Thread and Data Mapping in Software Transactional Memory: An Overview
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2022
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| _version_ | 1866916658356944896 |
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| author | Pasqualin, Douglas Pereira Diener, Matthias Bois, André Rauber Du Pilla, Maurício Lima |
| author_facet | Pasqualin, Douglas Pereira Diener, Matthias Bois, André Rauber Du Pilla, Maurício Lima |
| contents | In current microarchitectures, due to the complex memory hierarchies and different latencies on memory accesses, thread and data mapping are important issues to improve application performance. Software transactional memory (STM) is an abstraction used for thread synchronization, replacing the use of locks in parallel programming. Regarding thread and data mapping, STM presents new challenges and mapping opportunities, since (1) STM can use different conflict detection and resolution strategies, making the behavior of the application less predictable and; (2) the STM runtime has precise information about shared data and the intensity with each thread accesses them. These unique characteristics provide many opportunities for low-overhead, but precise statistics to guide mapping strategies for STM applications. The main objective of this paper is to survey the existing work about thread and data mapping that uses solely information gathered from the STM runtime to guide thread and data mapping decisions. We also discuss future research directions within this research area. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2206_01359 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Thread and Data Mapping in Software Transactional Memory: An Overview Pasqualin, Douglas Pereira Diener, Matthias Bois, André Rauber Du Pilla, Maurício Lima Distributed, Parallel, and Cluster Computing In current microarchitectures, due to the complex memory hierarchies and different latencies on memory accesses, thread and data mapping are important issues to improve application performance. Software transactional memory (STM) is an abstraction used for thread synchronization, replacing the use of locks in parallel programming. Regarding thread and data mapping, STM presents new challenges and mapping opportunities, since (1) STM can use different conflict detection and resolution strategies, making the behavior of the application less predictable and; (2) the STM runtime has precise information about shared data and the intensity with each thread accesses them. These unique characteristics provide many opportunities for low-overhead, but precise statistics to guide mapping strategies for STM applications. The main objective of this paper is to survey the existing work about thread and data mapping that uses solely information gathered from the STM runtime to guide thread and data mapping decisions. We also discuss future research directions within this research area. |
| title | Thread and Data Mapping in Software Transactional Memory: An Overview |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2206.01359 |