1 مستودع
Awesome GitHub RepositoriesAccelerator Placement Mapping
Strategies for mapping compute workers to specific GPUs and nodes to optimize hardware utilization.
Distinct from Worker Node Management: Distinct from Worker Node Management: specifically focuses on the mapping and placement logic for GPU accelerators.
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Awesome Accelerator Placement Mapping GitHub Repositories
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- rlinf/rlinf
RLinf/RLinf
2,502عرض على GitHubRLinf is a distributed reinforcement learning orchestrator and embodied AI training framework. It provides the infrastructure to train vision-language-action models and robotic policies using a combination of reinforcement learning and supervised fine-tuning. The system is designed for scaling workloads across GPU clusters, managing the placement of actors, rollout workers, and environment components. It features a specialized robotics data collection pipeline for gathering teleoperated demonstrations and simulation trajectories into standardized replay buffers, alongside a hardware interface
Maps compute workers to specific nodes and GPUs using various execution modes to optimize resource utilization.
Pythonagentic-aiembodied-aireinforcement-learning
