* 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)
---------
Co-authored-by: Ubuntu <ubuntu@ip-172-31-15-137.us-west-2.compute.internal>
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
* add bf16 specializations
* remove SWITCH_BITS
* enable amp for bf16
* remove SWITCH_BITS for cpu kernels
* enbale bf16 based on CUDART
* fix compiling for sm<80
* fix cpu build
* enable unit tests
* update doc
* disable test for CUDA < 11.0
* address comments
* address 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>
* 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
* * 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>
* 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>
* [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
* [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
* [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>
* first commit
* some thoughts
* move around
* more commit
* more fixes
* now it uses torch allocator
* fix symbol export error
* fix
* fixes
* test fix
* add script
* building separate library per version
* fix for vs2019
* more fixes
* fix on windows build
* update jenkinsfile
* auto copy built dlls for windows
* lint and installation guide update
* fix
* specify conda environment
* set environment for ci
* fix
* fix
* fix
* fix again
* revert
* fix cmake
* fix
* switch to using python interpreter path
* remove scripts
* debug
* oops sorry
* Update index.rst
* Update index.rst
* copies automatically, no need for this
* do not print message if library not found
* tiny fixes
* debug on nightly
* replace add_compile_definitions to make CMake 3.5 happy
* fix linking to wrong lib for multiple pytorch envs
* changed building strategy
* fix nightly
* fix windows
* fix windows again
* setup bugfix
* address comments
* change README
* Add async transferer class
* Add async ndarray copy interface
* Add python bindings
* Fix comment
* Add python class
* Fix linting issues
* Add python unit test
* Update python interface
* move async_transferer to cuda only directory
* Fix linting issue
* Move out of contrib
* Add doc strings
* Move test compute from backend
* Update comment
* Fix test naming
* Fix argument usage
* Wrap/unwrap backend parameters
* Move to dataloading
* Move to 'dataloading'
* Make GPU/CPU compatible
* Fix unit tests
* Add docs
* Use only backend interface for datamovement in unit test