~/talk

PipeThreader: Software-Defined Pipelining for Efficient DNN Execution

name:Yu Cheng
links:none on file
name:Lei Wang
links:none on file
links:none on file
links:none on file
links:none on file
links:none on file
name:Yang Wang
links:none on file
name:Fan Yang
linkedin:fyang26
name:Mao Yang
links:none on file
name:Zhi Yang
links:none on file
slides:none on file

A compiler shifts pipeline scheduling from hardware to software, exposing tile-level tasks and heterogeneous units to generate efficient DNN pipelines. It defines sTask-graph nodes mapped to SEU/EU hardware, and new primitives (append/wait/propagate) to place and order work. PipeThreader automatically rediscovers FlashAttention-style pipelining, achieves up to 2.18× speedup on H100 versus handcrafted kernels, finds faster schedules for Mamba2 and Llama3, and targets AMD Mi300X; code is open-sourced.

AI-written summary · about

  1. 0:00PipeThreader introduction
  2. 3:10Handcrafted DNN kernel challenges
  3. 7:24Software-defined pipelining approach
  4. 10:17PEPThreader abstractions
  5. 12:46Automated scheduling
  6. 13:26Performance gains
  7. 14:31Conclusion
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