Is your feature request related to a problem? Please describe.
Activation prefetch features to enlarge batch size on middle-size(100B~1T) of models
- From DeepSpeedExamples repo, GPU throughput with Activation checkpoint in CPU matters.
- On A100 server pods, Activation checkpoint in CPU perform worse because of synchronization (HtoD memcpy or all-gather when partitioned activation).
- For Tensor Parallelism, it would be better to save activation checkpoint in partitioned tensor.
Describe the solution you'd like
Activation prefetch during backward re-computation based on configuration
Furthermore, to increase batch size in tensor parallelism, asynchronous all-gather prefetched partitioned activation is needed.
Describe alternatives you've considered
For large scale GPU pods more than 128 GPU would not be problem.
It would be appreciated if we have candidates of GPU cluster size based on model configuration (10B, 50B, 100B, 1T).
Is your feature request related to a problem? Please describe.
Activation prefetch features to enlarge batch size on middle-size(100B~1T) of models
Describe the solution you'd like
Activation prefetch during backward re-computation based on configuration
Furthermore, to increase batch size in tensor parallelism, asynchronous all-gather prefetched partitioned activation is needed.
Describe alternatives you've considered
For large scale GPU pods more than 128 GPU would not be problem.
It would be appreciated if we have candidates of GPU cluster size based on model configuration (10B, 50B, 100B, 1T).