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Fix Merge Conflicts for 2024 #2040

Merged
merged 22 commits into from
Jan 27, 2022
Merged

Fix Merge Conflicts for 2024 #2040

merged 22 commits into from
Jan 27, 2022

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This PR includes 2 changes:

shwina and others added 22 commits January 20, 2022 16:55
@shwina
Fix call to getDeviceAttribute following API change in RMM. (rapids…
487143c 
…ai#2008)

Please do not merge until rapidsai/rmm#930 is merged.

For the reasons described in that PR, this API has changed to accept a `cuda.cudart.cudaDeviceAttr` object, `cuda` being the official CUDA Python bindings package.

Authors:
  - Ashwin Srinath (https://github.com/shwina)

Approvers:
  - Brad Rees (https://github.com/BradReesWork)
  - Rick Ratzel (https://github.com/rlratzel)
  - AJ Schmidt (https://github.com/ajschmidt8)

URL: rapidsai#2008
@jjacobelli
Prepare upload scripts for Python 3.7 removal (rapidsai#2027)
c009679 
As we will remove Python 3.7, we need to update the Python version in the upload scripts

Authors:
  - Jordan Jacobelli (https://github.com/Ethyling)

Approvers:
  - Sevag Hanssian (https://github.com/sevagh)
  - AJ Schmidt (https://github.com/ajschmidt8)

URL: rapidsai#2027
@seunghwak
Fix Louvain hang in multi-GPU testing (rapidsai#2028)
a2b8d5a 
If the CSR + DCSR hybrid format is used to store a graph, the size of the offset array can be smaller than the number of vertices + 1. The previous code didn't consider this in calling cub's segmented sort. This PR fixes this mistake.

Authors:
  - Seunghwa Kang (https://github.com/seunghwak)

Approvers:
  - Chuck Hastings (https://github.com/ChuckHastings)
  - Brad Rees (https://github.com/BradReesWork)

URL: rapidsai#2028
@acostadon
Updated build.sh help text and test execution steps in SOURCEBUILD.md (…
abc6492 
…rapidsai#2020)

Authors:
  - Don Acosta (https://github.com/acostadon)

Approvers:
  - Brad Rees (https://github.com/BradReesWork)

URL: rapidsai#2020
@jjacobelli
Fix build script (rapidsai#2029)
197db5e 
The directory moving for `cugraph` was missing a `*` in the `cp` command which was creating the wrong directory hierarchy. Fixing this by using `mv` instead

Authors:
  - Jordan Jacobelli (https://github.com/Ethyling)

Approvers:
  - Sevag Hanssian (https://github.com/sevagh)
  - AJ Schmidt (https://github.com/ajschmidt8)
  - Brad Rees (https://github.com/BradReesWork)

URL: rapidsai#2029
@ChuckHastings
Add SSSP API, test and implementation (rapidsai#2016)
f4b5f3d 
@rlratzel needed the SSSP C API squeezed into version 22.02.  Skipped the usual API PR and implementation PR to squeeze these together in the interest of time.  Note that SSSP is nearly identical (semantically) to BFS which is already in the C API using a similar API.

This PR provides:
* C API definition of SSSP
* C unit test for SSSP
* Implementation of the C API of SSSP (calling the underlying C++ implementation)

Authors:
  - Chuck Hastings (https://github.com/ChuckHastings)

Approvers:
  - Brad Rees (https://github.com/BradReesWork)
  - Seunghwa Kang (https://github.com/seunghwak)
  - Rick Ratzel (https://github.com/rlratzel)

URL: rapidsai#2016
@trxcllnt
Remove FAISS dependency, inherit other common dependencies from raft (r…
bae28f7 
…apidsai#1863)

Originally this PR was about building FAISS shared libs via CPM, but @rlratzel mentioned cuGraph doesn't need FAISS anymore, and it'd be better if we remove it.

If we need FAISS again in the future, we can add `faiss::faiss` back to `target_link_libraries` without needing extra CPM configuration as it will be available [via raft](rapidsai/raft#345).

Edit: Removed more dependencies that we inherit from raft and/or rmm. Depends on rapidsai/raft#345.

Edit 2: I think the CUDA 11.0 thrust issue will be solved by rapidsai/rapids-cmake#98

Authors:
  - Paul Taylor (https://github.com/trxcllnt)
  - Divye Gala (https://github.com/divyegala)

Approvers:
  - Brad Rees (https://github.com/BradReesWork)
  - AJ Schmidt (https://github.com/ajschmidt8)

URL: rapidsai#1863
@rlratzel
Removed unused CI files (rapidsai#2017)
83e8079 
After an internal discussion, it was determined the `Dockerfile` has not been in use since RAPIDS `devel` and `runtime` Docker images have been released.

