Quantum Computation Reading Group at KAUST - Introductory CUDA-Q Lecture

Short Description

Quantum computing is a new model of computing that can impact applications across industries, including drug discovery, chemistry, finance, energy, and more. Useful quantum computing will need a heterogeneous architecture which, in turn, requires an open and unified programming model. NVIDIA CUDA-Q is an open-source platform for integrating and programming quantum processing units (QPUs), GPUs, and CPUs in one system. In this lecture, we will discuss the history of the acceleration of computing, its intersection with quantum computing, quantum computing fundamentals on CUDA-Q, and CUDA-Q examples.

Outline

• Accelerating computing through GPUs and CUDA: scientific computing, AI and Deep Learning, now Quantum Computing.
• State of Quantum Computing: challenges and paths forward: simulation, hybrid quantum-classical computing (heterogeneous computing), AI for quantum
• CUDA-Q and CUDA-Q in action (examples: GQE, HSBC)
• Quantum Computing fundamentals on CUDA-Q: how to get started on CUDA-Q, qubits, sampling, how you use CUDA-Q.
• Interactive approach: participants are encouraged and welcome to pose questions. Those can be done through chat or by themselves directly. The lecture will be moderated.

Lecturers

• Principal Lecturer: Monica van Dieren
• Introduction, Moderation, Facilitation: Esperanza Cuenca Gomez

Date and Time

August 28th, 2024, at 6:00 PM AST (Riyadh Time), with a duration of 1 to 1.5 hours.

Suggested Readings

• Explainer: what is quantum computing?
• Explainer: What Is a QPU?
• An Introduction to Quantum Accelerated Supercomputing
• Defining the Quantum-Accelerated Supercomputer
• Quantum Accelerated Supercomputing: Powering Tomorrow's Breakthroughs
• NVIDIA CUDA-Q: The high-performance platform for hybrid quantum-classical computing
• **Focus on:** CUDA-Q documentation - Quick start, Basics, and Examples