GitLab

* Wrap all CUDA runtime API/CUB calls with macro

* remove the usage of explicit cudaMalloc in favor of AllocWorkspace

* fix typo
Co-authored-by: Israt Nisa <neesha295@gmail.com>

* [ist] enable time out when fetching msg

* fix lint error

* minor refinements

* improve minor log

* fix dist test

* fix timeout issue in tensorpipe

Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>
Co-authored-by: Israt Nisa <neesha295@gmail.com>

* change warning message

* Update tensordispatch.cc

This reverts commit fdd1fe19.

* Explicitly unpin tensoradapter allocated arrays

* Undo unrelated change

* Add unit test

* update unit test

[Examples] Update graphsage multi-gpu example to use mutliple GPUs for validation and testing. (#3827)

* Update graphsage multi-gpu example to use mutliple GPUs for validation and
testing.

* Remove argmax

* Fix rebase error

* Add more documentation to example and simplify

* Switch to name shared memory

* Add comment about how training is distributed

* Restore iteration count

* fix munmap error reporting for better error messages
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>

* fixes

* fix

* more fixes

* update

* oops

* lint?

* temporarily revert - will fix in another PR

* more fixes

* skipping mxnet test

* address comments

* fix DDP

* fix edge dataloader exclusion problems

* stupid bug

* fix

* use_uvm option

* fix

* fixes

* fixes

* fixes

* fixes

* add evaluation for cluster gcn and ddp

* stupid bug again

* fixes

* move sanity checks to only support DGLGraphs

* pytorch lightning compatibility fixes

* remove

* poke

* more fixes

* fix

* fix

* disable test

* docstrings

* why is it getting a memory leak?

* fix

* update

* updates and temporarily disable forkingpickler

* update

* fix?

* fix?

* oops

* oops

* fix

* lint

* huh

* uh

* update

* fix

* made it memory efficient

* refine exclude interface

* fix tutorial

* fix tutorial

* fix graph duplication in CPU dataloader workers

* lint

* lint

* Revert "lint"

This reverts commit 805484dd553695111b5fb37f2125214a6b7276e9.

* Revert "lint"

This reverts commit 0bce411b2b415c2ab770343949404498436dc8b2.

* Revert "fix graph duplication in CPU dataloader workers"

This reverts commit 9e3a8cf34c175d3093c773f6bb023b155f2bd27f.
Co-authored-by: xiny <xiny@nvidia.com>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

* add

* fix

* fix

* fix

* fix

* add

* add

* fix

* fix

* fix

* new loader

* fix

* fix

* fix for 3.6

* fix

* add

* add receipes and also some bug fixes

* fix

* fix

* fix

* fix receipies

* allow AsNodeDataset to work on ogb

* add ut

* many fixes for nodepred-ns pipeline

* receipe for nodepred-ns

* Update enter/README.md
Co-authored-by: Zihao Ye <zihaoye.cs@gmail.com>

* fix layers

* fix

* fix

* fix

* fix

* fix multiple issues

* fix for citation2

* fix comment

* fix

* fix

* clean up

* fix
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
Co-authored-by: Minjie Wang <minjie.wang@nyu.edu>
Co-authored-by: Zihao Ye <zihaoye.cs@gmail.com>

* implement pin_memory/unpin_memory/is_pinned for dgl.graph

* update python docstring

* update c++ docstring

* add test

* fix the broken UnifiedTensor

* XPU_SWITCH for kDLCPUPinned

* a rough version ready for testing

* eliminate extra context parameter for pin/unpin

* update train_sampling

* fix linting

* fix typo

* multi-gpu uva sampling case

* disable new format materialization for pinned graphs

* update python doc for pin_memory_

* fix unit test

* UVA sampling for link prediction

* dispatch most csr ops

* update graphsage example to combine uva sampling and UnifiedTensor

* update graphsage example to combine uva sampling and UnifiedTensor

* update graphsage example to combine uva sampling and UnifiedTensor

* update doc

* update examples

* change unitgraph and heterograph's PinMemory to in-place

* update examples for multi-gpu uva sampling

* update doc

* fix linting

* fix cpu build

* fix is_pinned for DistGraph

* fix is_pinned for DistGraph

* update graphsage unsupervised example

* update doc for gpu sampling

* update some check for sampling device switching

* fix linting

* adapt for new dataloader

* fix linting

* fix

* fix some name issue

* adjust device check

* add unit test for uva sampling & fix some zero_copy bug

* fix linting

* update num_threads in graphsage examples
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