The `ci/local` dir is also not working as originally intended (it was originally created to allow devs to reproduce CI failures locally) because the script does not support Project Flash. Since the script cannot be easily updated for Project Flash, it'll just be removed.

Authors:
  - Rick Ratzel (https://github.com/rlratzel)

Approvers:
  - AJ Schmidt (https://github.com/ajschmidt8)

URL: rapidsai#2017
@galipremsagar
Pin dask & distributed (rapidsai#2031)
4032f34 
Changed to be in-line with: rapidsai/cudf#10108

Authors:
  - GALI PREM SAGAR (https://github.com/galipremsagar)

Approvers:
  - Brad Rees (https://github.com/BradReesWork)
  - AJ Schmidt (https://github.com/ajschmidt8)

URL: rapidsai#2031
@jjacobelli
Fix raft git ref (rapidsai#2032)
12b53c8 
Authors:
  - Jordan Jacobelli (https://github.com/Ethyling)

Approvers:
  - Robert Maynard (https://github.com/robertmaynard)
  - Rick Ratzel (https://github.com/rlratzel)
  - Brad Rees (https://github.com/BradReesWork)

URL: rapidsai#2032
@rlratzel
Initial PropertyGraph implementation and tests (rapidsai#1999)
afeebee 
Initial implementation of the `PropertyGraph` graph class and corresponding unit tests.
```
pG = cugraph.experimental.PropertyGraph()

# Add properties
pG.add_vertex_data(...)
pG.add_edge_data(...)

# Select specific vertices and edges based on conditions
selection = pG.select_vertices("(user_location==47906) | (user_location==78750)")
selection += pG.select_edges("_TYPE_=='referrals'")

# Extract a subgraph using selection
G = pG.extract_subgraph(selection=selection,
                        create_using=DiGraph_inst,
                        edge_weight_property="review_rating")

# run some algo on G, get algo_results

# annotate results with properties
algo_results_with_properties = pG.annotate_dataframe(algo_results, G, edge_vertex_id_columns=("from", "to"))

# Add algo results back to the PropertyGraph for further analysis
pG.add_edge_data(algo_results, type_name="referral_data", vertex_id_columns=("from", "to"))
```

closes rapidsai#1876

Authors:
  - Rick Ratzel (https://github.com/rlratzel)
  - Don Acosta (https://github.com/acostadon)

Approvers:
  - Don Acosta (https://github.com/acostadon)
  - Brad Rees (https://github.com/BradReesWork)

URL: rapidsai#1999
@BradReesWork
updated for release 22.02 (rapidsai#2034)
63efaea 
Updated the README with latest algorithm info and update the release benchmark notebook to include additional comparisons

Authors:
  - Brad Rees (https://github.com/BradReesWork)

Approvers:
  - Rick Ratzel (https://github.com/rlratzel)

URL: rapidsai#2034
@chirayuG-nvidia
Add optimized 2x string column renumbering code (rapidsai#1996)
e0038f0 
Authors:
  - https://github.com/chirayuG-nvidia

Approvers:
  - Chuck Hastings (https://github.com/ChuckHastings)

URL: rapidsai#1996
@rlratzel
Python API updates to enable explicit control of internal graph_t c…
4dfbec4 
…reation and deletion (rapidsai#2023)

Python API updates to enable explicit control of internal `graph_t` creation and deletion. These changes will allow users who need more control over how the internal `graph_t` object is managed to have additional APIs to do so.  Current cugraph algos construct the appropriate `graph_t` at the C++ boundary, run the algo, and destroy the object each time.  This is more convenient and safer in some cases since it does not require the user to understand the necessary data format requirements for each algo (CSC, CSR, etc.), but it adds overhead to each algo call. If a user knows which algos will be called ahead of time and the relevant graph creation options to use, they can reuse the underlying `graph_t` object and eliminate the redundant creation/deletion expense.  These APIs also allow for benchmarks to measure only the algo run time without the initial graph creation time.

