Autopoiesis uses LLM-driven program synthesis to evolve serving policies online during deployment, delivering up to 53% and average 34% gains over prior LLM serving systems under runtime dynamics.
Kernelevolve: Scaling agentic kernel coding for heterogeneous ai accelerators at meta
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
DITRON introduces a hierarchical multi-level tiling compiler for distributed tensor programs that matches or exceeds expert CUDA libraries with 6-30% speedups and has been deployed to improve training MFU by over 10% while saving hundreds of thousands of GPU hours monthly.
citing papers explorer
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Autopoiesis: A Self-Evolving System Paradigm for LLM Serving Under Runtime Dynamics
Autopoiesis uses LLM-driven program synthesis to evolve serving policies online during deployment, delivering up to 53% and average 34% gains over prior LLM serving systems under runtime dynamics.
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DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs
DITRON introduces a hierarchical multi-level tiling compiler for distributed tensor programs that matches or exceeds expert CUDA libraries with 6-30% speedups and has been deployed to improve training MFU by over 10% while saving hundreds of thousands of GPU hours monthly.