218 citations · 448 across the 18 of their papers we have counts for
18 papers
Towards Seamless Management of AI Models in High-Performance Computing
Sixing Yu, Murali Emani, Chunhua Liao +4
With the increasing prevalence of artificial intelligence (AI) in diverse science/engineering communities, AI models emerge on an unprecedented scale among various domains. However…
Finding Reusable Machine Learning Components to Build Programming Language Processing Pipelines
Patrick Flynn, Tristan Vanderbruggen, Chunhua Liao +3
Programming Language Processing (PLP) using machine learning has made vast improvements in the past few years. Increasingly more people are interested in exploring this promising f…
Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU
Jou-An Chen, Hsin-Hsuan Sung, Xipeng Shen +3
In a general graph data structure like an adjacency matrix, when edges are homogeneous, the connectivity of two nodes can be sufficiently represented using a single bit. This insig…
Coarsening Optimization for Differentiable Programming
Xipeng Shen, Guoqiang Zhang, Irene Dea +10
This paper presents a novel optimization for differentiable programming named coarsening optimization. It offers a systematic way to synergize symbolic differentiation and algorith…
G-TADOC: Enabling Efficient GPU-Based Text Analytics without Decompression
Feng Zhang, Zaifeng Pan, Yanliang Zhou +4
Text analytics directly on compression (TADOC) has proven to be a promising technology for big data analytics. GPUs are extremely popular accelerators for data analytics systems. U…
Toward Efficient Interactions between Python and Native Libraries
Jialiang Tan, Yu Chen, Zhenming Liu +4
Python has become a popular programming language because of its excellent programmability. Many modern software packages utilize Python for high-level algorithm design and depend o…
Faster SAT Solving for Software with Repeated Structures (with Case Studies on Software Test Suite Minimization)
Jianfeng Chen, Xipeng Shen, Tim Menzies
Theorem provers has been used extensively in software engineering for software testing or verification. However, software is now so large and complex that additional architecture i…
Achieving Real-Time LiDAR 3D Object Detection on a Mobile Device
Pu Zhao, Wei Niu, Geng Yuan +7
3D object detection is an important task, especially in the autonomous driving application domain. However, it is challenging to support the real-time performance with the limited…
TADOC: Text Analytics Directly on Compression
Feng Zhang, Jidong Zhai, Xipeng Shen +5
This article provides a comprehensive description of Text Analytics Directly on Compression (TADOC), which enables direct document analytics on compressed textual data. The article…
Simpler Hyperparameter Optimization for Software Analytics: Why, How, When?
Amritanshu Agrawal, Xueqi Yang, Rishabh Agrawal +2
How to make software analytics simpler and faster? One method is to match the complexity of analysis to the intrinsic complexity of the data being explored. For example, hyperparam…
RT3D: Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices
Wei Niu, Mengshu Sun, Zhengang Li +7
Mobile devices are becoming an important carrier for deep learning tasks, as they are being equipped with powerful, high-end mobile CPUs and GPUs. However, it is still a challengin…
CoCoPIE: Making Mobile AI Sweet As PIE --Compression-Compilation Co-Design Goes a Long Way
Shaoshan Liu, Bin Ren, Xipeng Shen +1
Assuming hardware is the major constraint for enabling real-time mobile intelligence, the industry has mainly dedicated their efforts to developing specialized hardware accelerator…
MKPipe: A Compiler Framework for Optimizing Multi-Kernel Workloads in OpenCL for FPGA
Ji Liu, Abdullah-Al Kafi, Xipeng Shen +1
OpenCL for FPGA enables developers to design FPGAs using a programming model similar for processors. Recent works have shown that code optimization at the OpenCL level is important…
In-Place Zero-Space Memory Protection for CNN
Hui Guan, Lin Ning, Zhen Lin +3
Convolutional Neural Networks (CNN) are being actively explored for safety-critical applications such as autonomous vehicles and aerospace, where it is essential to ensure the reli…
How to "DODGE" Complex Software Analytics?
Amritanshu Agrawal, Wei Fu, Di Chen +2
Machine learning techniques applied to software engineering tasks can be improved by hyperparameter optimization, i.e., automatic tools that find good settings for a learner's cont…
Hyperparameter Optimization for Effort Estimation
Tianpei Xia, Rahul Krishna, Jianfeng Chen +3
Software analytics has been widely used in software engineering for many tasks such as generating effort estimates for software projects. One of the "black arts" of software analyt…
Why Software Effort Estimation Needs SBSE
Tianpei Xia, Jianfeng Chen, George Mathew +2
Industrial practitioners now face a bewildering array of possible configurations for effort estimation. How to select the best one for a particular dataset? This paper introduces O…
Tuning for Software Analytics: is it Really Necessary?
Wei Fu, Tim Menzies, Xipeng Shen
Context: Data miners have been widely used in software engineering to, say, generate defect predictors from static code measures. Such static code defect predictors perform well co…