Autoscaling Autoresearch: Give your agents elastic GPUs on Modal | Modal Blog

This post details the application of Modal's elastic GPU provisioning and autoscaling capabilities to AI research agents, specifically in the context of OpenAI's Parameter Golf challenge. It demonstrates how agents can dynamically acquire and release compute resources (from single GPUs to multi-GPU clusters) based on the needs of different research stages (validation, exploration, validation at scale, debugging, and optimization). The post highlights the speedup and efficiency gains achieved by using Modal's serverless runtime, which allows for rapid scaling from one GPU to dozens or hundreds as a parameter change, and automatic scaling to zero when work is completed. It also showcases the use of Modal Skills to guide agents in provisioning GPUs, running experiments, and managing storage.