Programming future heterogeneous quantum-classical supercomputing architectures

by Alex McCaskey (NVIDIA)

Monday Apr 29, 2024, 1:00 PM → 2:00 PM America/Chicago

Supercomputing architectures based on GPU acceleration have greatly improved our scientific computing workflows and applications over the past decade. Quantum computing has recently been proposed as a potential addition to this heterogeneous compute architecture, serving as another node-level accelerator to continue problem scalability in domains such as quantum many-body physics and artificial intelligence. As stand-alone quantum processing units (QPUs) continue to evolve and improve, the applied computational science community is left to wonder - how do we build, program, and deploy large-scale quantum-classical heterogeneous architectures that incorporate both GPUs and QPUs? In this talk, we will demonstrate how NVIDIA is leveraging its current suite of multi-GPU platforms to define and deploy the NVIDIA quantum platform. Specifically, we will highlight CUDA Quantum - a quantum-classical programming model in C++ and Python, and associated compiler toolchain built on the MLIR and LLVM frameworks. This talk will focus on technical details of the programming model and compiler architecture, and demonstrate the utility of CUDA Quantum when targeting both real and emulated quantum coprocessors. 

McCaskey, Alex 04:29:2024.mp4