PLDI 2024
Mon 24 - Fri 28 June 2024 Copenhagen, Denmark
Mon 24 Jun 2024 11:50 - 12:05 at Iceland - Optimization Chair(s): Aviral Shrivastava

Function merging is a pivotal technique for reducing code size by combining identical or similar functions into a single function. While prior research has extensively explored this technique, it has not been assessed in conjunction with function outlining and linker’s identical code folding, despite substantial common ground. The traditional approaches necessitate the complete intermediate representation to compare functions. Consequently, none of these approaches offer a scalable solution compatible with separate compilations while achieving global function merging, which is critical for large app development. In this paper, we introduce our global function merger, leveraging global merge information from previous code generation runs to optimistically create merging instances within each module context independently. Notably, our approach remains sound even when intermediate representations change, making it well-suited for distributed build environments. We present a comprehensive code generation framework that can seamlessly operate both the state-of-the-art global function outliner and our global function merger. These components work in harmony with each other. Our assessment shows that this approach can lead to a 3.5% reduction in code size and a 9% decrease in build time.

Mon 24 Jun

Displayed time zone: Windhoek change

10:40 - 12:20
OptimizationLCTES at Iceland
Chair(s): Aviral Shrivastava Arizona State University
10:40
15m
Talk
Accelerating Shared Library Execution in a DBT
LCTES
Tom Spink University of St Andrews, Björn Franke University of Edinburgh
10:55
15m
Talk
Efficient Implementation of Neural Networks Usual Layers on Fixed-Point Architectures
LCTES
Dorra Ben Khalifa University of Toulouse - ENAC, Matthieu Martel Université de Perpignan Via Domitia
11:10
15m
Talk
TinySeg: Model Optimizing Framework for Image Segmentation on Tiny Embedded Systems
LCTES
Byungchul Chae Kyung Hee University, Jiae Kim Kyung Hee University, Seonyeong Heo Kyung Hee University
11:25
10m
Break
Break - 10 minutes
LCTES

11:35
15m
Talk
MixPert: Optimizing Mixed-Precision Floating-Point Emulation on GPU Integer Tensor Cores
LCTES
Zejia Lin Sun Yat-sen University, Aoyuan Sun Sun Yat-sen University, Xianwei Zhang Sun Yat-sen University, Yutong Lu Sun Yat-sen University
11:50
15m
Talk
Optimistic and Scalable Global Function Merging
LCTES
12:05
15m
Talk
(Invited paper) Language-Based Deployment Optimization for Random Forest
LCTES
Jannik Malcher TU Dortmund University, Daniel Biebert TU Dortmund University, Kuan-Hsun Chen University of Twente, Sebastian Buschjäger TU Dortmund University, Christian Hakert TU Dortmund University, Jian-Jia Chen TU Dortmund University