14 citations · 39 across the 11 of their papers we have counts for
11 papers
Quantum vs. Classical Machine Learning: A Unified Empirical Comparison
Chuanming Yu, Jiaming Liu, Zihao Ge +4
Quantum computing has emerged as a promising computational paradigm for machine learning (ML), with the potential to offer computational advantages over classical approaches. At th…
On Repairing Quantum Programs Using ChatGPT
Xiaoyu Guo, Jianjun Zhao, Pengzhan Zhao
Automated Program Repair (APR) is a vital area in software engineering aimed at generating automatic patches for vulnerable programs. While numerous techniques have been proposed f…
VQPy: An Object-Oriented Approach to Modern Video Analytics
Shan Yu, Zhenting Zhu, Yu Chen +6
Video analytics is widely used in contemporary systems and services. At the forefront of video analytics are video queries that users develop to find objects of particular interest…
An Empirical Study of Bugs in Quantum Machine Learning Frameworks
Pengzhan Zhao, Xiongfei Wu, Junjie Luo +2
Quantum computing has emerged as a promising domain for the machine learning (ML) area, offering significant computational advantages over classical counterparts. With the growing…
QChecker: Detecting Bugs in Quantum Programs via Static Analysis
Pengzhan Zhao, Xiongfei Wu, Zhuo Li +1
Static analysis is the process of analyzing software code without executing the software. It can help find bugs and potential problems in software that may only appear at runtime.…
Bamboo: Making Preemptible Instances Resilient for Affordable Training of Large DNNs
John Thorpe, Pengzhan Zhao, Jonathan Eyolfson +5
DNN models across many domains continue to grow in size, resulting in high resource requirements for effective training, and unpalatable (and often unaffordable) costs for organiza…
A Comprehensive Study of Bug Fixes in Quantum Programs
Junjie Luo, Pengzhan Zhao, Zhongtao Miao +2
As quantum programming evolves, more and more quantum programming languages are being developed. As a result, debugging and testing quantum programs have become increasingly import…
Bugs4Q: A Benchmark of Real Bugs for Quantum Programs
Pengzhan Zhao, Jianjun Zhao, Zhongtao Miao +1
Realistic benchmarks of reproducible bugs and fixes are vital to good experimental evaluation of debugging and testing approaches. However, there is no suitable benchmark suite tha…
Identifying Bug Patterns in Quantum Programs
Pengzhan Zhao, Jianjun Zhao, Lei Ma
Bug patterns are erroneous code idioms or bad coding practices that have been proved to fail time and time again, which are usually caused by the misunderstanding of a programming…
DISC: A Dynamic Shape Compiler for Machine Learning Workloads
Kai Zhu, Wenyi Zhao, Zhen Zheng +8
Many recent machine learning models show dynamic shape characteristics. However, existing AI compiler optimization systems suffer a lot from problems brought by dynamic shape model…
FusionStitching: Boosting Memory Intensive Computations for Deep Learning Workloads
Zhen Zheng, Pengzhan Zhao, Guoping Long +6
We show in this work that memory intensive computations can result in severe performance problems due to off-chip memory access and CPU-GPU context switch overheads in a wide range…