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    • Minjie Wang's avatar
      [Dist] New distributed data preparation pipeline (#4386) · 71ce1749
      Minjie Wang authored 
      * code changes for bug fixes identified during mag_lsc dataset (#4187)

* code changes for bug fixes identified during mag_lsc dataset

1. Changed from call torch.Tensor() to torch.from_numpy() to address memory corruption issues when creating large tensors. Tricky thing is this works correctly for small tensors.
2. Changed dgl.graph() function call to include 'num_nodes" argument to specifically mention all the nodes in  a graph partition.

* Update convert_partition.py

Moving the changes to the function "create_metadata_json" function to the "multiple-file-format" support, where this change is more appropriate. Since multiple machine testing was done with these code changes.

* Addressing review comments.

Removed space as suggested at the end of the line

* Revert "Revert "[Distributed Training Pipeline] Initial implementation of Distributed data processing step in the Dis… (#3926)" (#4037)"

This reverts commit 7c598aac

.

* Added code to support multiple-file-support feature and removed singl… (#4188)

* Added code to support multiple-file-support feature and removed single-file-support code

1. Added code to read dataset in multiple-file-format
2. Removed code for single-file format

* added files missing in the previous commit

This commit includes dataset_utils.py, which reads the dataset in multiple-file-format, gloo_wrapper function calls to support exchanging dictionaries as objects and helper functions in utils.py

* Update convert_partition.py

Updated function call "create_metadata_json" file to include partition_id so that each rank only creates its own metadata object and later on these are accumulated on rank-0 to create graph-level metadata json file.

* addressing code review comments during the CI process

code changes resulting from the code review comments received during the CI process.

* Code reorganization

Addressing CI comments and code reorganization for easier understanding.

* Removed commented out line

removed commented out line.

* Support new format for multi-file support in distributed partitioning. (#4217)

* Code changes for the following

1. Generating node data at each process
2. Reading csv files using pyarrow
3. feature complete code.

* Removed some typo's because of which unit tests were failing

1. Change the file name to correct file name when loading edges from file
2. When storing node-features after shuffling, use the correct key to store the global-nids of node features which are received after transmitted.

* Code changes to address CI comments by reviewers

1. Removed some redundant code and added text in the doc-strings to describe the functionality of some functions.
2 function signatures and invocations now match w.r.t argument list
3. Added detailed description of the metadata json structure so that the users understand the the type of information present in this file and how it is used through out the code.

* Addressing code review comments

1. Addressed all the CI comments and some of the changes include simplifying the code related to the concatenation of lists and enhancing the docstrings of functions which are changed in this process.

* Update docstring's of two functions appropriately in response to code review comments

Removed "todo" from the docstring of the gen_nodedata function.
Added "todo" to the gen_dist_partitions function when node-id to partition-id's are read for the first time.

Removed 'num-node-weights' from the docstring for the get_dataset function and added schema_map docstring to the argument list.

* [Distributed] Change for the new input format for distributed partitioning (#4273)

* Code changes to address the updated file format support for massively large graphs.

1. Updated the docstring for the starting function 'gen_dist_partitions" to describe the newly proposed file format for input dataset.
2. Code which was dependent on the structure of the old-metadata json object has been updated to read from the newly proposed metadata file.
3. Fixed some errors when appropriate functions were invoked and the calling function expects return values from the invoked furnction.
4. This modified code has been tested on "mag" dataset using 4-way partitions and verified the results

* Code changes to address the CI review comments

1. Improved docstrings for some functions.
2. Added a new function in the utils.py to compute the id ranges and this is used in multiple places.

* Added TODO to indicate the redundant data structure.

Because of the new file format changes, one of the dictionaries (node_feature_tids, node_tids) will be redundant. Added TODO text so that this will be removed in the next iteration of code changes.

* [Distributed] use alltoall fix to bypass gloo - alltoallv bug in distributed partitioning (#4311)

* Alltoall Fix to bypass gloo - alltoallv bug which is preventing further testing

1. Replaced alltoallv gloo wrapper call with alltoall message.
2. All the messages are padded to be of same length
3. Receiving side unpads the messages and continues processing.

