add async grad allreduce and chunk optimization #4084
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Signed-off-by: ericharper <complex451@gmail.com>
Signed-off-by: ericharper <complex451@gmail.com>
Signed-off-by: ericharper <complex451@gmail.com>
Signed-off-by: ericharper <complex451@gmail.com>
Signed-off-by: ericharper <complex451@gmail.com>
Signed-off-by: ericharper <complex451@gmail.com>
ericharper
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May 12, 2022
ericharper
reviewed
May 12, 2022
nemo/collections/nlp/models/language_modeling/megatron_lm_encoder_decoder_model.py
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* O2 runs but O1 does not Signed-off-by: ericharper <complex451@gmail.com> * disable async for O1 Signed-off-by: ericharper <complex451@gmail.com> * typo Signed-off-by: ericharper <complex451@gmail.com> * update async flag in configure_optimizers Signed-off-by: ericharper <complex451@gmail.com> * typo Signed-off-by: ericharper <complex451@gmail.com> * revert Signed-off-by: ericharper <complex451@gmail.com> * update _require if using async Signed-off-by: ericharper <complex451@gmail.com> * clean comments Signed-off-by: ericharper <complex451@gmail.com> * always all_reduce Signed-off-by: ericharper <complex451@gmail.com> * add async grad allreduce and chunk optimization to T5 * push reformatted files after style check * set chunk size as 0 while async grad allreduce is off * more experiments show that 125MB is a better default chunk size for most cases * add grad_allreduce_chunk_size_mb for GPT-3 * at the end of each training step, wait until all async grad allreduce works are done * replace individual allreduce work.wait() with a single dGPU evice synchroonization * record the status of each allreduce work seems too much for perf * add more comments * push a reformatted file Co-authored-by: ericharper <complex451@gmail.com>
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What does this PR do ?
Add async grad allreduce, work for T5 and GPT-3.
Increase allreduce granularity by grouping params into multiple chunks. Every time a chunk is finished, we start an allreduce for the chunk (sending large chunk of data can better utilize bandwidth).
Current implementation works for BF16 O2 and PP=1.
Collection: [Note which collection this PR will affect]
Changelog
Usage
add a knob "grad_allreduce_chunk_size_mb", default config is 125MB. You can change it for different models and/or model sizes.
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