Qoro Launches Cloud Platform For Parallelised Quantum-Classical Computing Simulation
Insider Brief Qoro has launched Solo, a self-serve cloud platform that provides individual developers, enterprises, and scientists with streamlined access to classical simulation of hybrid quantum-classical workloads. Solo enables users to design, test, and scale workflows across CPUs, GPUs, and QPUs without extensive custom integration, reducing infrastructure complexity and cutting benchmark simulation times from more than a day to under 10 minutes for 9,000 jobs. The platform operates alongside Qoro’s enterprise offering Dedicato and is built on the company’s core technologies — Divi, Composer, and Maestro — which support hybrid workload development, orchestration, and multilayered parallelized simulation across heterogeneous hardware. PRESS RELEASE — Qoro has announced the launch of Solo, giving individual IT developers, enterprises, and scientists seamless, self-serve access to classical simulation of hybrid quantum workloads. Currently, building workflows across fragmented hybrid computing systems – which combine CPUs, GPUs, and Quantum Processing Units (QPUs) – requires deep academic expertise, months of custom integration code, and complex hardware translation. However, through Qoro’s new cloud service, Solo, developers and scientists no longer need to write extensive code every time they test a new simulator, a new quantum backend, or scale to high-performance computers (HPC). By eliminating the infrastructure headache, Solo saves enormous amounts of time, making the design, simulation, and scaling of quantum-classical workloads much more accessible. For example, where running 9,000 quantum simulation jobs on a standard local setup takes more than a day, Solo completes the same workload in under 10 minutes*. “Developers working on large-scale quantum computing problems, such as financial portfolio optimisation, are hitting the limits of classical simulation – problems that have outgrown even high-performance servers, yet remain too complex for today’s
