UNESA
si.ft@unesa.ac.id

AWS, NVIDIA Offer Deep Dive Into Their Partnership to Develop Hybrid Quantum Computing

AWS, NVIDIA Offer Deep Dive Into Their Partnership to Develop Hybrid Quantum Computing

- kategori Berita 65 Views

AWS and NVIDIA have partnered to tackle one of quantum computing’s major challenges: integrating classical computing into quantum systems. According to an AWS Quantum Technologies blog post, this collaboration introduces NVIDIA’s open-source CUDA-Q quantum development platform into Amazon Braket, allowing researchers to design, simulate, and run hybrid quantum-classical algorithms more effectively.

The Importance of Hybrid Computing
Hybrid computing, which merges classical and quantum computing, is essential for all quantum computing applications. Classical computers handle tasks like testing algorithms and error correction, while quantum computers solve problems beyond the reach of classical systems. As quantum processors advance, the need for powerful classical computing increases, particularly for error correction and pre-processing tasks.

This AWS-NVIDIA partnership aims to bridge this gap by providing researchers with direct access to NVIDIA’s CUDA-Q platform through Amazon Braket. This integration facilitates the use of powerful GPUs for program testing, enabling the same programs to be executed on quantum hardware with minimal adjustments.

Enhanced Simulations and Simplified Workflows
Integrating CUDA-Q into Amazon Braket brings notable performance improvements. For instance, tests have demonstrated that simulating a 21-qubit algorithm on a GPU was 350 times faster than on a CPU. This acceleration allows researchers to work on more extensive quantum systems efficiently.

According to the team, this collaboration is intended to help researchers concentrate on developing algorithms without worrying about managing infrastructure. The integration is designed to make hybrid quantum computing more accessible and practical for research purposes.

Amazon Braket users can now run CUDA-Q programs on any supported quantum hardware, including devices from IonQ, Rigetti, and IQM, by simply modifying a single line of code.

Preparing for Future Quantum Demands
Quantum error correction, a key technique for scaling quantum computing, heavily depends on classical processing. As quantum systems grow to support more qubits and deeper circuits, researchers will need faster hardware and more sophisticated tools to manage the quantum-classical interaction.

The AWS-NVIDIA partnership is building a foundation for such advancements. Their goal is to develop an integrated hybrid quantum-computing infrastructure that merges classical and quantum systems to provide flexibility and scalability for complex tasks.

The team highlights that as quantum technologies evolve, state-of-the-art workloads will demand increasingly advanced classical computing resources. This includes ultra-low-latency co-processing for quantum error correction, supercomputing-level classical pre- and post-processing, quantum hardware control, and AI-enhanced quantum simulations. To address these needs, AWS and NVIDIA are assessing future latency and computational requirements and developing a quantum computing stack that optimizes performance and flexibility.

Advantages for Researchers
This integration offers several benefits, including:

  • Accelerated Simulations: NVIDIA GPUs drastically cut simulation times, enabling quicker testing of quantum algorithms.
  • Streamlined Hybrid Workflows: Researchers can transition smoothly from simulations to quantum hardware execution with CUDA-Q on Braket.
  • Focus on Research: Managed access to GPUs and quantum devices simplifies infrastructure management for researchers.

Additionally, AWS’s pay-as-you-go pricing ensures cost-effectiveness for researchers dealing with demanding computational problems.

Performance Insights
AWS’s performance tests indicated that the CUDA-Q platform outpaced other open-source simulators for a 29-qubit algorithm, running much faster on a single GPU instance. Braket Hybrid Jobs also allow researchers to scale tasks across multiple GPUs, achieving significant speed boosts. For instance, parallelizing a 30-qubit circuit across eight GPUs resulted in a 6.5x speedup, while distributing 128 circuits yielded up to a 17x speedup for parameterized circuits. These improvements are essential for pushing the limits of quantum computing.

Future Focus
As the partnership between AWS and NVIDIA continues to evolve, it will focus on understanding the latency and compute requirements for future quantum workloads. The long-term vision is to establish an integrated quantum-classical computing ecosystem that supports researchers from algorithm design to execution on advanced quantum systems.

The team considers this integration as the initial step in a larger collaboration, anticipating a future where quantum and classical computing are increasingly interwoven. AWS provides example notebooks for researchers interested in exploring these tools, available in their GitHub repository.

Source: https://thequantuminsider.com/2024/12/04/aws-nvidia-offer-deep-dive-into-their-partnership-to-develop-hybrid-quantum-computing/

Scroll to Top