Data Partitioning and Asynchronous Processing to Improve the Embedded Software Performance on Multicore Processors
Nowadays, ensuring information security is extremely inevitable and urgent. We are also witnessing the strong development of embedded systems, IoT. As a result, research to ensure information security for embedded software is being focused. However, studies on optimizing embedded software on multi-c...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Russian Academy of Sciences, St. Petersburg Federal Research Center
2022-03-01
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| Series: | Информатика и автоматизация |
| Subjects: | |
| Online Access: | http://ia.spcras.ru/index.php/sp/article/view/15084 |
| _version_ | 1797695312900390912 |
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| author | Phuc Bui Minh Le Binh Hoang Nguyen Ngoc Huong Pham |
| author_facet | Phuc Bui Minh Le Binh Hoang Nguyen Ngoc Huong Pham |
| author_sort | Phuc Bui |
| collection | DOAJ |
| description | Nowadays, ensuring information security is extremely inevitable and urgent. We are also witnessing the strong development of embedded systems, IoT. As a result, research to ensure information security for embedded software is being focused. However, studies on optimizing embedded software on multi-core processors to ensure information security and increase the performance of embedded software have not received much attention. The paper proposes and develops the embedded software performance improvement method on multi-core processors based on data partitioning and asynchronous processing. Data are used globally to be retrieved by any threads. The data are divided into different partitions, and the program is also installed according to the multi-threaded model. Each thread handles a partition of the divided data. The size of each data portion is proportional to the processing speed and the cache size of the core in the multi-core processor. Threads run in parallel and do not need synchronization, but it is necessary to share a general global variable to check the executing status of the system. Our research on embedded software is based on data security, so we have tested and assessed the method with several block ciphers like AES, DES, etc., on Raspberry PI3. The average performance improvement rate achieved was 59.09%. |
| first_indexed | 2024-03-12T03:10:36Z |
| format | Article |
| id | doaj.art-c67946992e49424588d7e6eec8b17b66 |
| institution | Directory Open Access Journal |
| issn | 2713-3192 2713-3206 |
| language | English |
| last_indexed | 2024-03-12T03:10:36Z |
| publishDate | 2022-03-01 |
| publisher | Russian Academy of Sciences, St. Petersburg Federal Research Center |
| record_format | Article |
| series | Информатика и автоматизация |
| spelling | doaj.art-c67946992e49424588d7e6eec8b17b662023-09-03T14:27:46ZengRussian Academy of Sciences, St. Petersburg Federal Research CenterИнформатика и автоматизация2713-31922713-32062022-03-0121224327410.15622/ia.21.2.215084Data Partitioning and Asynchronous Processing to Improve the Embedded Software Performance on Multicore ProcessorsPhuc Bui0Minh Le1Binh Hoang2Nguyen Ngoc3Huong Pham4Vietnam National UniversityInformation Technology Institute – Vietnam National UniversityTechnological Application and Production One Member Limited Liability companyKyoto College of Graduate Studies for Informatics (KCGI)Academy of CryptographyNowadays, ensuring information security is extremely inevitable and urgent. We are also witnessing the strong development of embedded systems, IoT. As a result, research to ensure information security for embedded software is being focused. However, studies on optimizing embedded software on multi-core processors to ensure information security and increase the performance of embedded software have not received much attention. The paper proposes and develops the embedded software performance improvement method on multi-core processors based on data partitioning and asynchronous processing. Data are used globally to be retrieved by any threads. The data are divided into different partitions, and the program is also installed according to the multi-threaded model. Each thread handles a partition of the divided data. The size of each data portion is proportional to the processing speed and the cache size of the core in the multi-core processor. Threads run in parallel and do not need synchronization, but it is necessary to share a general global variable to check the executing status of the system. Our research on embedded software is based on data security, so we have tested and assessed the method with several block ciphers like AES, DES, etc., on Raspberry PI3. The average performance improvement rate achieved was 59.09%.http://ia.spcras.ru/index.php/sp/article/view/15084embedded software performance improvementmulticore processorsmultithreaddata partitioningasynchronous processing |
| spellingShingle | Phuc Bui Minh Le Binh Hoang Nguyen Ngoc Huong Pham Data Partitioning and Asynchronous Processing to Improve the Embedded Software Performance on Multicore Processors Информатика и автоматизация embedded software performance improvement multicore processors multithread data partitioning asynchronous processing |
| title | Data Partitioning and Asynchronous Processing to Improve the Embedded Software Performance on Multicore Processors |
| title_full | Data Partitioning and Asynchronous Processing to Improve the Embedded Software Performance on Multicore Processors |
| title_fullStr | Data Partitioning and Asynchronous Processing to Improve the Embedded Software Performance on Multicore Processors |
| title_full_unstemmed | Data Partitioning and Asynchronous Processing to Improve the Embedded Software Performance on Multicore Processors |
| title_short | Data Partitioning and Asynchronous Processing to Improve the Embedded Software Performance on Multicore Processors |
| title_sort | data partitioning and asynchronous processing to improve the embedded software performance on multicore processors |
| topic | embedded software performance improvement multicore processors multithread data partitioning asynchronous processing |
| url | http://ia.spcras.ru/index.php/sp/article/view/15084 |
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