The race to build a distributed GPU runtime
For a decade, GPUs have delivered breathtaking data processing speedups. However, data is growing far beyond the capacity of a single GPU server. When your work drifts beyond GPU local memory or VRAM (e.g., HBM and GDDR), hidden costs of inefficiencies show up: spilling to host, shuffling over networks, and idling accelerators. Before jumping straight into the latest distributed computing effort underway at NVIDIA and AMD, let’s quickly level set on what distributed computing is, how it works, a