WoolyAI Acceleration Service
GPU service with GPU core and memory resources used billing
About
WoolyAI is a GPU Hypervisor for ML Platforms, targeting MLOps and ML Infra teams running PyTorch workloads on NVIDIA and AMD GPUs. It enables notebooks, dev/test jobs, and small training runs to execute on CPU-only nodes while their GPU kernels are routed to a shared remote GPU pool. This approach, featuring kernel-level scheduling, aims to increase GPU utilization by up to 3x, reduce queue times, and delay new GPU purchases without requiring any code changes to existing ML containers or MLOps stacks (Kubernetes, Ray, Airflow, Slurm). Key use cases include interactive development, hyperparameter optimization, multi-model pipelines, inference with SLAs, pre-production canary training, and integrating multi-vendor GPU fleets.
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