Wed 23 Oct 2024 16:40 - 17:00 at IBR West - Performance Analysis and Optimisation 2 Chair(s): Matthew Flatt

Programs written in C/C++ often include inline assembly: a snippet of architecture-specific assembly code used to access low-level functionalities that are impossible or expensive to simulate in the source language. Although inline assembly is widely used, its semantics has not yet been formally studied.

In this paper, we overcome this deficiency by investigating the effect of inline assembly to the consistency semantics of C/C++ programs. We propose the first memory model of the C++ Programming Language with support for inline assembly for Intel’s x86 including non-temporal stores and store fences. We argue that previous provably correct compiler optimizations and correct compiler mappings should remain correct under such an extended model and we prove that this requirement is met by our proposed model.

Wed 23 Oct

Displayed time zone: Pacific Time (US & Canada) change

16:00 - 17:40
Performance Analysis and Optimisation 2OOPSLA 2024 at IBR West
Chair(s): Matthew Flatt University of Utah
16:00
20m
Talk
Jmvx: Fast Multi-threaded Multi-Version eXecution and Record-Replay for Managed Languages
OOPSLA 2024
David Schwartz University of Illinois at Chicago, Ankith Kowshik University of Illinois Chicago, Luís Pina University of Illinois at Chicago
DOI
16:20
20m
Talk
libLISA: Instruction Discovery and Analysis on x86-64
OOPSLA 2024
Jos Craaijo Open Universiteit, Freek Verbeek Open Universiteit & Virginia Tech, Binoy Ravindran Virginia Tech
DOI
16:40
20m
Talk
Extending the C/C++ Memory Model with Inline Assembly
OOPSLA 2024
Paulo Emílio de Vilhena Imperial College London, Ori Lahav Tel Aviv University, Viktor Vafeiadis MPI-SWS, Azalea Raad Imperial College London
DOI
17:00
20m
Talk
TorchQL: A Programming Framework for Integrity Constraints in Machine Learning
OOPSLA 2024
Aaditya Naik University of Pennsylvania, Adam Stein University of Pennsylvania, Yinjun Wu University of Pennsylvania, Mayur Naik University of Pennsylvania, Eric Wong
DOI
17:20
20m
Talk
Verification of Neural Networks' Global RobustnessRemote
OOPSLA 2024
Anan Kabaha Technion, Israel Institute of Technology, Dana Drachsler Cohen Technion
DOI