GitLab

* [Misc] clang-format auto fix.

* manual

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

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

* rename `DLContext` to `DGLContext`

* rename `kDLGPU` to `kDLCUDA`

* replace DLTensor with DGLArray

* fix linting

* Unify DGLType and DLDataType to DGLDataType

* Fix FFI

* rename DLDeviceType to DGLDeviceType

* decouple dlpack from the core library

* fix bug

* fix lint

* fix merge

* fix build

* address comments

* rename dl_converter to dlpack_convert

* remove redundant comments

* add set_stream

* add .record_stream for NDArray and HeteroGraph

* refactor dgl stream Python APIs

* test record_stream

* add unit test for record stream

* use pytorch's stream

* fix lint

* fix cpu build

* address comments

* address comments

* add record stream tests for dgl.graph

* record frames and update dataloder

* add docstring

* update frame

* add backend check for record_stream

* remove CUDAThreadEntry::stream

* record stream for newly created formats

* fix bug

* fix cpp test

* fix None c_void_p to c_handle

* Use an internal cuda stream for CopyDataFromTo

* small fix white space

* Fix to compile

* Make stream optional in copydata for compile

* fix lint issue

* Update cub functions to use internal stream

* Lint check

* Update CopyTo/CopyFrom/CopyFromTo to use internal stream

* Address comments

* Fix backward CUDA stream

* Avoid overloading CopyFromTo()

* Minor comment update

* Overload copydatafromto in cuda device api
Co-authored-by: xiny <xiny@nvidia.com>

* fix

* explain

* oops

* gpu compact graph template

* cuda compact graph draft

* fix typo

* compact graphs

* pass unit test but fail in training

* example using EdgeDataLoader on the GPU

* refactor cuda_compact_graph and cuda_to_block

* update training scripts

* fix linting

* fix linting

* fix exclude_edges for the GPU

* add --data-cpu & fix copyright

[Performance][Feature] Add `src_nodes` paramter to `to_block()` to avoid cost running unique() when available. (#2973)

* Add lhs_nodes are paremeter to to_block

* Update unit test

* Switch to simplified node conversion

* Switch lhs_nodes to be in/out parameter

* Update docs
Co-authored-by: Da Zheng <zhengda1936@gmail.com>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Minjie Wang <wmjlyjemaine@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>

* 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>