Dr Wei Fang1
1NVIDIA, Sydney, Australia
Quantum computing has the potential to offer giant leaps in computational capabilities—and the ability of scientists, developers, and researchers to simulate quantum circuits on classical computers is vital to get us there. The research community across academia, laboratories, and industry are using simulators to help design and verify algorithms to run on quantum computers. These simulators capture the properties of superposition and entanglement and are built on quantum circuit simulation frameworks.
To help bridge the gap between classical and quantum computers, NVIDIA has introduced cuQuantum SDK and Quantum-Optimized Device Architecture (QODA) hybrid quantum-classical computing platform. The cuQuantum is an SDK of optimized libraries and tools for accelerating quantum computing workflows. Using NVIDIA Tensor Core GPUs, developers can use cuQuantum to speed up quantum circuit simulations based on state vector and tensor network methods by orders of magnitude. The cuQuantum works with an expanding ecosystem of quantum computing and simulation frameworks. QODA hybrid quantum-classical computing platform facilitates the integration and programming of quantum processing units (QPUs), GPUs, and CPUs in one system. It enables GPU-accelerated system scalability and performance across heterogeneous QPU, CPU, GPU, and emulated quantum system elements.
In this talk we are going to discuss the QODA and cuQuantum and how the universities or industry can start to adopt the hybrid quantum-classical computing platforms to enable pioneering quantum computing research and quantum applications development on existing HPC clusters, or emerging hybrid infrastructures either on-prem, in the national HPC facilities, or in the cloud.
Biography:
Dr. Wei Fang joined NVIDIA as a Solution Architect for HPC in Dec 2021. He is currently working with the HPC community in the APAC South region to help adopt the best of HPC and AI technology. Before joining NVIDIA, he had been an HPC Specialist for more than 8 years at Intersect Australia delivering HPC operation, designing and consultation services for the higher education and research community around Australia. Before that he worked with National Computational Infrastructure (NCI), Geoscience Australia and a few private companies delivering software solutions solving challenging engineering problems. He has many years of full stack HPC experience including GPU/CPU internal, networking, storage, clustering, parallel programming and performance optimization. He received his PhD in Electrical Engineering from Nanyang Technology University, Singapore in 2004.