Published Mar 1 – 5, 2025 | Version v2
Software Open

ATTNChecker: Highly-Optimized Fault Tolerant Attention for Large Language Model Training

Authors/Creators

  • 1. ROR icon University of Alabama at Birmingham
  • 2. ROR icon Pacific Northwest National Laboratory
  • 3. ROR icon William & Mary

Description

Artifacts for the "ATTNChecker: Highly-Optimized Fault Tolerant Attention for Large Language Model Training" accepted at PPoPP 2025.

Files

ATTNChecker.zip

Files (330.3 MB)

Name Size
md5:d958a68356698511ee2cfe1c990841fb
330.3 MB Preview Download