[All five systems](https://kushawaha.com/capabilities)

High-Performance Systems

# Heterogeneous GPU & Distributed Task Scheduling

Single-binary cluster orchestration across mixed hardware environments.

Our scheduling engines run distributed compute jobs across mixed hardware fleets. By discovering and coordinating NVIDIA CUDA, AMD ROCm, Apple Metal, and Intel Arc GPUs over an encrypted peer-to-peer gossip protocol, fleets operate without a single centralized master node.

**Business value**

Lowers compute spending by 40% to 60% by using all available GPU hardware across on-premise servers and cloud instances.

#### Architecture & Implementation

- Peer-to-peer gossip discovery with encrypted node messaging and bidirectional gRPC streams
- Native hardware detection reading driver counters directly without third-party agent software
- Single-binary Go and Rust architecture with zero CGO and zero external runtime libraries
- Cross-compiled execution supporting Linux, macOS, and Windows across x86_64 and arm64

#### Critical Problems Solved

- Eliminates dependence on a single GPU vendor, utilizing idle AMD and Apple Silicon hardware
- Removes single points of failure by replacing fragile centralized coordinators with a gossip mesh
- Simplifies cluster administration to a single binary deployment that requires no setup scripts

Specifications

Supported Hardware NVIDIA (CUDA), AMD (ROCm/sysfs), Apple (Metal), Intel (Arc/xpu-smi)

Cluster Protocol Encrypted gossip mesh with direct gRPC peer streaming

Binary Footprint Single executable under 25 MB with zero runtime dependencies

Operating Systems Linux (amd64/arm64), macOS (Apple Silicon), Windows (x64/arm64)

[Explore Industry Solutions](https://kushawaha.com/solutions) [Inquire Regarding Integration](https://kushawaha.com/contact)

## Deploy sovereign, high-assurance capabilities

Speak directly with Kushawaha Group architects regarding licensing, on-premise deployment, or collaborative development.

[Schedule Architecture Review](https://kushawaha.com/contact) [Review Whitepapers](https://kushawaha.com/research)

---

Source: https://kushawaha.com/capabilities/distributed-compute
Published by Kushawaha Group. Index of all pages: https://kushawaha.com/llms.txt