The GPU Mesh Network

Architecture of the decentralized inference routing layer.

The Vektor GPU Mesh is a peer-to-peer network of enterprise-grade compute nodes, specifically optimized for high-throughput AI inference and Large Language Model (LLM) serving.

Architectural Overview

Unlike traditional cloud providers that rely on centralized, geographically isolated server farms, Vektor utilizes a distributed mesh topology. This ensures zero single points of failure and dynamic load balancing across global regions.

The Routing Engine

When an AI developer submits an inference request to the Vektor API, the request is not routed to a static server. Instead, it hits the Vektor Routing Engine, an intelligent load balancer that evaluates the global mesh in milliseconds based on:

1. Proximity: Routing to the geographically closest available node to minimize latency to < 50ms.
2. Hardware Matching: Ensuring the specific model requirements (e.g., memory bandwidth, tensor core utilization) are matched with the optimal hardware (NVIDIA H100 vs. A100).
3. Current Load: Avoiding node saturation by distributing concurrent requests across multiple redundant data centers.

Zero-Downtime Fallback

In the event of a localized power failure or hardware degradation at a specific data center, the mesh automatically reroutes the inference pipeline to the next optimal node within 12ms. This guarantees the 99.97% Uptime SLA promised to enterprise clients.