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UVM notebook update and add tracker for notebooks to readme #3595

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May 23, 2023
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25 changes: 24 additions & 1 deletion notebooks/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -61,9 +61,32 @@ Running the example in these notebooks requires:
* CUDA 11.4+
* NVIDIA driver 450.51+



## Notebooks outside the algorithm subdirectory are specified here along with what they need to run
They are not currently tested daily due to run constraints so we will keep track of special
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reword - do not start with "they"

and the latest fixes/tests

|Notebook |Location |Environment |Extra Dependencies|Notes |
|----------------------|-------------------------|------------------|------------------|---------------------------------------------|
|batch_betweenness |N/A | | |removed due to missing batch algorithm 23.0 |
|mg_louvain |demo |cugraph conda |None |fixed in PR #3558/23.06 |
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is "cugraph conda" defined?

|mg_pagerank |demo |cugraph conda |None |fixed in PR #3558/23.06 |
|mg_property_graph |demo |cugraph conda |None |fixed in PR #3558/23.06 |
|uvm |demo |cugraph conda |None |fixed in PR/23.06 |
|CostMatrix |applications |cugraph conda |None |fixed in PR #3551/23.06 |
|gen_550M |applications |cugraph conda |None |tested and documented PR #3551/23.06 |
|multi_gpu_pagerank |contrib/community/cugraph|cugraph conda |None |fixed notebook-contrib PR #374/23.06 |
|bfs_benchmark |cugraph_benchmark |cugraph conda |None |fixed in PR #3561/23.06 |
|louvain_benchmark |cugraph_benchmark |cugraph conda |None |fixed in PR #3561/23.06 |
|pagerank_benchmark |cugraph_benchmark |cugraph conda |None |fixed in PR #3561/23.06 |
|sssp_benchmark |cugraph_benchmark |cugraph conda |None |fixed in PR #3561/23.06 |



#### Copyright

Copyright (c) 2019-2022, NVIDIA CORPORATION. All rights reserved.
Copyright (c) 2019-2023, NVIDIA CORPORATION. All rights reserved.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

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37 changes: 29 additions & 8 deletions notebooks/demo/uvm.ipynb
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@@ -1,22 +1,31 @@
{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Oversubscribing GPU memory in cuGraph\n",
"#### Author : Alex Fender\n",
"# Skip notebook test\n",
"\n",
"\n",
"In this notebook, we will show how to **scale to 4x larger graphs than before** without incurring a performance drop using managed memory features in cuGraph. We will compute the PageRank of each user in Twitter's dataset on a single GPU as an example. This technique applies to all features.\n",
"\n",
"Unified Memory is a single memory address space accessible from any processor in a system. If a kernel tries to access any absent pages,the Page Migration Engine migrates the pages. When the GPU memory is full, the least recently used pages are evicted. In other words, Unified Memory transparently enables oversubscribing GPU memory, enabling out-of-core computations.\n",
"\n",
"\n",
"This notebook was tested on an NVIDIA 48GB RTX8000 GPU using RAPIDS 0.14 and CUDA 10.2. Please be aware that your system may be different, and you may need to modify the code or install packages to run the below examples. If you think you have found a bug or an error, please file an issue in [cuGraph](https://github.com/rapidsai/cugraph/issues)"
"This notebook was tested on an NVIDIA 48GB RTX8000 GPU using RAPIDS 0.14 and CUDA 10.2. Please be aware that your system may be different, and you may need to modify the code or install packages to run the below examples. If you think you have found a bug or an error, please file an issue in [cuGraph](https://github.com/rapidsai/cugraph/issues)\n",
"\n",
"| Author Credit | Date | Update | cuGraph Version | Test Hardware |\n",
"|-----------------|------------|-----------------------|-----------------|--------------------------------|\n",
"|Alex Fender | 05/15/2020 | created | 0.14 | RTX8000 48G GPU CUDA 10.2 |\n",
"|Chuck Hastings | 02/21/2021 | incorporate dendrogram| 0.18 | |\n",
"|Jordan Jacobelli | 11/08/2021 | update dataset URL | 23.04 | |\n",
"| Don Acosta | 05/21/2023 | updated/tested | 23.06 nightly | 2xA6000 CUDA 11.7 |\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -30,6 +39,7 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand Down Expand Up @@ -58,6 +68,7 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -78,13 +89,15 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"### Get the data"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand Down Expand Up @@ -135,6 +148,7 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -159,6 +173,7 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -174,8 +189,8 @@
"t_start = time.time()\n",
"\n",
"# Create a directed graph using the source (src) and destination (dst) vertex pairs from the Dataframe \n",
"G = cugraph.DiGraph()\n",
"G.from_cudf_edgelist(e_list, source='src', destination='dst', renumber=False)\n",
"G = cugraph.Graph(directed=True)\n",
"G.from_cudf_edgelist(e_list, source='src', destination='dst', renumber=False, store_transposed=True)\n",
"\n",
"# (optional) request the transposed here so that we can analyse pagerank solver time alone\n",
"G.view_transposed_adj_list()\n",
Expand All @@ -185,6 +200,7 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -210,6 +226,7 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -218,6 +235,7 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand Down Expand Up @@ -249,6 +267,7 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -264,6 +283,7 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
Expand All @@ -275,11 +295,12 @@
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"___\n",
"Copyright (c) 2020, NVIDIA CORPORATION.\n",
"Copyright (c) 2020-2023, NVIDIA CORPORATION.\n",
"\n",
"Licensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0\n",
"\n",
Expand All @@ -290,9 +311,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "cugraph_dev",
"display_name": "cugraph_0411",
"language": "python",
"name": "cugraph_dev"
"name": "python3"
},
"language_info": {
"codemirror_mode": {
Expand All @@ -304,7 +325,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
"version": "3.10.10"
}
},
"nbformat": 4,
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