The Department of Energy’s Pacific Northwest National Laboratory has partnered with NVIDIA to develop an open-source framework that connects open-source graphics processing unit, or GPU, acceleration to quantum-classical computing using the NVIDIA NVQLink platform.
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What Is the Purpose of the PNNL Framework?
PNNL said Monday the framework is designed to expand access to advanced quantum research capabilities by lowering barriers for scientists and engineers. Announced at NVIDIA GTC 2026, the initiative enables more detailed exploration of quantum control and measurement than is typically possible through cloud-based services.
How Does the Framework Work?
The research team is integrating NVIDIA GH200 Grace Hopper Superchips with a field-programmable gate array, or FPGA-based measurement and control system. FPGAs are reconfigurable logic devices used in quantum instrumentation kits for fast signal processing. By linking GPUs directly, the system enables high-throughput computing with minimal delay, a critical factor for quantum experiments where timing and rapid data processing are essential.
How Does the Integration Support Quantum Experimentation?
Connecting directly to GPUs enables high-throughput computing to handle complex calculations while reducing delay. This close integration is important for quantum experiments, where precise timing and fast data processing are critical. The approach also offers a practical way to test and refine near-term quantum systems, with potential benefits for both scientific research and industry use.
PNNL project lead Sam Stein said the NVQLink platform, an open system architecture that integrates GPU computing with quantum processors, leverages high-performance classical GPUs to handle the intensive real-time computing demands of quantum processors.
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