ko3n1g
released this
24 Oct 10:30
·
10 commits
to core_r0.9.0
since this release
- Uneven pipeline parallelism
- Enable pipeline parallelism where first and last ranks have fewer transformer layers than the intermediate ranks
- Per layer CUDAGraph support for GPT training with Transformer Engine modules
- Enable different TP sizes for the vision encoder
- Enable pipeline parallelism for T5 & Llava models
- Support multi-tile multi-image input in Llava models
- MoE
- FP8 support
- Runtime upcycling support
- Dispatcher implementation optimizations
- Shared expert support with overlapping optimizations
- Qwen Model support
- Known Issues
- When using sequence parallel, during the transformer block forward pass, dropout is not using the appropriate rng context.