Results for “multi-gpu”
9 skills
orchestra-research lambda-labs-gpu-cloud
Manage and use Lambda Labs GPU cloud instances for ML training and inference with SSH access, persistent filesystems, and multi-node clusters.
10.4k · bundle
nvidia tao-run-on-lepton
Submit TAO jobs to Lepton managed GPU compute on DGX Cloud, with run/status/cancel interface and multi-node distributed training support.
2.2k · bundle
nvidia tao-setup-nvidia-gpu-host
Checks and installs NVIDIA driver, CUDA Toolkit, and NVIDIA Container Toolkit for GPU-accelerated Docker and Kubernetes hosts. Supports multiple Linux distributions with automated install and read-only check modes.
2.2k · bundle
More results
lord1egypt modal-serverless-gpu
Run ML workloads on Modal's serverless GPU cloud: deploy models as auto-scaling APIs, run batch jobs, and schedule tasks with pay-per-second GPU pricing.
2
google gke-inference
Deploys and optimizes AI/ML inference workloads on GKE, using GPUs, TPUs, and model servers.
14.4k
orchestra-research modal-serverless-gpu
Run ML workloads on Modal's serverless GPU cloud platform with auto-scaling, pay-per-second pricing, and Python-native infrastructure.
10.4k · bundle
orchestra-research skypilot-multi-cloud-orchestration
Run ML training and batch jobs across multiple clouds with automatic cost optimization, spot instance recovery, and unified orchestration.
10.4k · bundle
nvidia tao-run-platform
Submit and monitor GPU training jobs on Brev, SLURM, Docker, or Kubernetes using the TAO Execution SDK, with job handles, S3 I/O wrapping, and multi-node distributed training.
2.2k · bundle
nvidia dynamo-interconnect-check
Validates that a Dynamo deployment's NIXL/UCX/NCCL interconnect is ready for disaggregated serving over RDMA/NVLink. Use after deploying a disagg or multi-node recipe to confirm KV transport is correct, or use troubleshoot for already-failed pods.
2.2k · bundle