Quantum computing guarantees to revolutionize science and industry, from drug discovery to materials science. But constructing a useful, large-scale quantum computer is a major engineering challenge, particularly in terms of designing qubits which might be less at risk of noise.Â
In traditional chip design, the fashionable semiconductor industry relies on Electronic Design Automation (EDA) tools to create and validate chips in software before committing to costly fabrication. Similarly, the design of quantum chips can profit significantly from EDA tools. Simulating the noise in quantum chips is notoriously complex. Such chips are highly sensitive to each noise within the environment and unwanted interactions between different circuit elements, something generally known as cross-talk.
NVIDIA works closely with Lawrence Berkeley National Laboratory (Berkeley Lab) and other researchers to supply the hardware and software platform needed for GPU-accelerated EDA tools that allow rapid iteration on quantum chip designs.
Berkeley Lab researchers have developed ARTEMIS, an open source simulation package for full-wave simulation of novel chips. Using the NVIDIA CUDA platform to GPU-accelerate ARTEMIS, the researchers recently demonstrated the world’s largest simulation of a full quantum chip on the NVIDIA GPUs inside NERSC’s Perlmutter supercomputer.
Simulating across spatial-scalesÂ
Probably the most popular architectures for developing quantum processors is to leverage superconducting qubits fabricated on a solid-state substrate, allowing the usage of fabrication methods much like those from traditional semiconductor manufacturing.
Accurate simulations of those qubits must resolve physics across multiple orders of magnitude in spatial scale, from micrometer-scale qubit structures to the centimeter-scale dimensions of the total chip. Without access to GPU-accelerated simulations, nevertheless, simulations-to-date have been limited either to small, high-resolution regions of the chip or coarser-resolution, full-chip models that miss critical microscale interactions; they’ve forced researchers to trade accuracy for scalability.Â
Accurately capturing the coupled electromagnetic behavior of those systems requires a computationally demanding time-domain approach. Time-resolved simulations can track how control pulses and microwave signals propagate, reflect, and interfere across the chip in real time, directly revealing transient effects resembling cross-talk, mode coupling, and signal distortion that frequency-domain methods often miss.
Berkeley Lab’s ARTEMIS platform optimizes these comprehensive simulations for parallelization on NVIDIA GPUs—providing a full-wave, time-domain electromagnetic solver. Resulting from the acute scalability of GPU-accelerated simulations, ARTEMIS can accurately model large, chip-scale systems while preserving superb spatial and temporal details. It resolves electromagnetic interactions from micrometer-scale qubit structures to centimeter-scale control lines. This multiscale fidelity provides latest physical insight into chip-level coupling dynamics between control signals and qubit structures.
Simulating on the shoulders of giants
Announced at GTC DC, Berkeley Lab and NERSC performed the primary full-wave electrodynamical simulation of a whole state-of-the-art, multi-layer quantum chip. The team harnessed the total power of Perlmutter, running the simulation on 6,724 NVIDIA A100 Tensor Core GPUs, 95% of the whole system. The 1 cm chip was discretized into over 10 billion grid points using micron resolution. Â
It took nearly eight hours on the total system to model the 1.5 million time steps required to succeed in 1 nanosecond of physical time. The simulation modeled the full-time dynamics of the chip, allowing researchers to watch the propagation of control signals through the chip at femtosecond time resolution. That is critical for understanding crosstalk, which is certainly one of the largest hurdles within the design of superconducting quantum chips.
By drawing on the NVIDIA CUDA platform for a validated and scalable simulation framework, physicists can now test novel qubit architectures, discover and reduce noise sources and cross-talk, and validate quantum chip designs before entering the fabrication cycle. This information is critical for designers to construct higher, more robust chips, and speed up their fabrication cycles—providing the powerful toolset needed to speed up the trail to useful quantum computing.
The NVIDIA CUDA-Q platform provides out-of-the-box tools which might be accelerating breakthroughs in the important thing workloads in quantum computing.
