cfaed Publications
SHERLOCK: Scheduling Efficient and Reliable Bulk Bitwise Operations in NVMs
Reference
Hamid Farzaneh, João Paulo Cardoso De Lima, Ali Nezhadi Khelejani, Asif Ali Khan, Mahta Mayahinia, Mehdi Tahoori, Jeronimo Castrillon, "SHERLOCK: Scheduling Efficient and Reliable Bulk Bitwise Operations in NVMs", Proceedings of the 61th ACM/IEEE Design Automation Conference (DAC'24), Association for Computing Machinery, New York, NY, USA, Jun 2024. [doi]
Abstract
Bulk bitwise operations are commonplace in application domains such as databases, web search, cryptography, and image processing. The ever-growing volume of data and processing demands of these domains often result in high energy consumption and latency in conventional system architectures, mainly due to data movement between the processing and memory subsystems. Non-volatile memories (NVMs), such as RRAM, PCM and STT-MRAM, facilitate conducting bulk-bitwise logic operations in-memory (CIM). Efficient mapping of complex applications to these CIM-capable NVMs is non-trivial and can even lead to slowdowns. This paper presents Sherlock, a novel mapping and scheduling method for efficient execution of bulk bitwise operations in NVMs. Sherlock collaboratively optimizes for performance and energy consumption and outperforms the state-of-the-art by 10\texttimes and 4.6\texttimes, respectively.
Bibtex
author = {Hamid Farzaneh and Jo{\~a}o Paulo Cardoso De Lima and Ali Nezhadi Khelejani and Asif Ali Khan and Mahta Mayahinia and Mehdi Tahoori and Jeronimo Castrillon},
booktitle = {Proceedings of the 61th ACM/IEEE Design Automation Conference (DAC'24)},
title = {{SHERLOCK}: Scheduling Efficient and Reliable Bulk Bitwise Operations in {NVMs}},
location = {San Francisco, California},
series = {DAC '24},
month = jun,
year = {2024},
isbn = {9798400706011},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3649329.3658485},
doi = {10.1145/3649329.3658485},
abstract = {Bulk bitwise operations are commonplace in application domains such as databases, web search, cryptography, and image processing. The ever-growing volume of data and processing demands of these domains often result in high energy consumption and latency in conventional system architectures, mainly due to data movement between the processing and memory subsystems. Non-volatile memories (NVMs), such as RRAM, PCM and STT-MRAM, facilitate conducting bulk-bitwise logic operations in-memory (CIM). Efficient mapping of complex applications to these CIM-capable NVMs is non-trivial and can even lead to slowdowns. This paper presents Sherlock, a novel mapping and scheduling method for efficient execution of bulk bitwise operations in NVMs. Sherlock collaboratively optimizes for performance and energy consumption and outperforms the state-of-the-art by 10\texttimes{} and 4.6\texttimes{}, respectively.},
articleno = {293},
numpages = {6},
}
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2406_Farzaneh_DAC [PDF]
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