Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

John Lu

dblp:79/5253 · DBLP profile ↗
← Back
3ranked-venue papers
1as first author
1since 2021 · last 2024
0009-0001-1789-7569ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 since 2021Software engineering, systems software and programming languages · 1Databases, data management, data science and information retrieval · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Data mining · 50% Web and social media mining · 50%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 100%
Software engineering, system software, and programming languages
1 paper
Compilers and program optimization · 67% Program analysis · 33%

Topics — the 5 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Web and social media mining › social media analysis
social media text analysis
0.412019
Investigate Transitions into Drug Addiction through Text Mining of Reddit Data · KDD 2019
Data mining
text mining
0.412019
Investigate Transitions into Drug Addiction through Text Mining of Reddit Data · KDD 2019
Program analysis › static analysis
pointer analysis
0.011997
Register Promotion in C Programs · PLDI 1997
Compilers and program optimization
register allocation
0.011997
Register Promotion in C Programs · PLDI 1997
Compilers and program optimization › register allocation
register promotion
0.011997
Register Promotion in C Programs · PLDI 1997

Methods — techniques the papers use, named apart from their topics

linguistic feature analysis · 0.8cox regression · 0.8binary classification · 0.8static analysis · 0.0experimental evaluation · 0.0
YearPublicationVenuePosition
2024 CuPBoP: Making CUDA a Portable Language
abstract
CUDA is designed specifically for NVIDIA GPUs and is not compatible with non-NVIDIA devices. Enabling CUDA execution on alternative backends could greatly benefit the hardware community by fostering a more diverse software ecosystem. To address the need for portability, our objective is to develop a framework that meets key requirements, such as extensive coverage, comprehensive end-to-end support, superior performance, and hardware scalability. Existing solutions that translate CUDA source code into other high-level languages, however, fall short of these goals. In contrast to these source-to-source approaches, we present a novel framework, CuPBoP , which treats CUDA as a portable language in its own right. Compared to two commercial source-to-source solutions, CuPBoP offers a broader coverage and superior performance for the CUDA-to-CPU migration. Additionally, we evaluate the performance of CuPBoP against manually optimized CPU programs, highlighting the differences between CPU programs derived from CUDA and those that are manually optimized. Furthermore, we demonstrate the hardware scalability of CuPBoP by showcasing its successful migration of CUDA to AMD GPUs. To promote further research in this field, we have released CuPBoP as an open-source resource.
Ruobing Han, Jun Chen 0038, Bhanu Garg, Xule Zhou, John Lu, Jeffrey Young 0001, Jaewoong Sim, Hyesoon Kim
ACM Trans. Design Autom. Electr. Syst.5
2019 Investigate Transitions into Drug Addiction through Text Mining of Reddit Data
abstract
Increasing rates of opioid drug abuse and heightened prevalence of online support communities underscore the necessity of employing data mining techniques to better understand drug addiction using these rapidly developing online resources. In this work, we obtained data from Reddit, an online collection of forums, to gather insight into drug use/misuse using text snippets from users narratives. Specifically, using users' posts, we trained a binary classifier which predicts a user's transitions from casual drug discussion forums to drug recovery forums. We also proposed a Cox regression model that outputs likelihoods of such transitions. In doing so, we found that utterances of select drugs and certain linguistic features contained in one's posts can help predict these transitions. Using unfiltered drug-related posts, our research delineates drugs that are associated with higher rates of transitions from recreational drug discussion to support/recovery discussion, offers insight into modern drug culture, and provides tools with potential applications in combating the opioid crisis.
John Lu, Sumati Sridhar, Ritika Pandey, Mohammad Al Hasan, George O. Mohler
KDD1
1997 Register Promotion in C Programs
abstract
The combination of pointers and pointer arithmetic in C makes the task of improving C programs somewhat more difficult than improving programs written in simpler languages like Fortran. While much work has been published that focuses on the analysis of pointers, little has appeared that uses the results of such analysis to improve the code compiled for C. This paper examines the problem of register promotion in C and presents experimental results showing that it can have dramatic effects on memory traffic.
Keith D. Cooper, John Lu
PLDI2