(HPCWire) Agnostiq, Inc., a quantum computing SaaS startup headquartered in Toronto, has announced the release of Covalent, an open-source workflow orchestration platform designed specifically for quantum computing and HPC technologies. Covalent aims to make quantum and high performance computing resources more accessible to practitioners and developers, including machine learning engineers and data scientists.
Covalent started out as an internal tool for our quantum algorithm research team,” says Agnostiq’s head of R&D, Santosh Kumar Radha. “It was a tool designed to give my team the ability to prototype, calculate, and analyze reproducible experiments at scale right from the comfort of our laptops. We are very excited to share Covalent with the broader community,” he added.
“Covalent encourages users to break down and reuse components in scientific applications. This modularity enables users to focus on code design while abstracting away the details of how or where execution occurs. As a result, users can more easily integrate a variety of classical and quantum hardware backends into their software,” says William Cunningham, Agnostiq’s head of software engineering.
Covalent solves the following challenges associated with these advanced computing technologies:
Breaks workflows down into modular Python components, allowing users to easily reproduce repetitive code and avoid costly reruns; important in a high performance computing/quantum setting since running experiments on these devices is extremely expensive;
Serves as a single entry point for Quantum Processors, CPUs, GPUs, and quantum-inspired hardware, with no additional setup required; and
Includes an intelligent task scheduler that automatically selects the best hardware resource for a given task based on a mix of predefined as well as user-defined constraints.
The company previously secured $2 million in seed funding, led by Differential Ventures, with follow-on participation from Scout Ventures, Boost VC, Tensility Venture Partners, and Green Egg Ventures.