69 citations · 83 across the 8 of their papers we have counts for
8 papers
ATTNChecker: Highly-Optimized Fault Tolerant Attention for Large Language Model Training
Yuhang Liang, Xinyi Li, Jie Ren +3
Large Language Models (LLMs) have demonstrated remarkable performance in various natural language processing tasks. However, the training of these models is computationally intensi…
Red-QAOA: Efficient Variational Optimization through Circuit Reduction
Meng Wang, Bo Fang, Ang Li +1
The Quantum Approximate Optimization Algorithm (QAOA) addresses combinatorial optimization challenges by converting inputs to graphs. However, the optimal parameter searching proce…
TANQ-Sim: Tensorcore Accelerated Noisy Quantum System Simulation via QIR on Perlmutter HPC
Ang Li, Chenxu Liu, Samuel Stein +7
Although there have been remarkable advances in quantum computing (QC), it remains crucial to simulate quantum programs using classical large-scale parallel computing systems to va…
MEMQSim: Highly Memory-Efficient and Modularized Quantum State-Vector Simulation
Boyuan Zhang, Bo Fang, Qiang Guan +2
In this extended abstract, we have introduced a highly memory-efficient state vector simulation of quantum circuits premised on data compression, harnessing the capabilities of bot…
Efficient Hierarchical State Vector Simulation of Quantum Circuits via Acyclic Graph Partitioning
Bo Fang, M. Yusuf Özkaya, Ang Li +2
Early but promising results in quantum computing have been enabled by the concurrent development of quantum algorithms, devices, and materials. Classical simulation of quantum prog…
A Hybrid System for Learning Classical Data in Quantum States
Samuel A. Stein, Ryan L'Abbate, Wenrui Mu +6
Deep neural network powered artificial intelligence has rapidly changed our daily life with various applications. However, as one of the essential steps of deep neural networks, tr…
QuGAN: A Quantum State Fidelity based Generative Adversarial Network
Samuel A. Stein, Betis Baheri, Daniel Chen +5
Tremendous progress has been witnessed in artificial intelligence where neural network backed deep learning systems have been used, with applications in almost every domain. As a r…
MARS: Malleable Actor-Critic Reinforcement Learning Scheduler
Betis Baheri, Jacob Tronge, Bo Fang +3
In this paper, we introduce MARS, a new scheduling system for HPC-cloud infrastructures based on a cost-aware, flexible reinforcement learning approach, which serves as an intermed…