ACC Cyfronet AGH and Quantumz.io proudly announce that, thanks to their cooperation, the advanced physics-inspired optimization solver VeloxQ is now available within the national supercomputing infrastructure PLGrid. This strategic integration enables Polish researchers to access state‑of‑the‑art optimization capabilities without the need for specialized hardware or complex computing environments.
VeloxQ - developed by a team of Polish experts in physics, mathematics, and computer science - introduces a new generation of large‑scale optimization tools capable of solving some of the world’s most challenging computational problems using classical supercomputers only. With its deployment on PLGrid, these capabilities become accessible to a broad scientific community.
A physics‑inspired approach to complex optimization
VeloxQ is based on the QUBO (Quadratic Unconstrained Binary Optimization) model, a widely used mathematical formalism for decision‑making, planning, and combinatorial problems. Inspired by physical and statistical processes, VeloxQ treats computational problems as energy landscapes, dynamically exploring the most promising low‑energy (optimal) states.
This unique methodology allows VeloxQ to:
- Efficiently handle problems involving hundreds of millions of binary variables
- Provide a spectrum of multiple high‑quality solutions, rather than a single output
- Eliminate the need for problem embedding, which limits many classical and quantum solvers
- Run on widely available GPUs, including high‑performance PLGrid compute nodes
VeloxQ on PLGrid - high performance made accessible
The newly launched VeloxQ on PLGrid service allows users to submit large‑scale optimization workloads directly to PLGrid HPC resources. Instead of managing clusters, queues, or GPUs, researchers can:
- Hold an active PLGrid account with an appropriate computing grant
- Log in to the VeloxQ portal using Login with PLGrid
- Link their PLGrid account with their VeloxQ profile
- Generate an API key and authenticate via the VeloxQ SDK
- Submit QUBO/HUBO optimization tasks to VeloxQ backends running on PLGrid
- Retrieve solution ensembles for further analysis or deployment
This workflow ensures high computational performance with minimal integration effort, making it ideal for academic laboratories, R&D teams, and AI/ML engineers.
Key benefits for researchers
Supercomputer‑level scalability - VeloxQ runs efficiently on GPUs without requiring quantum computers or specialized hardware, delivering breakthrough‑scale optimization today. Future releases are expected to support hybrid workflows combining classical and quantum hardware.
Multiple candidate solutions - Instead of a single result, users receive a diverse ensemble of low‑energy solutions, enabling scenario analysis, risk evaluation, and multi‑criteria decision‑making.
Native graph support without embedding - VeloxQ natively supports problem topologies, eliminating costly and time‑consuming embedding stages.
Seamless workflow integration - An intuitive SDK and API enable rapid prototyping, experimentation, and integration with existing scientific and enterprise software ecosystems.
About VeloxQ
VeloxQ is an advanced optimization solver developed by Quantumz.io. It leverages physics‑inspired heuristics, massive scalability, and GPU acceleration to deliver top performance for solving extremely large QUBO and HUBO problems.
A new chapter for Polish computational innovation
Making VeloxQ available through PLGrid marks an important step toward democratizing high‑performance optimization for academic environments in Poland. Combining cutting‑edge solver technology with national supercomputing resources enables larger problems, faster experimentation, and accelerated innovation.
VeloxQ was officially introduced as a PLGrid service during the 18th HPC Users' Conference organized by ACC Cyfronet AGH in Zakopane, April 13–15, 2026.
Find more information in the VeloxQ documentation in the PLGrid Guide.
