The Mueller Minute
Zach MuellerI discuss common problems I've seen when it comes to distributed training, provide general tips, and talk about cool things I've found that week.
| Platform |  | Pricing | Only free issues | Publishes | Daily |
|---|---|---|---|---|---|
| Issues | 40 | Subscribers | Read | muellerminute.substack.com |
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Latest Issues
Recent posts by this newsletter. Browse the email archive.
Distributed Operations: The Reduce Op
Ring-reduce (torch’s default reduce operation) is a bandwidth-friendly way to add a large tensor that is split across several GPUs or machines.
torch.distributed.gather
There are a few reasons why it’s critical to grab tensors from other GPUs and centralize them on a singular one.
The send/recv pattern
send/recv is a core concept behind distributed PyTorch operations. The general idea revolves around how do you send a tensor from device A to device B.
Batch Sampler Sharding
Unlike iterable dataset sharding, where each worker directly pulls raw data in its `__iter__`, batch sampler sharding first generates indices that specify which items to fetch. These indices are grouped into batches, which are then collated...
Authors
The writers behind this newsletter.
I've been in the field for almost a decade. I was a fast.ai community leader, and quickly learned how training pipelines are built and operated. Then I moved to Hugging Face, where work on the accelerate project and manage the Trainer.
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