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High-Performance Computing & Machine Learning

# Heterogeneous GPU Cluster Scheduling

#### The challenge

Most cluster tools only support one GPU brand, leaving AMD, Apple Silicon, and Intel hardware idle while teams wait for expensive cloud instances.

#### Our approach

We deploy a single-binary gossip scheduler that discovers and balances tasks across mixed NVIDIA CUDA, AMD ROCm, Apple Metal, and Intel Arc hardware without a central master node.

#### Outcomes

40% to 60% reduction in cluster idle time across mixed hardware fleets

Single-binary deployment under 25 MB with zero runtime dependencies

Resilient peer-to-peer cluster coordination with zero single points of failure

Built on

Distributed GPU Compute

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Source: https://kushawaha.com/solutions/distributed-gpu-management
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