HexaGrid™ — Architecture
Architecture

Built for GPU-Intensive Infrastructure

HexaGrid integrates live wholesale electricity markets, neural forecasting, reinforcement learning, and quantum-ready optimization into a unified control layer designed for AI data centers and multi-site compute environments. Powered by the QLLMe™ hybrid optimization engine.

System Design

Three-Tier Modular Architecture

Each tier of HexaGrid is independently deployable and communicates exclusively over a versioned REST API. This enables horizontal scaling of any individual component without disrupting the platform.

The backend consists of ten independent Python modules, each owning its own data persistence layer. All modules are exposed through a unified FastAPI application on port 8000 with auto-generated OpenAPI documentation. The dashboard is a single static HTML file — zero build dependencies, deployable anywhere.

Powered by QLLMe™ at the optimization core


Schedule Infrastructure Review
External
EIA Grid Prices
Electricity Maps CO₂
NVML GPU Telemetry
Backend
Grid Connector
Digital Twin
LSTM Forecaster
QLLMe™ Core
QAOA Scheduler
PPO RL Agent
Fleet Orchestrator
Monitoring
Carbon Connector
GPU Monitor
Site Orchestrator
API Layer
FastAPI · Port 8000 · OpenAPI /docs · Versioned REST
Dashboard
8-Tab Dashboard · Overview · Twin · Scheduler · RL · Carbon · Fleet · Hardware
Design Principles

How HexaGrid Is Built

01

Modular, Not Monolithic

Every pillar is an independent Python module with its own data persistence and API surface. Components can be deployed, updated, or replaced in isolation without disrupting the rest of the platform.

02

Live Data, Not Stale Models

HexaGrid maintains live connections to EIA and Electricity Maps at all times. Every dispatch decision is made on current market state — not monthly averages, estimates, or historical proxies.

03

Quantum-Ready by Design

The QAOA scheduler runs on Cirq's hardware abstraction layer. The same circuit architecture migrates to real QPU backends as quantum hardware matures — with zero code changes required.

04

Full Operator Transparency

Every routing decision, RL action, and hardware alert is logged and visible in the dashboard. Operators see the reasoning behind every recommendation and retain full override capability.

05

Zero Build Dependencies

The dashboard is a single static HTML file. No webpack, no Node, no build pipeline. It serves from nginx, an S3 bucket, or a local Python server in seconds.

06

Continuous Adaptation

The PPO agent and IsolationForest models retrain on live data. HexaGrid does not degrade over time — it improves as market patterns and hardware behavior accumulate in its training corpus.

Technical Stack

What HexaGrid Runs On

Component Technology Purpose Version
Digital Twin SimPy discrete-event simulation GPU rack power flow, PUE modeling, thermal dynamics 4.1+
LSTM Forecaster TensorFlow LSTM 120-minute grid price prediction, real-time inference TF 2.13+
QAOA Scheduler Cirq + TensorFlow Quantum Quantum-classical hybrid job scheduling optimization Cirq 1.2+
RL Dispatch Agent Stable Baselines 3 PPO Adaptive workload deferral, 200k training steps SB3 2.0+
API Platform FastAPI + Uvicorn Versioned REST, OpenAPI /docs, CORS, structured logging 0.104+ / 0.24+
Carbon Layer Electricity Maps API Live gCO₂eq/kWh per ISO, Pareto cost–carbon analysis v3
Fleet Orchestrator Python + SQLite Multi-site composite scoring, routing history, 4 strategies Python 3.11+
GPU Monitor pynvml + scikit-learn NVML telemetry, IsolationForest anomaly detection, health scoring 11.5+ / 1.3+
GPU Acceleration CUDA + NVIDIA Driver TF training, RL optimization, quantum circuit simulation CUDA 12.x / 525+
About

Quantum Clarity LLC

HexaGrid is built by Quantum Clarity LLC, a deep-technology firm developing quantum-enhanced optimization systems for AI infrastructure and enterprise compute environments.

The platform emerged from applied research at the intersection of quantum computing, reinforcement learning, and real-time energy systems. Every component has been validated on live hardware with real market data — not simulated environments or theoretical benchmarks.

Quantum Clarity also develops the QLLMe™ optimization engine and QuantaCore™ modular quantum computing platform — two complementary technologies that underpin HexaGrid's long-term technical roadmap.

QLLMe™ Hybrid Optimization Engine

Proprietary engine combining QAOA quantum circuits, PPO reinforcement learning, and classical multi-objective optimization in a unified dispatch pipeline. Core IP of the HexaGrid platform.

QuantaCore™ Quantum Platform

Modular quantum computing platform validated at 116 qubits with 85.7% average fidelity. Provides the hardware pathway for HexaGrid's QAOA scheduler as QPU backends mature.

Validated on Production Hardware

All platform benchmarks produced on real NVIDIA GPU hardware with live EIA and Electricity Maps data feeds. Fully operational at v1.0.0 — not a prototype.

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