The Cloud is Just Someone Else's Computer
We are living through a Compute Famine. NVIDIA H100s are the new gold bullion. Cloud providers are rationing GPUs like water in a desert. To run a decent LLM, you are expected to pay a monthly rent that rivals a car payment.
But look around your room. You have a gaming PC. You have an old MacBook Pro from 2020. You have a desktop gathering dust in the closet. Individually, they are weak. Together? They are a Cluster.
Enter VGD
VGD (Virtual GPU Daemon) is a protocol I designed to smash the walls between your devices. It allows you to pool the VRAM of every device in your house into a single, unified inference engine.
- The Gaming Rig (RTX 4090): Handles the heavy matrix multiplication.
- The MacBook (M1 Max): Handles the pre-fill and prompt encoding.
- The Old Laptop: Handles the routing and API serving.
The Technical Challenge: Latency
Distributed inference is notoriously hard because of The Speed of Light. The interconnects in a data center run at 800 Gbps. Your home Wifi runs at maybe 500 Mbps. If you simply split a model in half, the time spent sending data between devices outweighs the time saved by computing in parallel.
VGD solves this with Optimized Tensor Splitting. We don't just split the model anywhere. We analyze the neural network graph to find "Cut Points"—layers where the data transfer volume is minimal.
We also implement Pipeline Parallelism. While Node B is computing Layer 13, Node A is already computing Layer 1 for the next token. The cluster never stops breathing.
Digital Sovereignty
This project is about more than just saving money. It is about Independence.
If you rely on OpenAI or AWS, you can be de-platformed. Your API key can be revoked. Your rates can be hiked. But if you own the metal, and you own the software that binds the metal, you are untouchable.
VGD turns your home into a Data Center. It turns your consumer electronics into a supercomputer. Stop renting. Start clustering.