Speaker
Description
Quantum circuit simulation is a critical step for developing, validating, and debugging novel quantum algorithms designed for the gate-based quantum computing model. It allows quantum computing researchers, scientists and engineers to harness the classical computing power for simulating an ideal, fault-tolerant quantum computer way before one is ready for use in production. However, it requires delicate design and implementation to bring satisfying performance, and graphic processing units (GPUs) are a natural candidate for tackling massively parallel computation. In this talk, I will present the cuQuantum SDK developed by NVIDIA, a collection of high-performance GPU libraries currently offering state vector and tensor network based simulation methods. Since its debut, the cuQuantum SDK has been adopted by major quantum computing frameworks such as Qiskit, Cirq, and Pennylane, as we ensure it is easily accessible to C/C++ and Python users, thus allowing straightforward integration into any existing workflow. I will discuss the design principles and key features that we bring to our GPU users. Finally, I will briefly comment on the future plan for cuQuantum, including multi-node and multi-GPU support.
