Select optimal EC2 GPU instance types for Physical AI RL training based on VRAM, interconnect, and cost requirements
원문 언어: 영어
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SkillsMP는 aws-samples/sample-rlinf-on-eks에서 19개의 skill을 수집했습니다. skill을 열어 소스와 세부 정보를 확인하세요.
수집된 skill 19개 중 19개를 표시합니다.
Select optimal EC2 GPU instance types for Physical AI RL training based on VRAM, interconnect, and cost requirements
원문 언어: 영어
Leverage Kubernetes-native features for GPU training including GPU Operator, topology scheduling, and priority classes
원문 언어: 영어
Deploy and manage Physical AI RL training jobs on EKS including CodeBuild CI, GitOps, and experiment management
원문 언어: 영어
Provision an Amazon EKS cluster with GPU node groups, EFA networking, and OIDC for Physical AI RL training workloads
원문 언어: 영어
RLinf: Download, preprocess, and stage datasets and model weights for RLinf training on EKS
원문 언어: 영어
Validate the Physical AI RL training stack end-to-end from infrastructure smoke tests to training step verification
원문 언어: 영어
Construct Kubernetes Jobs, StatefulSets, and Services for GPU-accelerated RL training workloads on EKS
원문 언어: 영어
RLinf: Validate RLinf training examples end-to-end from container tests to single-step training
원문 언어: 영어
RLinf: Integrate Ray, veRL, vLLM, and KubeRay into the RLinf training stack on EKS
원문 언어: 영어
Configure AMI selection and GPU node bootstrap including NVIDIA drivers, EFA, and Lustre client
원문 언어: 영어
Build container images for Physical AI RL training including dependency conflict management, patching, and CodeBuild CI
원문 언어: 영어
Monitor GPU utilization, training progress, and costs using DCGM, Prometheus, Grafana, MLflow, and CloudWatch
원문 언어: 영어
Configure Elastic Fabric Adapter networking for high-performance NCCL allreduce in multi-node GPU training
원문 언어: 영어
RLinf: Evaluate training quality and infrastructure performance using LIBERO, RoboTwin, and throughput benchmarks
원문 언어: 영어
RLinf: Adapt RLinf training scripts for distributed execution on Amazon EKS with veRL, Ray, and FSDP
원문 언어: 영어
Deploy Amazon FSx for Lustre as shared high-performance storage for datasets, checkpoints, and model weights
원문 언어: 영어
Mount S3 buckets as POSIX-like filesystems in training pods via the Mountpoint for Amazon S3 CSI driver
원문 언어: 영어
Use Amazon S3 Connector for PyTorch to read datasets and save checkpoints directly to S3
원문 언어: 영어
Mount S3 buckets as native NFS file systems on EKS via Amazon S3 Files for shared, low-latency file access
원문 언어: 영어