TY - JOUR
T1 - A Hardware/Software Co-design Methodology for In-memory Processors
AU - Yantir, Hasan Erdem
AU - Eltawil, Ahmed
AU - Salama, Khaled N.
N1 - KAUST Repository Item: Exported on 2021-11-13
Acknowledgements: We acknowledge the financial support from AI Initiative, King Abdullah University of Science and Technology (KAUST), Saudi Arabia.
PY - 2021/11
Y1 - 2021/11
N2 - The bottleneck between the processor and memory is the most significant barrier to the ongoing development of efficient processing systems. Therefore, a research effort begun to shift from processor-centric architectures to memory-centric architectures. Various in-memory processor architectures have been proposed to break this barrier to pave the way for ever-demanding memory-bound applications. Associative in-memory processing is a successful candidate for truly in-memory computing, in which processor and memory are combined in the same location to eliminate the expensive data access costs. The architecture exhibits an unmatched advantage for data-intensive applications due to its memory-centric design principles. On the other hand, this advantage can be revealed fully by an efficient design methodology. This study puts further progressive effort by proposing a hardware/software design methodology for associative in-memory processors. The methodology aims to decrease energy consumption and area requirement of the processor architecture specifically programmed to perform a given task. According to the evaluation of nine different benchmarks, such as fast Fourier transform and multiply-accumulate, the proposed design flow accomplishes an average 7% reduction in memory area and 18% savings in total energy consumption.
AB - The bottleneck between the processor and memory is the most significant barrier to the ongoing development of efficient processing systems. Therefore, a research effort begun to shift from processor-centric architectures to memory-centric architectures. Various in-memory processor architectures have been proposed to break this barrier to pave the way for ever-demanding memory-bound applications. Associative in-memory processing is a successful candidate for truly in-memory computing, in which processor and memory are combined in the same location to eliminate the expensive data access costs. The architecture exhibits an unmatched advantage for data-intensive applications due to its memory-centric design principles. On the other hand, this advantage can be revealed fully by an efficient design methodology. This study puts further progressive effort by proposing a hardware/software design methodology for associative in-memory processors. The methodology aims to decrease energy consumption and area requirement of the processor architecture specifically programmed to perform a given task. According to the evaluation of nine different benchmarks, such as fast Fourier transform and multiply-accumulate, the proposed design flow accomplishes an average 7% reduction in memory area and 18% savings in total energy consumption.
UR - http://hdl.handle.net/10754/673326
UR - https://linkinghub.elsevier.com/retrieve/pii/S0743731521002070
U2 - 10.1016/j.jpdc.2021.10.009
DO - 10.1016/j.jpdc.2021.10.009
M3 - Article
SN - 0743-7315
JO - Journal of Parallel and Distributed Computing
JF - Journal of Parallel and Distributed Computing
ER -