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updated for release 22.02 (#2034)
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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: #2034
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BradReesWork authored Jan 25, 2022
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9 changes: 7 additions & 2 deletions README.md
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Expand Up @@ -79,7 +79,7 @@ _Italic_ algorithms are planned for future releases.
| Link Analysis| | | |
| | Pagerank | Multi-GPU | [C++ README](cpp/src/centrality/README.md#Pagerank) |
| | Personal Pagerank | Multi-GPU | [C++ README](cpp/src/centrality/README.md#Personalized-Pagerank) |
| | HITS | Single-GPU | leverages Gunrock |
| | HITS | Single-GPU | Multi-GPU C code is ready, Python wrapper in 22.04 |
| Link Prediction | | | |
| | Jaccard Similarity | Single-GPU | |
| | Weighted Jaccard Similarity | Single-GPU | |
Expand All @@ -88,7 +88,8 @@ _Italic_ algorithms are planned for future releases.
| | _Local Clustering Coefficient_ | --- | |
| Sampling | | | |
| | Random Walks (RW) | Single-GPU | Biased and Uniform |
| | _node2vec_ | --- | |
| | Egonet | Single-GPU | multi-seed |
| | _node2vec_ | --- | C code is ready, Python wrapper coming in 22.04 |
| Traversal | | | |
| | Breadth First Search (BFS) | Multi-GPU | with cutoff support <br/> [C++ README](cpp/src/traversal/README.md#BFS) |
| | Single Source Shortest Path (SSSP) | Multi-GPU | [C++ README](cpp/src/traversal/README.md#SSSP) |
Expand All @@ -98,6 +99,7 @@ _Italic_ algorithms are planned for future releases.
| Other | | | |
| | Renumbering | Multi-GPU | multiple columns, any data type |
| | Symmetrize | Multi-GPU | |
| | Path Extraction | | Extract paths from BFS/SSP results in parallel |
| Data Generator | | | |
| | RMAT | Multi-GPU | |
| | _Barabasi-Albert_ | --- | |
Expand Down Expand Up @@ -170,6 +172,9 @@ conda install -c nvidia -c rapidsai -c numba -c conda-forge cugraph cudatoolkit=

# CUDA 11.4
conda install -c nvidia -c rapidsai -c numba -c conda-forge cugraph cudatoolkit=11.4

# CUDA 11.5
conda install -c nvidia -c rapidsai -c numba -c conda-forge cugraph cudatoolkit=11.5
```

Note: This conda installation only applies to Linux and Python versions 3.7/3.8.
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