NVIDIA cuQuantum SDK: Accelerating Quantum Circuit Simulation I – cuTensorNet

20 views
Download
  • Share
Create Account or Sign In to post comments
#quantum computing #simulation #acceleration #simulators #GPU-based #tensor network #entangled pair

(39:25 + Q&A) Dr. Azzam Haidar, Nvidia -- Presentation from 2023 Workshop on Quantum Computing: Devices, Cryogenic Electronics and Packaging (QC-DCEP) ... 
Summary: We present the NVIDIA cuQuantum SDK, a state-of-the-art library of composable primitives for GPU-accelerated quantum circuit simulations. The cuQuantum SDK was created to accelerate and scale-up quantum circuit simulators developed by the quantum information science community by enabling them to utilize efficient scalable software building blocks optimized for NVIDIA GPU-based platforms. The functional building blocks provided cover the needs of both state vector- and tensor network-based simulators, including approximate tensor network simulation methods based on matrix product state, projected entangled pair state, and other factorized tensor representations. By leveraging the enormous computing power of the latest NVIDIA GPU architectures, quantum circuit simulators that have adopted the cuQuantum SDK demonstrate significant acceleration, compared to CPU-only execution, for both the state vector and tensor network simulation methods.
Azzam Haidar is a principal engineer at NVIDIA developing HPC and Quantum Computing software. He received a Ph.D. in 2008 major Computer Science and Applied Mathematics from the National Polytechnic Institute of Toulouse and from the CERFACS Lab, France. Before joining NVIDIA, he was a Research Director at the Innovative Computing Laboratory at the University of Tennessee, Knoxville. Azzam has a strong background in numerical mathematics, with interests focusing on the development, optimization and implementation of parallel scalable HPC libraries for distributed multicore/GPU-based architectures, for extreme-scale scientific applications. He is also working on developing algorithms and techniques to help making quantum simulation and synthesis feasible on current computer hardware.
He has an interest in developing optimized kernels for Deep Learning algorithm and studying techniques to speedup the learning process. He also developed novel algorithms for singular value (SVD) and eigenvalue problems as well as approaches that uses data flow representations to express parallelism in scientific applications.

Additional videos from the QC-DCEP Workhop can be accessed at https://attend.ieee.org/qc-dcep.

(39:25 + Q&A) Dr. Azzam Haidar, Nvidia -- Presentation from 2023 Workshop on Quantum Computing: Devices, Cryogenic Electronics and Packaging (QC-DCEP) ... 
Summary: We present the NVIDIA cuQuantum SDK, a state-of-the-art library of composable primitives for GPU-accelerated quantum circuit simulations. The cuQuantum SDK was created to accelerate and scale-up quantum circuit simulators developed by the quantum information science community by enabling them to utilize efficient scalable software building blocks ...

Speakers in this video

Advertisment

Advertisment