An Integrated Temporal Partitioning and Mapping Framework for Improving Performance of a Reconfigurable Instruction Set Processor
الموضوعات : Journal of Computer & Robotics
Farhad Mehdipour
1
(Faculty of Information Science and Electrical Engineering, Department of Informatics, Kyushu University, Fukuoka, Japan)
Hamid Noori
2
(School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran)
Morteza Saheb Zamani
3
(Department of Computer Engineering and IT, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran)
Hiroaki Honda
4
(Institute of Systems, Information Technologies and Nanotechnologies, Fukuoka, Japan)
Koji Inoue
5
(Faculty of Information Science and Electrical Engineering, Department of Informatics, Kyushu University, Fukuoka, Japan)
Kazuaki Murakami
6
(Faculty of Information Science and Electrical Engineering, Department of Informatics, Kyushu University, Fukuoka, Japan)
الکلمات المفتاحية: Reconfigurable instruction set processor, Custom instruction, Reconfigurable functional unit, Temporal partitioning,
ملخص المقالة :
Reconfigurable instruction set processors allow customization for an application domain by extending the core instruction set architecture. Extracting appropriate custom instructions is an important phase for implementing an application on a reconfigurable instruction set processor. A custom instruction (CI) is usually extracted from critical portions of applications and implemented on a reconfigurable functional unit. In this paper, our proposed RFU architecture for a reconfigurable instruction set processor is introduced. As the main contribution of this work, an integrated framework of temporal partitioning and mapping is introduced that partitions and maps CIs on the RFU. Temporal partitioning iterates and modifies partitions incrementally to generate CIs. The proposed framework improves the timing performance particularly for the applications comprising a considerable amount of CIs that could not be implemented on the RFU due to architectural limitations. Furthermore, exploiting similarity detection and merging as two complementary techniques for the integrated framework brings about reduction in the configuration memory size.
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