* implement pin_memory/unpin_memory/is_pinned for dgl.graph

* update python docstring

* update c++ docstring

* add test

* fix the broken UnifiedTensor

* eliminate extra context parameter for pin/unpin

* fix linting

* fix typo

* disable new format materialization for pinned graphs

* update python doc for pin_memory_

* fix unit test

* update doc

* change unitgraph and heterograph's PinMemory to in-place

* update comments for NDArray's PinMemory_ and PinData

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

* first commit

* a bunch of fixes

* add unique

* lint

* lint

* lint

* address comments

* Update negative_sampler.py

* fix

* description

* address comments and fix

* fix

* replace unique with replace

* test pylint

* Update negative_sampler.py

* support shared memory on windows

* Update shared_mem.cc

* Add pytorch-direct version

* remove

* add documentation for UnifiedTensor

* Revert "add documentation for UnifiedTensor"

This reverts commit 63ba42644d4aba197c1cb4ea4b85fa1bc43b8849.

* add boundary check for UVM IndexSelect

* relocate boundary check index kernels to cuda

* fix function name

* fix indexkernel in nccl api

* fix argument ordering

* simplify code

* Add a comment for the uvm version
Co-authored-by: shhssdm <shhssdm@gmail.com>
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* [Bugfix] fix a compile error for Debug-BuildType on Windows Platform

When using CMakeLists.txt to build the "Debug" BuildType on the Windows Platform, it has three compile errors (C4716) in the file "dgl\src\runtime\shared_mem.cc":

'dgl::runtime::SharedMemory::CreateNew': must return a value
'dgl::runtime::SharedMemory::Open': must return a value
'dgl::runtime::SharedMemory::Exist': must return a value

* [Bugfix] cmake error "cannot find load file" when DGL as a sub_directory on Linux

When using DGL as a subdirectory in a CMake Project, the "CMAKE_SOURCE_DIR" here will return the parent cmake scope dir, which is not a expected dir.
Maybe it is better to use "CMAKE_CURRENT_SOURCE_DIR" to set "GKLIB_PATH".

* [Bugfix] cmd cmake error when DGL as a subdirectory

When DGL as a subdirectory of another project, the WORKING_DIRECTORY of "add_custom_command" will be incorrect at the line 255 of "CMakeLists.txt", such that making a cmake "setlocal" error.

* [Feature] enable create/set/free cuda stream for internal use

* add unit test

* fix unit test failure on mxnet and tf

* refactor stream wrapper

* fix lint error

* fix lint error

Co-authored-by: JingchengYu94 <jingchengyu94@gmail.com>

* remove

* remove

* fix

* remove

* remove

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

* 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>

* Only link tensordispatcher against pytorch

* Only modify libraries when not using MSVC

[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>

* 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

Co-authored-by: Minjie Wang <wmjlyjemaine@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>

[Feature][Performance] Implement NCCL wrapper for communicating NodeEmbeddings and sparse gradients. (#2825)

* Split NCCL wrapper from sparse optimizer and sparse embedding

* Add more unit tests for single node nccl

* Fix unit test for tf

* Switch to device histogram

* Fix histgram issues

* Finish migration to histogram

* Handle cases with zero send/recieve data

* Start on partition object

* Get compiling

* Updates

* Add unit tests

* Switch to partition object

* Fix linting issues

* Rename partition file

* Add python doc

* Fix python assert and finish doxygen comments

* Remove stubs for range based partition to satisfy pylint

* Wrap unit test in GPU only

* Wrap explicit cuda call in ifdef

* Merge with partition.py

* update docstrings

* Cleanup partition_op

* Add Workspace object

* Switch to using workspace object

* Move last remainder based function out of nccl_api

* Add error messages

* Update docs with examples

* Fix linting erros
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>

* init cuda support

* cuSPARSE err

* passed unittest for csr_mm/SpGEMM. int64 not supported

* Debugging cuSPARSE error 3

* csrgeam only supports int32?