* Code changes to address CI comments

1. Removed unused functions from gloo_wrapper.py
2. Changed the function signature of alltoallv_cpu_data as suggested.
3. Added docstring to include more description of the functionality inside alltoallv_cpu_data. Included more asserts to validate the assumptions.

* Changed the function name appropriately

Changed the function name from "alltoallv_cpu_data" to alltoallv_cpu which I believe is appropriate because underlying functionality is providing alltoallv which is basically alltoall_cpu + padding

* Added code and text to address the review comments.

1. Changed the function name to indicate the local use of this function.
2. Changed docstring to indicate the assumptions made by alltoallv_cpu function.

* Removed unused function from import statement

Removed unused/removed function from import statement.

* [Distributed] reduce memory consumption in distributed graph partitioning. (#4338)

* Fix for node_subgraph function, which seems to generate segmentation fault for very large partitions

1. Removed three graph dgl objects and we create the final dgl object directly by maintaining the following constraints
a) nodes are reordered so that local nodes are placed in the beginning of the nodes list compared to non-local nodes.
b)Edges order are maintained as passed into this function.
c) src/dst end points are mapped to target values based on the reshuffle'd nodes order.

* Code changes addressing CI comments for this PR

1. Used Da's suggested map to map nodes from old to new order.
This is much simpler and mem. efficient.

* Addressing CI Comments.

1. Reduced the amount of documentation to reflect the actual implementation.
2. named the mapping object appropriately.

* [Distributed] Graph chunking UX (#4365)

* first commit

* update

* huh

* fix

* update

* revert core

* fix

* update

* rewrite

* oops

* address comments

* add graph name

* address comments

* remove sample metadata file

* address comments

* fix

* remove

* add docs

* Adding launch script and wrapper script to trigger distributed graph … (#4276)

* Adding launch script and wrapper script to trigger distributed graph partitioning pipeline as defined in the UX document

1. dispatch_data.py is a wrapper script which builds the command and triggers the distributed partitioning pipeline
2. distgraphlaunch.py is the main python script which triggers the pipeline and to simplify its usage dispatch_data.py is included as a wrapper script around it.

* Added code to auto-detect python version and retrieve some parameters from the input metadata json file

1. Auto detect python version
2. Read the metadata json file and extract some parameters to pass to the user defined command which is used to trigger the pipeline.

* Updated the json file name to metadata.json file per UX documentation

1. Renamed json file name per UX documentation.

* address comments

* fix

* fix doc

* use unbuffered logging to cure anxiety

* cure more anxiety

* Update tools/dispatch_data.py
Co-authored-by: default avatarMinjie Wang <minjie.wang@nyu.edu>

* oops
Co-authored-by: default avatarQuan Gan <coin2028@hotmail.com>
Co-authored-by: default avatarMinjie Wang <minjie.wang@nyu.edu>
Co-authored-by: default avatarkylasa <kylasa@gmail.com>
Co-authored-by: default avatarDa Zheng <zhengda1936@gmail.com>
Co-authored-by: default avatarQuan (Andy) Gan <coin2028@hotmail.com>
      71ce1749
  13. 10 Aug, 2022 4 commits
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  25. 30 Jul, 2022 2 commits
  27. 29 Jul, 2022 1 commit
    • Xin Yao's avatar
      [Feature] Add CUDA Weighted Neighborhood Sampling (#4064) · 86c81b4e
      Xin Yao authored 
      

* add weighted sampling without replacement (A-Chao)

* improve Algorithm A-Chao with block-wise prefix sum

* correctly fill out_idxs

* implement weighted sampling with replacement

* small fix

* merge host-side code of weighted/uniform sampling

* enable unit tests for cuda weighted sampling

* move thrust/cub wrapper to the cmake file

* update docs accordingly

* fix linting

* fix linting

* fix unit test

* Bump external CUB/Thrust versions

* Fix code style and update description of algorithm design

* [Feature] GPU support weighted graph neighbor sampling
commit by pengqirong(OPPO)

* merge pengqirong's implementation

* revert the change to cub and thrust

* fix linting

* use DeviceSegmentedSort for better performance

* add more comments

* add necessary notes

* add necessary notes

* resolve some comments

* define THRUST_CUB_WRAPPED_NAMESPACE

* fix doc
Co-authored-by: default avatar彭齐荣 <657017034@qq.com>
      86c81b4e
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