Parallel Shadow Execution to Accelerate the Debugging of Numerical Errors
Wed 25 Aug 2021 21:00 - 21:10 - Testing—Analysis and Testing of Unconventional Software Chair(s): Na Meng
This paper proposes a new approach for debugging errors in floating point computation by performing shadow execution with higher precision in parallel. The programmer specifies parts of the program that need to be debugged for errors. Our compiler creates shadow execution tasks, which execute on different cores and perform the computation with higher precision. We propose a novel method to execute a shadow execution task from an arbitrary memory state, which is necessary because we are creating a parallel shadow execution from a sequential program. Our approach also ensures that the shadow execution follows the same control flow path as the original program. Our runtime automatically distributes the shadow execution tasks to balance the load on the cores. Our prototype for parallel shadow execution, PFPSanitizer, provides comprehensive detection of errors while having lower performance overheads than prior approaches.
Wed 25 AugDisplayed time zone: Athens change
09:00 - 10:00 | Testing—Analysis and Testing of Unconventional SoftwareResearch Papers +12h Chair(s): Gregory Gay Chalmers and the University of Gothenburg | ||
09:00 10mPaper | Parallel Shadow Execution to Accelerate the Debugging of Numerical Errors Research Papers DOI | ||
09:10 10mPaper | Exposing Numerical Bugs in Deep Learning via Gradient Back-Propagation Research Papers Ming Yan Tianjin University, Junjie Chen Tianjin University, Xiangyu Zhang Purdue University, Lin Tan Purdue University, Gan Wang Tianjin University DOI | ||
09:20 10mPaper | Metamorphic Testing of Datalog Engines Research Papers DOI | ||
09:30 30mLive Q&A | Q&A (Testing—Analysis and Testing of Unconventional Software) Research Papers |
21:00 - 22:00 | Testing—Analysis and Testing of Unconventional SoftwareResearch Papers Chair(s): Na Meng Virginia Tech | ||
21:00 10mPaper | Parallel Shadow Execution to Accelerate the Debugging of Numerical Errors Research Papers DOI | ||
21:10 10mPaper | Exposing Numerical Bugs in Deep Learning via Gradient Back-Propagation Research Papers Ming Yan Tianjin University, Junjie Chen Tianjin University, Xiangyu Zhang Purdue University, Lin Tan Purdue University, Gan Wang Tianjin University DOI | ||
21:20 10mPaper | Metamorphic Testing of Datalog Engines Research Papers DOI | ||
21:30 30mLive Q&A | Q&A (Testing—Analysis and Testing of Unconventional Software) Research Papers |