ELFies: Executable Region Checkpoints for Performance Analysis and Simulation
| Autor: | Ali Hajiabadi, Trevor E. Carlson, Alexander Isaev, Harish Patil, Alen Sabu, Wim Heirman |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
010302 applied physics
Focus (computing) business.industry Computer science Reliability (computer networking) 02 engineering and technology computer.file_format 01 natural sciences 020202 computer hardware & architecture Set (abstract data type) Region of interest 0103 physical sciences 0202 electrical engineering electronic engineering information engineering Dynamic program analysis Performance monitoring Executable State (computer science) Software engineering business computer |
| Zdroj: | CGO |
| DOI: | 10.1109/cgo51591.2021.9370340 |
| Popis: | We address the challenge faced in characterizing long-running workloads, namely how to reliably focus the detailed analysis on interesting execution regions. We present a set of tools that allows users to precisely capture any region of interest in program execution, and create a stand-alone executable, called an ELFie, from it. An ELFie starts with the same program state captured at the beginning of the region of interest and then executes natively. With ELFies, there is no fast-forwarding to the region of interest needed or the uncertainty of reaching the region. ELFies can be fed to dynamic program-analysis tools or simulators that work with regular program binaries. Our tool-chain is based on the PinPlay framework and requires no special hardware, operating system changes, recompilation, or re-linking of test programs. This paper describes the design of our ELFie generation tool-chain and the application of ELFies in performance analysis and simulation of regions of interest in popular long-running single and multi-threaded benchmarks. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|