LLVM Static Analysis for Program Characterization and Memory Reuse Profile Estimation
Author:
Affiliation:
1. New Mexico State University, USA and Intel Corporation, USA
2. Los Alamos National Laboratory, USA
3. New Mexico State University, USA
4. New Mexico State University, USA and Los Alamos National Laboratory, USA
Funder
Los Alamos National Laboratory is managed by Triad National Security, LLC, for the National Nuclear Security Administration of the U.S. DOE under contract 89233218CNA000001.
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3631882.3631885
Reference20 articles.
1. Atanu Barai. 2022. Scalable Performance Prediction of Parallel Applications on Multicore Processors Using Analytical Reuse Distance Modeling. Ph. D. Dissertation. New Mexico State University.
2. PPT-SASMM: Scalable Analytical Shared Memory Model
3. Antonia Bertolino. 2007. Software Testing Research: Achievements Challenges Dreams. In Future of Software Engineering (FOSE ’07). 85–103. https://doi.org/10.1109/FOSE.2007.25
4. Refactoring for Data Locality
5. William R. Bush Jonathan D. Pincus and David J. Sielaff. [n. d.]. A static analyzer for finding dynamic programming errors. Software: Practice and Experience 30 7 ([n. d.]) 775–802.
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