GitLab

* 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>

* enable turn on/off libxsmm at runtime by adding a global config and related API
Co-authored-by: Ubuntu <ubuntu@ip-172-31-19-194.ap-northeast-1.compute.internal>

* Allocate tensors in DGL's current stream

* make tensoradaptor stream-aware

* replace TAemtpy with cpu allocator

* fix typo

* try fix cpu allocation

* clean header

* redirect AllocDataSpace as well

* resolve comments

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

* * Added missing specializations for `__half` of `DLDataTypeTraits`, `IndexSelect`, `Full`, `Scatter_`, `CSRGetData`, `CSRMM`, `CSRSum`, `IndexSelectCPUFromGPU`
* Fixed casting issue in `_LinearSearchKernel` that was preventing it from supporting `__half`
* Added `#if`'d out specializations of `CSRGEMM`, `CSRGEAM`, and `Xgeam`, which would require functions that aren't currently provided by cublas

* * Added more specific error messages for unimplemented FP16 specializations of Xgeam, CSRGEMM, and CSRGEAM

* * Added missing instantiation of DLDataTypeTraits<__half>::dtype

* * Fixed linter error
* Added clearer comment explaining why the cast to long long is necessary

* * Worked around a compile error in some particular setup, where __half can't be constructed on the host side

* * Fixed linter formatting errors

* * Changes to comments as recommended

* * Made recommended changes to logging errors in FP16 specializations
* Also changed the existing Xgeam function for unsupported data types from LOG(INFO) to LOG(FATAL)

* Explicitly unpin tensoradapter allocated arrays

* Undo unrelated change

* Add unit test

* update unit test

* add pinned_by_dgl flag to NDArray::Container

* use dgl.ndarray for holding the pinning status

* update multi-gpu uva inference

* reinterpret cast NDArray::Container* to DLTensor* in MoveAsDLTensor

* update unpin column and examples

* add unit test for unpin column
Co-authored-by: Dominique LaSalle <dlasalle@nvidia.com>
Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>

This reverts commit fdd1fe19.

* Explicitly unpin tensoradapter allocated arrays

* Undo unrelated change

* Add unit test

* update unit test

* [BugFix] record/restore pin status when pickle/unpickle

* disable test on TF

* set version as expected

* unpin memory in test

* fix

* remove setcxx methods

* move pin flag to CSR and COO matrix
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

* fix

* raise an error

* fix docserver crash

* huuuuge update

* remove

* lint

* lint

* fix

* what happened to nccl

* update multi-gpu unsupervised graphsage example

* replace most of the dgl.mp.process with torch.mp.spawn

* update if condition for use_uva case

* update user guide

* address comments

* incorporating suggestions from @jermainewang

* oops

* fix tutorial to pass CI

* oops

* fix again
Co-authored-by: Xin Yao <xiny@nvidia.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>

* 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>

* Pass the std:min argument's type, to avoid the compilation error.

* Update parallel_for.h

* Update negative_sampling.cc
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.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

* first commit

* second commit

* spaghetti unit tests

* rewrite test

* [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

* graceful c++ exception in OpenMP

* credits

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

* [Feature] Exclude edges in sample_neighbors

Extending sample_neighbors and sample_frontier
API to support exclude_edges parameter.

exclude_edges support tensor and dict data
Feature enable excluding certain edges
during neighborhood sampling
Exclude_edges contains EID's of edges
which will be excluded
during neighbor picking for seed nodes.

Added test case for heterograph and homograph
RFC issue id: 2944

* compatibility

* fix

* fix
Co-authored-by: Quan Gan <coin2028@hotmail.com>

* [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>

* 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>

[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>

* 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>

* 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>

* 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>

* 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>

* [CPU Parallel] implementation of parallel_for with grain size

* Create parallel_for.h

* Update parallel_for.h
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.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>

* 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>