Alleria
| Autor: | Preeti Ranjan Panda, Hadi Brais |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
010302 applied physics
Profiling (computer programming) business.industry Computer science 02 engineering and technology 01 natural sciences Execution time 020202 computer hardware & architecture Instructions per second Memory address Hardware and Architecture Overhead (business) Embedded system 0103 physical sciences 0202 electrical engineering electronic engineering information engineering business Software |
| Zdroj: | ACM Transactions on Embedded Computing Systems. 18:1-22 |
| ISSN: | 1558-3465 1539-9087 |
| DOI: | 10.1145/3358193 |
| Popis: | Application analysis and simulation tools are used extensively by embedded system designers to improve existing optimization techniques or develop new ones. We propose the Alleria framework to make it easier for designers to comprehensively collect critical information such as virtual and physical memory addresses, accessed values, and thread schedules about one or more target applications. Such profilers often incur substantial performance overheads that are orders of magnitude larger than native execution time. We discuss how that overhead can be significantly reduced using a novel profiling mechanism called adaptive profiling. We develop a heuristic-based adaptive profiling mechanism and evaluate its performance using single-threaded and multi-threaded applications. The proposed technique can improve profiling throughput by up to 145% and by 37% on an average, enabling Alleria to be used to comprehensively profile applications with a throughput of over 3 million instructions per second. |
| Databáze: | OpenAIRE |
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