A5010618296- Quantum Computing Algorithms and Architecture
- Advanced Data Storage Technologies
- Quantum Information and Cryptography
- Quantum many-body systems
- Tensor decomposition and applications
- IoT and Edge/Fog Computing
- Parallel Computing and Optimization Techniques
- Image Enhancement Techniques
- Distributed and Parallel Computing Systems
- Cloud Computing and Resource Management
- Industrial Vision Systems and Defect Detection
- Spectroscopy and Quantum Chemical Studies
- Neural Networks and Reservoir Computing
- Quantum-Dot Cellular Automata
University of Illinois Urbana-Champaign
1989-2021
This report presents a methodology for measuring the performance of supercomputers. It includes 13 Fortran programs that total over 50,000 lines source code. They represent applications in several areas engi neering and scientific computing, many cases codes are currently being used by computational re search development groups. We also present PERFECT standard, set guidelines allow portability to types machines. Furthermore, we some measures method ology recording sharing results among...
Simulation of quantum systems is challenging due to the exponential size state space. Tensor networks provide a systematically improvable approximation for states. 2D tensor such as Projected Entangled Pair States (PEPS) are well-suited key classes physical and circuits. However, direct contraction PEPS has cost, while approximate algorithms require computations with large tensors. We propose new scalable software abstractions PEPS-based methods, accelerating bottleneck operation...
Abstract The recent emergence of novel computational devices, such as quantum computers, coherent Ising machines, and digital annealers presents new opportunities for hardware-accelerated hybrid optimization algorithms. Unfortunately, demonstrations unquestionable performance gains leveraging hardware platforms have faced significant obstacles. One key challenge is understanding the algorithmic properties that distinguish devices from established approaches. Through careful design contrived...
Simulation of quantum systems is challenging due to the exponential size state space. Tensor networks provide a systematically improvable approximation for states. 2D tensor such as Projected Entangled Pair States (PEPS) are well-suited key classes physical and circuits. However, direct contraction PEPS has cost, while approximate algorithms require computations with large tensors. We propose new scalable software abstractions PEPS-based methods, accelerating bottleneck operation...