CODA: Rewriting Transformer Blocks as GEMM-Epilogue Programs

Published
Source
arXiv
Paper number
194
Field
Machine Learning
arXiv ID
2605.19269

Key points

  • It maintains local state for operations such as the online log-sum-exp used in cross-entropy loss.
  • It recovers a substantial portion of GPU time that would otherwise be lost to data movement.
  • It provides a structured DSL that simplifies writing high-performance kernels.

Paper links

External research summaries. These are not HDATF publications or measured product results.

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