Invention Grant
- Patent Title: Selective batching for inference system for transformer-based generation tasks
-
Application No.: US17948139Application Date: 2022-09-19
-
Publication No.: US11922282B2Publication Date: 2024-03-05
- Inventor: Gyeongin Yu , Geon-Woo Kim , Joo Seong Jeong , Soojeong Kim , Byung-Gon Chun
- Applicant: FriendliAI Inc.
- Applicant Address: KR Seoul
- Assignee: FRIENDLIAI INC.
- Current Assignee: FRIENDLIAI INC.
- Current Assignee Address: KR Seoul
- Agency: FENWICK & WEST LLP
- Main IPC: G06F16/2455
- IPC: G06F16/2455 ; G06F40/284 ; G06N20/10

Abstract:
An inference system applies a machine-learning transformer model to a batch of requests with variable input length or variable target length or variable internal sate length by selectively batching a subset of operations in the transformer model but processing requests in the batch individually for a subset of operations in the transformer model. In one embodiment, the operation to be processed individually is an attention operation of an encoder or a decoder of the transformer model. By selective batching, the inference system can allow batching operations to be performed for a batch of requests with variable input or target length or internal state length to utilize the parallel computation capabilities of hardware accelerators while preventing unnecessary computations that occur for workarounds that restrain the data of a batch of requests to a same length.
Public/Granted literature
- US20230177399A1 SELECTIVE BATCHING FOR INFERENCE SYSTEM FOR TRANSFORMER-BASED GENERATION TASKS Public/Granted day:2023-06-08
Information query