Skill UI

This guide details how to set up and execute large-scale, distributed GPU training jobs on the CoreWeave platform. It covers both single-node multi-GPU setups and multi-node training utilizing PyTorch DDP and Kubernetes resources (A100/H100). This workflow is ideal for fine-tuning large language models (LLMs) or running complex deep learning models that require high-performance, shared-storage compute clusters.

This guide demonstrates how to deploy GPU workloads on the CoreWeave platform using Kubernetes (kubectl). It covers deploying vLLM inference services for large language model (LLM) testing and running batch CUDA jobs for benchmarking. This is ideal for users running their first GPU workloads, testing inference pipelines, or verifying cluster access on bare-metal GPU nodes (A100, H100).

Rowan is a comprehensive, cloud-native platform accessible via a Python API for molecular simulation and medicinal chemistry. It streamlines complex drug discovery workflows, including pKa prediction, conformer searching, molecular docking (single and analogue series), protein-ligand cofolding, and molecular dynamics. It eliminates the need for local HPC/GPU infrastructure, making programmatic batch screening and multi-step chemistry pipelines highly scalable and reliable.