Google researchers solve hierarchical resource allocation with market equilibrium
New algorithm allocates TPUs/GPUs across org trees efficiently using a two-step process.
Deep Dive
Google researchers (Yuan Deng, Giannis Fikioris, et al.) propose a market equilibrium approach to allocate multiple heterogeneous resources like TPUs and GPUs across organizational hierarchies (e.g., business units, departments, teams). They prove a feasible solution always exists and provide an algorithm that first solves “harmonic” instances, then approximates general cases. Tested on real Google compute allocation data, the method handles resource conversion between certain pairs.
Key Points
- Uses market equilibrium framework to allocate multiple heterogeneous resources (e.g., TPUs, GPUs) across hierarchical org structures.
- Proves existence of feasible solution and provides a two-step algorithm: solving 'harmonic' instances then approximating general cases.
- Tested on real Google compute resource allocation dataset, showing efficient convergence and practical applicability.
Why It Matters
Automates fair, efficient resource allocation across org hierarchies—reducing waste and political friction in large tech companies and institutions.