ASFRM: An Array State Self-feedback-Based Self-reconfiguration Mechanism in a Reconfigurable Array Processor.
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| Title: | ASFRM: An Array State Self-feedback-Based Self-reconfiguration Mechanism in a Reconfigurable Array Processor. |
|---|---|
| Authors: | Yang, Kun1 (AUTHOR), Jiang, Lin2 (AUTHOR) jianglin@xust.edu.cn, Deng, Junyong3 (AUTHOR), Shan, Rui3 (AUTHOR), Li, Kangle1 (AUTHOR), Zhang, Xiaofan4 (AUTHOR) |
| Source: | Journal of Circuits, Systems & Computers. 9/30/2025, Vol. 34 Issue 14, p1-29. 29p. |
| Subjects: | Array processors, Legal judgments, Scheduling, Encoding, Hardware |
| Abstract: | With complex tasks in neural network computing, existing reconfiguration methods have a long reconfiguration time and it is not easy to achieve fast task switching. Therefore, this paper presents an array state self-feedback based self-reconfiguration mechanism (ASFRM) to quickly achieve autonomous task switching and dynamic scheduling based on task execution status. This mechanism is based on the array state information autonomously fed back by the reconfigurable array, and the host controller makes autonomous judgments and decisions on the current execution status of the array, achieving dynamic task rearrangement, dynamic scheduling of the array and fast task switching. The proposed ASFRM can switch configurations between different tasks within 6 clock cycles. To verify the correctness and efficiency of ASFRM, we modeled the hardware with synthesizable RTL encoding and implemented it on FPGA and chip. The experimental results show that compared with traditional reconfiguration methods and SIMD-like methods, ASFRM can effectively reduce reconfiguration overhead. The volume of bits in the configuration file has decreased by an average of 11.79% and 4.51%. The reconfiguration time has decreased by an average of 52.79% and 37.12%. Based on the UMC 55 nm process, the operating frequency can reach 400 MHz. Meanwhile, the chip area is 64 mm2 and the throughput is 115.2 GOPS. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Circuits, Systems & Computers is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 186254877 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: ASFRM: An Array State Self-feedback-Based Self-reconfiguration Mechanism in a Reconfigurable Array Processor. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yang%2C+Kun%22">Yang, Kun</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jiang%2C+Lin%22">Jiang, Lin</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> jianglin@xust.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Deng%2C+Junyong%22">Deng, Junyong</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shan%2C+Rui%22">Shan, Rui</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Kangle%22">Li, Kangle</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Xiaofan%22">Zhang, Xiaofan</searchLink><relatesTo>4</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Circuits%2C+Systems+%26+Computers%22">Journal of Circuits, Systems & Computers</searchLink>. 9/30/2025, Vol. 34 Issue 14, p1-29. 29p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Array+processors%22">Array processors</searchLink><br /><searchLink fieldCode="DE" term="%22Legal+judgments%22">Legal judgments</searchLink><br /><searchLink fieldCode="DE" term="%22Scheduling%22">Scheduling</searchLink><br /><searchLink fieldCode="DE" term="%22Encoding%22">Encoding</searchLink><br /><searchLink fieldCode="DE" term="%22Hardware%22">Hardware</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: With complex tasks in neural network computing, existing reconfiguration methods have a long reconfiguration time and it is not easy to achieve fast task switching. Therefore, this paper presents an array state self-feedback based self-reconfiguration mechanism (ASFRM) to quickly achieve autonomous task switching and dynamic scheduling based on task execution status. This mechanism is based on the array state information autonomously fed back by the reconfigurable array, and the host controller makes autonomous judgments and decisions on the current execution status of the array, achieving dynamic task rearrangement, dynamic scheduling of the array and fast task switching. The proposed ASFRM can switch configurations between different tasks within 6 clock cycles. To verify the correctness and efficiency of ASFRM, we modeled the hardware with synthesizable RTL encoding and implemented it on FPGA and chip. The experimental results show that compared with traditional reconfiguration methods and SIMD-like methods, ASFRM can effectively reduce reconfiguration overhead. The volume of bits in the configuration file has decreased by an average of 11.79% and 4.51%. The reconfiguration time has decreased by an average of 52.79% and 37.12%. Based on the UMC 55 nm process, the operating frequency can reach 400 MHz. Meanwhile, the chip area is 64 mm2 and the throughput is 115.2 GOPS. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Circuits, Systems & Computers is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1142/S0218126625503050 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 29 StartPage: 1 Subjects: – SubjectFull: Array processors Type: general – SubjectFull: Legal judgments Type: general – SubjectFull: Scheduling Type: general – SubjectFull: Encoding Type: general – SubjectFull: Hardware Type: general Titles: – TitleFull: ASFRM: An Array State Self-feedback-Based Self-reconfiguration Mechanism in a Reconfigurable Array Processor. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yang, Kun – PersonEntity: Name: NameFull: Jiang, Lin – PersonEntity: Name: NameFull: Deng, Junyong – PersonEntity: Name: NameFull: Shan, Rui – PersonEntity: Name: NameFull: Li, Kangle – PersonEntity: Name: NameFull: Zhang, Xiaofan IsPartOfRelationships: – BibEntity: Dates: – D: 30 M: 09 Text: 9/30/2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 02181266 Numbering: – Type: volume Value: 34 – Type: issue Value: 14 Titles: – TitleFull: Journal of Circuits, Systems & Computers Type: main |
| ResultId | 1 |
