Introduction

Introduction

The Quantum Datacenter

Quantum datacenters are on the horizon. These next-generation facilities will house not just classical CPUs and GPUs, but also quantum processing units (QPUs) from multiple vendors — each with different architectures, qubit counts, gate sets, and error characteristics.

There won’t be a single winner. Superconducting qubits, trapped ions, neutral atoms, and photonic processors will coexist alongside classical accelerators. Each technology excels in a different regime:

Resource Strengths
CPUs Control flow, classical pre/post-processing, optimization loops
GPUs Tensor network simulation, large-scale parallel classical computation
QPUs Sampling from quantum distributions, certain optimization and chemistry problems
Simulators Prototyping, validation, circuits with low entanglement or Clifford structure

The challenge isn’t building these machines — it’s using them together effectively.

The Orchestration Problem

To extract value from a heterogeneous quantum datacenter, you need software that can:

  1. Analyze a quantum workload and determine which resources can handle it best
  2. Partition problems that are too large for any single device
  3. Route sub-tasks to the right hardware — simulator, GPU, or QPU
  4. Execute many circuits in parallel across all available backends
  5. Aggregate results and feed them back into classical optimization loops

This is exactly what Qoro’s platform does.

Qoro’s Software Stack

Qoro provides a modular software stack for programming, orchestrating, and executing quantum workloads across heterogeneous infrastructure:

  • Divi — A Python SDK for building quantum programs with built-in parallelization
  • Maestro — An intelligent simulator that auto-selects the best simulation backend
  • Composer — A cloud platform for scheduling, routing, and orchestrating jobs
  • Composer Interfaces — Unified access to QPU hardware from IBM, IQM, AWS Braket, and more

Together, these components turn a fragmented landscape of quantum and classical resources into a unified, programmable compute layer.