* disabling int64 for cuda

* refactor and add CSRMask

* lint

* oops

* remove todo

* rewrite CSRMask with CSRGetData

* lint

* fix test

* address comments

* lint

* fix

* addresses comments and rename BUG_ON
Co-authored-by: Israt Nisa <nisisrat@amazon.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-30-71.ec2.internal>
Co-authored-by: Quan Gan <coin2028@hotmail.com>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

[Bugfix] Wrap cub with CUB_NS_PREFIX and remove dependency on Thrust to linking issues with Torch 1.8 (#2758)

* Wrap cub with prefixes and remove thrust

* Using counting iterator
Co-authored-by: Zihao Ye <expye@outlook.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* finish graph matching gpu version

* use C++ shuffle

* finish graph matching

* fix bug

* fix bug

* change name and use swap

* upt

* fix format problem

* fix format problem

* stronger test

* upt

* upt

* change python api

* upt

* upt

* format check

* upt

* upt

* fix bug
Co-authored-by: Tong He <hetong007@gmail.com>

* Add start of to_block gpu implementation

* Pull in more changes from 0.4.2 cuda_to_block

* Move more code to IdArray

* Refactor DeviceNodeMapMaker

* Updates

* get compiling

* Integrate to_block

* Fix ID allocation

* Minor fixes

* Cleanup cuda calls to use cuda_common

* Reduce kernel calls

* Lint cleanup

* Expand documentation

* Remove unused function

* Rename variables for consistency

* Add doxygen comments

* Fix file extension

* Remove raw asynccopy for deviceapi

* Remove unused function

* Fix block/tile configuration

* Add cuda_device_common.cuh

* Add basic hashtable

* Migrate part of hashtable

* Refactor to use external hashtable

* Make functions members

* Format hash table functions

* Migrate duplicate filling

* Move last function over

* Refactor with cu file

* lint c++ code

* Move context check to C++ code

* Use macro switch

* Add missing files

* Update docstring

* update docs

* Move atomic functions

* Refactor hashtable

* Fix linting

* Expand docs

* Fix mismatched argument names

* Switch doxygen comments from using @param to \param
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>

* add tvm as submodule

* compilation is ok but calling fails

* can call now

* pack multiple modules, change names

* upd

* upd

* upd

* fix cmake

* upd

* upd

* upd

* upd

* fix

* relative path

* upd

* upd

* upd

* singleton

* upd

* trigger

* fix

* upd

* count reducible

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* upd

* only keep related files

* upd

* upd

* upd

* upd

* lint

* lint

* lint

* lint

* pylint

* upd

* upd

* compilation

* fix

* upd

* upd

* upd

* upd

* upd

* upd

* upd doc

* refactor

* fix

* upd number
Co-authored-by: Zhi Lin <linzhilynn@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-42-78.us-east-2.compute.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-21-156.us-east-2.compute.internal>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

* Add sparse embedding for dgl and update rgcn example

* upd

* Fix

* Revert "Fix"

This reverts commit 4da87cdfb8b8c3506b7fc7376cd2385ba8045c2a.

* Fix

* upd

* upd

* Fix

* Add unitest and update impl

* fix

* Clean up rgcn example code

* upd

* upd

* update

* Fix

* update score

* sparse for sage

* remove model sparse

* upd

* upd

* remove global norm

* revert delete model_sparse.py

* update according to comments

* Fix doc

* upd

* Fix test

* upd

* lint

* lint

* lint

* upd

* upd

* clean up
Co-authored-by: Ubuntu <ubuntu@ip-172-31-56-220.ec2.internal>

* Distributed heterograph (#3)

* heterogeneous graph partition.

