruteforce impl

* add nn descent implementation

* change doc-string

* remove redundant func

* use local rng for cuda

* fix lint

* fix lint

* fix bug

* fix bug

* wrap nndescent_knn_graph into knn

* fix lint

* change function names

* add comment for dist funcs

* let the compiler do the unrolling

* use better blocksize setting

* remove redundant line

* check the return of the cub calls
Co-authored-by: Tong He <hetong007@gmail.com>

[Performance] Perform to_block on the GPU when the dataloader is created with a GPU `device`. (#3016)

* add output device for dataloading

* Update dataloader

* Get sampler device from dataloader

* Fix line length

* Update examples

* Fix to_block GPU for empty relation types

* Handle the case where the DistGraph has None for the underlying graph
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* Split from NCCL PR

* Fix type in comment

* Expand documentation for sparse_all_to_all_push

* Restore previous behavior in example

* Re-work optimizer to use NCCL based on gradient location

* Allow for running with embedding on CPU but using NCCL for gradient exchange

* Optimize single partition case

* Fix pylint errors

* Add missing include

* fix gradient indexing

* Fix line continuation

* Migrate 'first_step'

* Skip tests without enough GPUs to run NCCL

* Improve empty tensor handling for pytorch 1.5

* Fix indentation

* Allow multiple NCCL communicator to coexist

* Improve handling of empty message

* Update python/dgl/nn/pytorch/sparse_emb.py
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* Update python/dgl/nn/pytorch/sparse_emb.py
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* Keepy empty tensor dimensionaless

* th.empty -> th.tensor

* Preserve shape for empty non-zero dimension tensors

* Use shared state, when embedding is shared

* Add support for gathering an embedding

* Fix typo

* Fix more typos

* Fix backend call

* Use NodeDataLoader to take advantage of ddp

* Update training script to share memory

* Only squeeze last dimension

* Better handle empty message

* Keep embedding on the target device GPU if dgl_sparse if false in RGCN example

* Fix typo in comment

* Add asserts

* Improve documentation in example
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Update

* Add files via upload

* Add files via upload

* Add files via upload

* Add files via upload

* Update

* Update

* Add files via upload

* Add files via upload

* Update

* Lint

* Add files via upload

* Lint

* Update

* Update

* Update

* Update

* Update

* Lint Fix

* Lint
Co-authored-by: Ubuntu <ubuntu@ip-172-31-12-161.us-west-2.compute.internal>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* Added a special implementation for MetapathBasedRandomWalkStep for the Uniform randomwalk case

* Fixed all linting issues

* add comment
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* SpMM for heterograph

* C APIs SDDMM heterograph

* passes initial result

* renamed eid with nid

* aggregation on same ntype for multiple etypes

* fix link check failure

* lint check part 2

* lint check part 3

* Fixed SpMMCmpCsr Min op

* added mem references

* fixed fill(Max/Min), added const

* removed newline

* brought back docstring
Co-authored-by: Israt Nisa <nisisrat@amazon.com>
Co-authored-by: Da Zheng <zhengda1936@gmail.com>

* update

* update

* update

* update

* lint

* lint

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* update

* lint

* update

* clone

* update

* update

* update

* update

* replace idarray with ndarray

* refactor cpp part

* refactor python part

* debug

* refactor interface

* test and doc

* lint and test

* lint

* fix

* fix

* fix

* const

* doc

* fix

* fix

* fix

* fix

* fix & doc

* fix

* fix

* fix

* fix

* fix

* fix

* update
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* speed up random number generation.

* fix lint.

* Fix

* fix.
Co-authored-by: Zheng <dzzhen@3c22fba32af5.ant.amazon.com>

Move pointer dereferencing in CDFSampler::draw() and AliasSampler::draw() to inside of conditional (#2943)
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>