Commits
pengwa authored and GitHub committed a3e7da60e7a
Trade subgraph recompute for memory (#12852) **Description**: Subgraph-level recompute This PR adds an optional capability trading additional re-computation for better memory efficiency. Specifically, a pre-defined operator list used to iterate the Graph to find some subgraphs for recompute, to reduce some stashed activations whose lifetime across forward and backward pass. When training with ORTModule, by default, the graph transformer will scan the execution graph to find all eligible subgraph to recompute, along with sizes that can save. An example looks like below. If we want to enable some of them to recompute, we can define env variable this way: `export ORTMODULE_ENABLE_MEMORY_ALLEVIATION="Mul+FusedMatMul+Cast+Unsqueeze+Unsqueeze+Cast+Sub+Mul+Add+BiasSoftmaxDropout+Cast+:1:-1,BiasGelu+:1:-1,BitmaskDropout+Cast+:1:-1,FusedMatMul+:1:-1,Cast+:1:-1,Mul+Add+:1:-1,Mul+Sub+:1:-1"` ``` [1,0]<stderr>:2,022-10-12 14:47:39.302,954,530 [W:onnxruntime:, memory_alleviation.cc:595 PrintSummary] [1,0]<stderr>:MemoryAlleviation Summary: [1,0]<stderr>: User config: [1,0]<stderr>: Mul+FusedMatMul+Cast+Unsqueeze+Unsqueeze+Cast+Sub+Mul+Add+BiasSoftmaxDropout+Cast+:1,BiasGelu+:1,BitmaskDropout+Cast+:1,FusedMatMul+:1,Cast+:1,Mul+Add+:1,Mul+Sub+:1 [1,0]<stderr>: ================================= [1,0]<stderr>: Subgraph: BitmaskDropout+ [1,0]<stderr>: AlleviationType: Disabled [1,0]<stderr>: Patterns: [1,0]<stderr>: PatternShape:input_ids_dim0 x 1,024 x Frequency:1 [1,0]<stderr>: -------------------------------- [1,0]<stderr>: Subgraph: BiasGelu+ [1,0]<stderr>: AlleviationType: Recompute [1,0]<stderr>: Patterns: [1,0]<stderr>: PatternShape:input_ids_dim0 x input_ids_dim1 x 4,096 x Frequency:24 [1,0]<stderr>: -------------------------------- [1,0]<stderr>: Subgraph: Reshape[1,0]<stderr>:+ [1,0]<stderr>: AlleviationType: Disabled [1,0]<stderr>: Patterns: [1,0]<stderr>: PatternShape:labels_dim0 x Frequency:1 [1,0]<stderr>: -------------------------------- [1,0]<stderr>: Subgraph: Unsqueeze+Unsqueeze+Cast+Sub+Mul+Mul+FusedMatMul+Cast+Add+BiasSoftmaxDropout+Cast+ [1,0]<stderr>: AlleviationType: Disabled [1,0]<stderr>: Patterns: [1,0]<stderr>: PatternShape:input_ids_dim0 x 16 x input_ids_dim1 x input_ids_dim1 x Frequency:23 [1,0]<stderr>: -------------------------------- [1,0]<stderr>: Subgraph: Mul+FusedMatMul+Cast+Unsqueeze+Unsqueeze+Cast+Sub+Mul+Add+BiasSoftmaxDropout+Cast+ [1,0]<stderr>: AlleviationType: Recompute [1,0]<stderr>: Patterns: [1,0]<stderr>: PatternShape:input_ids_dim0 x 16 x input_ids_dim1 x input_ids_dim1 x Frequency:1 [1,0]<stderr>: -------------------------------- [1,0]<stderr>: Subgraph: Mul+Add+ [1,0]<stderr>: AlleviationType: Recompute [1,0]<stderr>: Patterns: [1,0]<stderr>: PatternShape:input_ids_dim0 x 16 x input_ids_dim1 x 1 x Frequency:24 [1,0]<stderr>: -------------------------------- [1,0]<stderr>: Subgraph: FusedMatMul+Cast+Add+Reshape+Cast+ [1,0]<stderr>: AlleviationType: Disabled [1,0]<stderr>: Patterns: [1,0]<stderr>: PatternShape:input_ids_dim0 x 16 x input_ids_dim1 x 2 x 4 x Frequency:24 [1,0]<stderr>: -------------------------------- [1,0]<stderr>: Subgraph: Mul+Sub+ [1,0]<stderr>: AlleviationType: Recompute [1,0]<stderr>: Patterns: [1,0]<stderr>: PatternShape:input_ids_dim0 x 16 x input_ids_dim1 x 1 x Frequency:24 [1,0]<stderr>: -------------------------------- [1,0]<stderr>: Subgraph: Cast+ [1,0]<stderr>: AlleviationType: Recompute [1,0]<stderr>: Patterns: [1,0]<stderr>: PatternShape:1,024 x 1,024 x Frequency:97 [1,0]<stderr>: PatternShape:3 x 1,024 x Frequency:1 [1,0]<stderr>: PatternShape:8 x 64 x Frequency:24 [1,0]<stderr>: PatternShape:1,024 x 4,096 x Frequency:24 [1,0]<stderr>: PatternShape:4,096 x Frequency:24 [1,0]<stderr>: PatternShape:4,096 x 1,024 x Frequency:24 [1,0]<stderr>: -------------------------------- [1,0]<stderr>: Subgraph: FusedMatMul+ [1,0]<stderr>: AlleviationType: Recompute [1,0]<stderr>: Patterns: [1,0]<stderr>: PatternShape:input_ids_dim0 x input_ids_dim1 x 4,096 x Frequency:24 [1,0]<stderr>: -------------------------------- [1,0]<stderr>: ================================= ``` "Type config:" whether recompute is enabled by users. 0 - disable, 1- enable. "Subgraph" means what kind of subgraph will be recomputed, in this case, it is a single node "Gelu", and it will be "Recompute". "Shape && Frequency" means, for this recompute, one tensor of size (batch size, 500) will be saved because it will be recomputed. **Baseline** On a 1P model (DEBERTA V2), sequence length 256, training with 16 A100 GPUs. With latest main branch, we can run batch size 16, and the maximum batch size < 32. So 16 is usually chosen by data scientists. 65% of 40GB memory is used during training. The SamplesPerSec=479.2543353561354.  **With this PR** Gelu is recomputed for saving memory peak, batch size 32 can be run. The 97% of 40GB A100 is used, the SamplesPerSec=562.041593991271 (**1.17X** of baseline).  **Motivation and Context** - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here.