These changes are grouped into a category of enhancements sometimes referred to as "expert mode"

Changes here include:
* Updates to `pylibcugraph` to add the APIs from the `libcugraph_c` library for `graph_t` management and calling Pagerank and SSSP
* Addition of the `experimental` namespace to `pylibcugraph`, which is where some of the new APIs will be until we finalize decisions on names, signatures, etc.
* <s>Updates to cugraph Graph classes, Pagerank, and SSSP algos to call in to `pylibcugraph`</s>

Authors:
  - Rick Ratzel (https://github.com/rlratzel)
  - Chuck Hastings (https://github.com/ChuckHastings)
  - Seunghwa Kang (https://github.com/seunghwak)

Approvers:
  - Chuck Hastings (https://github.com/ChuckHastings)
  - Seunghwa Kang (https://github.com/seunghwak)
  - Brad Rees (https://github.com/BradReesWork)

URL: rapidsai#2023
@rlratzel
Python API updates to enable explicit control of internal graph_t c…
3668d8c 
…reation and deletion (rapidsai#2023)

Python API updates to enable explicit control of internal `graph_t` creation and deletion. These changes will allow users who need more control over how the internal `graph_t` object is managed to have additional APIs to do so.  Current cugraph algos construct the appropriate `graph_t` at the C++ boundary, run the algo, and destroy the object each time.  This is more convenient and safer in some cases since it does not require the user to understand the necessary data format requirements for each algo (CSC, CSR, etc.), but it adds overhead to each algo call. If a user knows which algos will be called ahead of time and the relevant graph creation options to use, they can reuse the underlying `graph_t` object and eliminate the redundant creation/deletion expense.  These APIs also allow for benchmarks to measure only the algo run time without the initial graph creation time.

These changes are grouped into a category of enhancements sometimes referred to as "expert mode"

Changes here include:
* Updates to `pylibcugraph` to add the APIs from the `libcugraph_c` library for `graph_t` management and calling Pagerank and SSSP
* Addition of the `experimental` namespace to `pylibcugraph`, which is where some of the new APIs will be until we finalize decisions on names, signatures, etc.
* <s>Updates to cugraph Graph classes, Pagerank, and SSSP algos to call in to `pylibcugraph`</s>

Authors:
  - Rick Ratzel (https://github.com/rlratzel)
  - Chuck Hastings (https://github.com/ChuckHastings)
  - Seunghwa Kang (https://github.com/seunghwak)

Approvers:
  - Chuck Hastings (https://github.com/ChuckHastings)
  - Seunghwa Kang (https://github.com/seunghwak)
  - Brad Rees (https://github.com/BradReesWork)

URL: rapidsai#2023
@rlratzel
Python API updates to enable explicit control of internal graph_t c…
8e6f26e 
…reation and deletion (rapidsai#2023)

Python API updates to enable explicit control of internal `graph_t` creation and deletion. These changes will allow users who need more control over how the internal `graph_t` object is managed to have additional APIs to do so.  Current cugraph algos construct the appropriate `graph_t` at the C++ boundary, run the algo, and destroy the object each time.  This is more convenient and safer in some cases since it does not require the user to understand the necessary data format requirements for each algo (CSC, CSR, etc.), but it adds overhead to each algo call. If a user knows which algos will be called ahead of time and the relevant graph creation options to use, they can reuse the underlying `graph_t` object and eliminate the redundant creation/deletion expense.  These APIs also allow for benchmarks to measure only the algo run time without the initial graph creation time.

These changes are grouped into a category of enhancements sometimes referred to as "expert mode"

Changes here include:
* Updates to `pylibcugraph` to add the APIs from the `libcugraph_c` library for `graph_t` management and calling Pagerank and SSSP
* Addition of the `experimental` namespace to `pylibcugraph`, which is where some of the new APIs will be until we finalize decisions on names, signatures, etc.
* <s>Updates to cugraph Graph classes, Pagerank, and SSSP algos to call in to `pylibcugraph`</s>

Authors:
  - Rick Ratzel (https://github.com/rlratzel)
  - Chuck Hastings (https://github.com/ChuckHastings)
  - Seunghwa Kang (https://github.com/seunghwak)

Approvers:
  - Chuck Hastings (https://github.com/ChuckHastings)
  - Seunghwa Kang (https://github.com/seunghwak)
  - Brad Rees (https://github.com/BradReesWork)

URL: rapidsai#2023
@rlratzel
Python API updates to enable explicit control of internal graph_t c…
a0661ff 
…reation and deletion (rapidsai#2023)

Python API updates to enable explicit control of internal `graph_t` creation and deletion. These changes will allow users who need more control over how the internal `graph_t` object is managed to have additional APIs to do so.  Current cugraph algos construct the appropriate `graph_t` at the C++ boundary, run the algo, and destroy the object each time.  This is more convenient and safer in some cases since it does not require the user to understand the necessary data format requirements for each algo (CSC, CSR, etc.), but it adds overhead to each algo call. If a user knows which algos will be called ahead of time and the relevant graph creation options to use, they can reuse the underlying `graph_t` object and eliminate the redundant creation/deletion expense.  These APIs also allow for benchmarks to measure only the algo run time without the initial graph creation time.

