Maestro accelerates compound LLM training via section graphs for per-component configuration and wavefront scheduling for dynamic execution, reducing GPU consumption by ~40% in real deployments.
Qwen3-VL-Team
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.DC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Accelerating Compound LLM Training Workloads with Maestro
Maestro accelerates compound LLM training via section graphs for per-component configuration and wavefront scheduling for dynamic execution, reducing GPU consumption by ~40% in real deployments.