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Sampling Performance Testing #3584
Sampling Performance Testing #3584
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Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
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Requested minor changes, mostly looks good.
the number of training epochs here. These are followed by the `REPLICATION_FACTOR` argument, which | ||
can be used to create replications of the dataset for scale testing purposes. | ||
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The final two arguments are `FRAMEWORK` which can be either "cuGraphPyG" or "PyG", and `GPUS_PER_NODE` |
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I assume we shall include "cuGraphDGL" here too.
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Yes
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in the next PR
benchmarks/cugraph/standalone/bulk_sampling/bench_cugraph_training.py
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SCRIPTS_DIR=$4 | ||
NUM_EPOCHS=$5 | ||
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SAMPLES_DIR=/samples |
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Assuming we are mounting this to the most performant path.
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Yes, it is up to us to set LOGS_DIR
, SAMPLES_DIR
, and DATASETS_DIR
in run_train_job.sh
correctly. In the srun
command, those are mounted to /logs
, /samples
, and /datasets
in the container that this script runs in.
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LGTM
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LGTM overall. I don't feel too strongly, but I noticed several places in the shell scripts that assume things about the file system (/datasets
, etc.). We usually put those scripts in another repo (the repo containing our machine-specific nightly scripts, etc.) and not the open cugraph repo.
The |
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Not sure why we need to update the copyright on a file that wasn't otherwise updated... but OK.
/merge |
…formance Improvements (#4081) Large-scale cuGraph-DGL performance testing scripts. Also changes the DGL and PyG scripts to evaluate on all ranks and reuse the test samples, and adds support for benchmarking cuGraph-DGL/cuGraph-PyG with WholeGraph. Updates `cuGraph.gnn.FeatureStore` and `cuGraph-PyG` for increased performance: * Supporting passing in a WG embedding directly to cugraph.gnn.FeatureStore * Simplifying how cuGraph-PyG handles filtering and using a cache to prevent repeatedly copying data between the device and host * Fix bug in cugraph.gnn.FeatureStore where indexing with a gpu tensor would raise an exception, especially with WG * Add a function to cugraph.gnn.FeatureStore to check where data is stored, which is used by cuGraph-PyG to prevent unnecessary d2h and h2d copies Merge after #3584 Authors: - Alex Barghi (https://github.com/alexbarghi-nv) - Seunghwa Kang (https://github.com/seunghwak) - Vibhu Jawa (https://github.com/VibhuJawa) - Brad Rees (https://github.com/BradReesWork) Approvers: - Vibhu Jawa (https://github.com/VibhuJawa) - Don Acosta (https://github.com/acostadon) - Brad Rees (https://github.com/BradReesWork) - Naim (https://github.com/naimnv) - Joseph Nke (https://github.com/jnke2016) URL: #4081
Adds performance benchmarking scripts for testing MNMG cuGraph GNN workflows.
This branch is the head branch for the cuGraph benchmarking effort. All work supporting the benchmarks should be merged into this branch. It will be merged into branch-24.02 once all features are ready.
Includes patches to cuGraph-PyG required for the latest DLFW container.
To-Do:
Add WholeGraph training portionDeferred to future PR (see Add WholeGraph Support alexbarghi-nv/cugraph#6)Add WholeGraph generatorsIncluded in aboveSupport DGLDeferred to future PRUse appropriate docker containersDeferred, waiting on DLFW releaseCloses #3839