#nvidiaquantumsimulation

NVIDIA quantum

NVIDIA has introduced a cloud service that enables scientists and engineers to explore the limits of quantum computing in important scientific fields including materials science, chemistry, and biology. And NVIDIA platforms for accelerated and quantum computing would power Japan’s new ABCI-Q supercomputer, which is intended to further the country’s quantum computing effort.

Nvidia quantum simulator NVIDIA’s Quantum Simulation Platform is accessible via major cloud providers and may help scientists advance research in quantum computing and algorithms.

Nvidia quantum computing Three-quarters of the businesses deploying quantum processing units, or QPUs, utilize the open-source CUDA-Q quantum computing technology, which forms the foundation of NVIDIA Quantum Cloud. It is the first microservice that enables users to create and test novel quantum algorithms and applications in the cloud, including robust simulators and tools for hybrid quantum-classical programming.

Tim Costa, head of HPC and quantum computing at NVIDIA, said, “Quantum computing presents the next revolutionary frontier of computing and it’s going to require the world’s most brilliant minds to bring this future one step closer.” “Every scientist in the world can now harness the power of quantum computing and bring their ideas closer to reality with the help of NVIDIA Quantum Cloud, which breaks down barriers to the exploration of this revolutionary technology.”

To speed up scientific research, Quantum Cloud has strong functionality and third-party software integrations, such as:

Working with the University of Toronto, the Generative Quantum Eigensolver makes use of large language models (LLMs) to speed up the quantum computer’s ability to determine a molecule’s ground-state energy. Due to Classiq’s integration with CUDA-Q, quantum researchers are able to create complex, large-scale programs and perform in-depth analysis and simulation of quantum circuits. Complex quantum chemistry challenges, such molecular modeling, are addressed by QC Ware Promethium. NVIDIA Cuda quantum The cutting-edge hybrid quantum-classical computer platform A bridge technology is required to allow dynamic workflows across heterogeneous system architectures for the purpose of conducting algorithm research and developing applications for future quantum benefits. NVIDIA CUDA-Q is an open-source platform that combines and programs GPUs, CPUs, and quantum processing units (QPUs) in a single system using a unified and open programming approach. Over heterogeneous QPU, CPU, GPU, and simulated quantum system parts, CUDA-Q accelerates system scalability and performance.

NVIDIA CUDA-Q Typical QML workflow in CUDA-Q using multi-threaded CPU versus multiple NVIDIA A100 Tensor Core GPUs Constructed for Effectiveness

Simple hybrid code execution on a wide variety of quantum processors both simulated and real is made possible by NVIDIA CUDA-Q. Researchers may link their own simulator or quantum processor, or they can use the cuQuantum-accelerated simulation backends and QPUs from their partners.

When comparing NVIDIA CUDA-Q to other quantum frameworks, quantum computations may be accelerated considerably. Using several GPUs, quantum algorithms may scale the number of qubits and reach speedups of up to 2500X over CPU.

The Quantum Ecosystem’s Adoption NVIDIA’s ecosystem for quantum computing has over 160 partners. As with many other major quantum enterprises including IQM Quantum Computers, OQC, ORCA Computing, qBraid, and Quantinuum, top cloud service providers like Google Cloud, Microsoft Azure, and Oracle Cloud Infrastructure are incorporating Quantum Cloud into their services.

Access to Quantum computing Nvidia By registering for early access, innovators in quantum computing may use NVIDIA Quantum Cloud to jumpstart and accelerate their quantum computing research.

ABCI-Q Advances National Quantum Computing with NVIDIA Hopper Architecture and CUDA-Q

Nvidia quantum 2 High-fidelity quantum simulations for research across sectors will be made possible by ABCI-Q. NVIDIA CUDA-Q, an open-source hybrid quantum computing platform with strong simulation tools and the ability to design hybrid quantum-classical systems, is integrated with the high-performance, scalable system. More than 500 nodes, each with more than 2,000 NVIDIA H100 Tensor Core GPUs, are linked to the supercomputer using NVIDIA Quantum-2 InfiniBand, the only completely offloadable in-network computing platform in existence.

Built by Fujitsu at the National Institute of Advanced Industrial Science and Technology (AIST) ABCI supercomputing center, the Global Research and Development center for Business by Quantum-AI Technology (G-QuAT) ABCI-Q is intended to be deployed early in the next year and is engineered for integration with quantum hardware in the future.

Tim Costa, NVIDIA’s head of high performance computing and quantum computing, said that “researchers need high-performance simulation to tackle the most difficult problems in quantum computing.” “Quantum-integrated supercomputing pioneers like those at ABCI are able to accelerate its development and make significant strides thanks to the NVIDIA H100 and Cuda-Q.”

Masahiro Horibe, deputy director of G-QuAT/AIST, said that “ABCI-Q will let Japanese researchers explore quantum computing technology to test and accelerate the development of its practical applications.” “These scientists will be able to explore the next frontiers of quantum computing research with the support of the NVIDIA CUDA-Q platform and NVIDIA H100.”

A component of Japan’s strategy for innovation in quantum technology, ABCI-Q seeks to open up new avenues for companies and society to profit from quantum technology, notably via research in artificial intelligence (AI), renewable energy, and biology.

The ABCI-Q system is meant to serve as a platform for the development of novel algorithms motivated by quantum technology, the creation of classical-quantum hybrid systems, and the progress of quantum machine learning and quantum circuit modeling.

Nvidia quantum-2 infiniband Network Communications Performance That Breaks Records

The seventh version of the NVIDIA InfiniBand architecture, NVIDIA Quantum-2, provides the fastest networking speed and feature sets accessible to scientific researchers and AI developers to tackle the most difficult issues in the world. With features like software-defined networking, In-Network Computing, performance isolation, powerful acceleration engines, remote direct memory access (RDMA), and the highest rates and feeds up to 400Gb/s, NVIDIA Quantum-2 powers the top supercomputing data centers in the world.

Improving Applications and Supercomputers for AI and HPC Enhanced In-Network Processing Faster interconnects and more intelligent networks are needed for high-performance computing (HPC), artificial intelligence (AI), and hyperscale infrastructures in order to analyze data and conduct complicated simulations more quickly and effectively. With preconfigured and programmable compute engines, such as the third iteration of the NVIDIA Scalable Hierarchical Aggregation and Reduction Protocol (SHARPv3), Message Passing Interface (MPI) Tag Matching, MPI All-to-All, and programmable engines, NVIDIA Quantum-2 expands and improves its In-Network Computing while providing the best ROI and cost per node.

Isolation of Performance With the help of cutting-edge proactive monitoring and congestion management, the NVIDIA Quantum-2 InfiniBand platform can enable traffic isolations, almost completely eliminate performance jitter, and guarantee predictive performance as if the application were running on a dedicated machine.

Native Cloud-Based Supercomputing The NVIDIA Cloud-Native Supercomputing platform combines high-speed, low-latency NVIDIA Quantum-2 InfiniBand networking with the NVIDIA BlueField data processing unit (DPU) architecture. The system easily and securely provides bare-metal performance, data security, user management and isolation, on-demand high performance computing (HPC), and AI services.