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Found 4 Skills
Run Python code in the cloud with serverless containers, GPUs, and autoscaling. Use when deploying ML models, running batch processing jobs, scheduling compute-intensive tasks, or serving APIs that require GPU acceleration or dynamic scaling.
Executes Python scripts, tests, or benchmarks on a provisioned remote cluster (GPU or TPU) using SkyPilot. Use this skill when the user asks to run code on GPU, TPU, or any "remote" cluster.
DigitalOcean compute services covering Droplets, App Platform, Functions, Kubernetes (DOKS), GPU Droplets, and Bare Metal GPUs. Use when selecting or provisioning compute for applications, containers, or serverless workloads.
CUDA/GPU computing guardrails, patterns, and best practices for AI-assisted development. Use when working with CUDA files (.cu, .cuh), or when the user mentions CUDA/GPU programming. Provides kernel design patterns, memory hierarchy guidelines, and occupancy optimization specific to this project's coding standards.