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- LI Yixiao
- Graduate School of Informatics, Nagoya University
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- MATSUBARA Yutaka
- Graduate School of Informatics, Nagoya University
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- TAKADA Hiroaki
- Graduate School of Informatics, Nagoya University
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Abstract
<p>Embedded systems are moving to multi-core and many-core platforms to satisfy the ever-growing demand for computing power. Complex task like autonomous driving will include both real-time applications and high-performance applications. Research has shown that traditional RTOS can be optimized to provide good scalability for parallel computing. The lack of performance analysis tools, however, is one of the major obstacles for identifying bottlenecks.<br/>In this paper, we first discuss the characteristics and challenges of existing tools used in high-performance computing. To meet the requirements of embedded systems, a generic infrastructure for creating customized profilers flexibly and effortlessly is then presented. As an example, a scalable and optimized call graph profiler has been developed. At last, we evaluate our profiler and existing profiler by measuring benchmark application on a 36-core platform. The results show that our profiler can provide much higher accuracy with very low overhead.</p>
Journal
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- Computer Software
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Computer Software 37 (1), 1_54-1_67, 2020-01-24
Japan Society for Software Science and Technology
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Details 詳細情報について
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- CRID
- 1390565134838768640
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- NII Article ID
- 130007815022
- 40022162055
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- NII Book ID
- AN10075819
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- NDL BIB ID
- 030263860
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- ISSN
- 02896540
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- Text Lang
- ja
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- Data Source
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- JaLC
- NDL
- CiNii Articles
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- Abstract License Flag
- Disallowed