* fix graph partition book for heterograph.

* load heterograph partitions.

* update DistGraphServer to support heterograph.

* make DistGraph runnable for heterograph.

* partition a graph and store parts with homogeneous graph structure.

* update DistGraph server&client to use homogeneous graph.

* shuffle node Ids based on node types.

* load mag in heterograph.

* fix per-node-type mapping.

* balance node types.

* fix for homogeneous graph

* store etype for now.

* fix data name.

* fix a bug in example.

* add profiler in rgcn.

* heterogeneous RGCN.

* map homogeneous node ids to hetero node ids.

* fix graph partition book.

* fix DistGraph.

* shuffle eids.

* verify eids and their mappings when loading a partition.

* Id map from homogneous Ids to per-type Ids.

* verify partitioned results.

* add test for distributed sampler.

* add mapping from per-type Ids to homogeneous Ids.

* update example.

* fix DistGraph.

* Revert "add profiler in rgcn."

This reverts commit 36daaed8b660933dac8f61a39faec3da2467d676.

* add tests for homogeneous graphs.

* fix a bug.

* fix test.

* fix for one partition.

* fix for standalone training and evaluation.

* small fix.

* fix two bugs.

* initialize projection matrix.

* small fix on RGCN.

* Fix rgcn performance (#17)
Co-authored-by: Ubuntu <ubuntu@ip-172-31-62-171.ec2.internal>

* fix lint.

* fix lint.

* fix lint.

* fix lint.

* fix lint.

* fix lint.

* fix.

* fix test.

* fix lint.

* test partitions.

* remove redundant test for partitioning.

* remove commented code.

* fix partition.

* fix tests.

* fix RGCN.

* fix test.

* fix test.

* fix test.

* fix.

* fix a bug.

* update dmlc-core.

* fix.

* fix rgcn.

* update readme.

* add comments.
Co-authored-by: Ubuntu <ubuntu@ip-172-31-2-202.us-west-1.compute.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-132.us-west-1.compute.internal>
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-62-171.ec2.internal>

* fix.

* fix.

* add div_int.

* fix.

* fix.

* fix lint.

* fix.

* fix.

* fix.

* adjust.

* move code.

* handle heterograph.

* return pytorch tensor in GPB.

* remove some tests in example.

* add to_block for distributed training.

* use distributed to_block.

* remove unnecessary function in DistGraph.

* remove distributed to_block.

* use pytorch tensor.

* fix a bug in ntypes and etypes.

* enable norm.

* make the data loader compatible with the old format.

* fix.

* add comments.

* fix a bug.

* add test for heterograph.

* support partition without reshuffle.

* add test.

* support partition without reshuffle.

* fix.

* add test.

* fix bugs.

* fix lint.

* fix dataset.

* fix for mxnet.

* update docstring.

* rename to floor_div

* avoid exposing NodePartitionPolicy and EdgePartitionPolicy.

* fix docstring.

* fix error.

* fixes.

* fix comments.

* rename.

* rename.

* explain IdMap.

* fix docstring.

* fix docstring.

* update docstring.

* remove the code of returning heterograph.

* remove argument.

* fix example.

* make GraphPartitionBook an abstract class.

* fix.

* fix.

* fix a bug.

* fix a bug in example

* fix a bug

* reverse heterograph sampling.

* temp fix.

* fix lint.

* Revert "temp fix."

This reverts commit c450717b9f578b8c48769c675f2a19d6c1e64381.

* compute norm.

* Revert "reverse heterograph sampling."

This reverts commit bd6deb7f52998de76508f800441ff518e2fadcb9.

* fix.

* move id_map.py

* remove check

* add more comments.

* update docstring.
Co-authored-by: Ubuntu <ubuntu@ip-172-31-2-202.us-west-1.compute.internal>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-9-132.us-west-1.compute.internal>
Co-authored-by: xiang song(charlie.song) <classicxsong@gmail.com>
Co-authored-by: Ubuntu <ubuntu@ip-172-31-62-171.ec2.internal>

* fix munmap() using wrong parameter

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