These changes are grouped into a category of enhancements sometimes referred to as "expert mode"

Changes here include:
* Updates to `pylibcugraph` to add the APIs from the `libcugraph_c` library for `graph_t` management and calling Pagerank and SSSP
* Addition of the `experimental` namespace to `pylibcugraph`, which is where some of the new APIs will be until we finalize decisions on names, signatures, etc.
* <s>Updates to cugraph Graph classes, Pagerank, and SSSP algos to call in to `pylibcugraph`</s>

Authors:
  - Rick Ratzel (https://github.com/rlratzel)
  - Chuck Hastings (https://github.com/ChuckHastings)
  - Seunghwa Kang (https://github.com/seunghwak)

Approvers:
  - Chuck Hastings (https://github.com/ChuckHastings)
  - Seunghwa Kang (https://github.com/seunghwak)
  - Brad Rees (https://github.com/BradReesWork)

URL: rapidsai#2023
@rlratzel
Python API updates to enable explicit control of internal graph_t c…
aecd54a 
…reation and deletion (rapidsai#2023)

Python API updates to enable explicit control of internal `graph_t` creation and deletion. These changes will allow users who need more control over how the internal `graph_t` object is managed to have additional APIs to do so.  Current cugraph algos construct the appropriate `graph_t` at the C++ boundary, run the algo, and destroy the object each time.  This is more convenient and safer in some cases since it does not require the user to understand the necessary data format requirements for each algo (CSC, CSR, etc.), but it adds overhead to each algo call. If a user knows which algos will be called ahead of time and the relevant graph creation options to use, they can reuse the underlying `graph_t` object and eliminate the redundant creation/deletion expense.  These APIs also allow for benchmarks to measure only the algo run time without the initial graph creation time.

These changes are grouped into a category of enhancements sometimes referred to as "expert mode"

Changes here include:
* Updates to `pylibcugraph` to add the APIs from the `libcugraph_c` library for `graph_t` management and calling Pagerank and SSSP
* Addition of the `experimental` namespace to `pylibcugraph`, which is where some of the new APIs will be until we finalize decisions on names, signatures, etc.
* <s>Updates to cugraph Graph classes, Pagerank, and SSSP algos to call in to `pylibcugraph`</s>

Authors:
  - Rick Ratzel (https://github.com/rlratzel)
  - Chuck Hastings (https://github.com/ChuckHastings)
  - Seunghwa Kang (https://github.com/seunghwak)

Approvers:
  - Chuck Hastings (https://github.com/ChuckHastings)
  - Seunghwa Kang (https://github.com/seunghwak)
  - Brad Rees (https://github.com/BradReesWork)

URL: rapidsai#2023
@gitbuda
Fix optional and cstddef includes (rapidsai#1998)
e0e66c5 
Authors:
  - Marko Budiselić (https://github.com/gitbuda)
  - Brad Rees (https://github.com/BradReesWork)

Approvers:
  - Seunghwa Kang (https://github.com/seunghwak)
  - Chuck Hastings (https://github.com/ChuckHastings)

URL: rapidsai#1998
@betochimas
Initial automated doctest, all current examples now pass, other docum…
2e781c1 
…entation edits (rapidsai#2014)

Closes rapidsai#2012 and rapidsai#2022

Authors:
  - https://github.com/betochimas

Approvers:
  - Don Acosta (https://github.com/acostadon)
  - Rick Ratzel (https://github.com/rlratzel)

URL: rapidsai#2014
@ajschmidt8
Merge branch 'branch-22.02' into 'branch-22.04'.
2db7710
@ajschmidt8
rm dask/distributed upper pins
9557f03
@ajschmidt8 ajschmidt8 added improvement Improvement / enhancement to an existing function non-breaking Non-breaking change labels Jan 27, 2022
@ajschmidt8 ajschmidt8 requested review from a team as code owners January 27, 2022 15:29
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@ajschmidt8 ajschmidt8 merged commit aa0704c into rapidsai:branch-22.04 Jan 27, 2022
@ajschmidt8 ajschmidt8 deleted the merge-22.02-into-22.04 branch January 27, 2022 15:50
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