Results for “gpu-cluster”

Submits TAO container jobs as single-pod Kubernetes Jobs with NVIDIA GPU scheduling on EKS, GKE, AKS, or on-prem clusters.

Enables fast similarity search and clustering of dense vectors using FAISS, supporting billions of vectors, GPU acceleration, and various index types.

Enables fast similarity search and clustering of dense vectors using FAISS, covering index types, GPU acceleration, and integrations with LangChain and LlamaIndex.

Evaluates NVIDIA Cosmos Policy on LIBERO and RoboCasa simulation environments. Use when setting up cosmos-policy for robot manipulation evaluation, running headless GPU evaluations with EGL rendering, or profiling inference latency on cluster or local GPU machines.

Launch distributed Megatron-LM training jobs on a SLURM cluster with a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDA_DEVICE_MAX_CONNECTIONS rules, container conventions, monitoring, and per-rank failure diagnosis.

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.

Plans, executes, and validates Google Kubernetes Engine (GKE) cluster upgrades and maintenance operations for both Standard and Autopilot clusters, producing upgrade plans, checklists, and runbooks with gcloud commands.

Runs batch processing and high-performance computing (HPC) workloads on Google Kubernetes Engine (GKE), including job queues, parallel processing, and MPI workloads.

Routes to specialized GKE sub-skills for cluster management, networking, security, scaling, and more on Google Kubernetes Engine.

Manages Google Kubernetes Engine clusters via gcloud CLI, covering cluster discovery, node pool management, workload analysis, autopilot configuration, and upgrade planning.

GPU-safe parallel processing patterns for KINTSUGI to prevent OOM crashes and ensure Jupyter-compatible progress output

Configure gke cluster config operations. Auto-activating skill for GCP Skills. Triggers on: gke cluster config, gke cluster config Part of the GCP Skills skill category. Use when configuring systems or services. Trigger with phrases like "gke cluster config", "gke config", "gke".

**Trigger**: Use when working with GKE Storage — Google Kubernetes Engine configuration and management.

Set up and manage Google Kubernetes Engine clusters, node pools, workloads, networking, and storage with Autopilot defaults.

Deploys and optimizes AI/ML inference workloads on GKE, using GPUs, TPUs, and model servers.

Provides guidance on enabling and optimizing GKE Cluster Autoscaler, including Node Auto Provisioning, troubleshooting scale-up/down issues, and best practices for capacity management.

Configures, optimizes, and troubleshoots GKE ComputeClasses for Spot VMs with on-demand fallback, GPU/TPU targeting, machine family selection, and zone colocation.

Hardens Google Kubernetes Engine (GKE) clusters with Workload Identity, Secret Manager, RBAC, Binary Authorization, Network Policies, and Pod Security Standards.

Configures GKE storage including PVCs, PersistentVolumes, Filestore, and GCS FUSE with best practices for production workloads.

Accelerate pandas workflows with GPU DataFrames using cuDF and dask-cuDF for ETL, joins, groupby, and large-scale data processing.

Reduces peak GPU memory in Megatron Bridge training by applying expandable segments, parallelism resizing, activation recompute, and CPU offloading constraints.

Launch, monitor, stop, and debug NeMo-RL recipes on a Kubernetes cluster using the nrl-k8s CLI, supporting ephemeral and long-lived RayCluster modes.

Plans and configures multi-tenancy on GKE, covering namespace isolation, RBAC planning, resource quotas, LimitRanges, network isolation, and cost allocation.

Protects stateful GKE workloads by configuring backup plans, restore workflows, and disaster recovery using Backup for GKE.

Plans, configures, and manages GKE networking including private clusters, VPC-native configurations, Gateway API, DNS, ingress/egress, Dataplane V2, and IP planning.

Configures GKE workload reliability with PodDisruptionBudgets, health probes, topology spread constraints, and graceful shutdown patterns.

GPU-accelerated correlation matrix computation with persistent SQLite caching to eliminate bottleneck at correlation calculation during symbol selection

Configure memorystore config operations. Auto-activating skill for GCP Skills. Triggers on: memorystore config, memorystore config Part of the GCP Skills skill category. Use when configuring systems or services. Trigger with phrases like "memorystore config", "memorystore config", "memorystore".

Manages Google AlloyDB for PostgreSQL clusters and instances via gcloud CLI, covering discovery, instance analysis, query insights, backup configuration, and maintenance windows.

GPU / MLOps person pack for Content Factory. Use when the user says person gpu, @person-gpu, GPU person, RunPod person, or MLOps person. Auto-loads gpu-infrastructure-engineer and mlops-engineer plus gpu-optimization, cf-llm-model-usage, cost-optimization.