Lookup Table-based Computing: A Survey from Software Implementations to Hardware Architectures

For decades, memory-based computation has been overshadowed by processor-centric paradigms. However, memory-based computation offers distinct advantages, including high-speed operation and energy efficiency. As a representative and powerful type of memory-based computation, lookup table (LUT)-based computing has seen a resurgence in interest. Recent advancements in memory technologies, particularly cost reduction in memories and the rise of emerging non-volatile memories (NVMs), have spurred widespread adoption of LUT-based approaches. In this article, we first trace the historical evolution of LUT-based computation, then systematically analyze its modern applications across two domains: (1) software implementations, including LUT-based function evaluation and LUT-based neural networks; and (2) hardware architectures, such as LUT in FPGA and LUT-based processing-in-memory (PIM) systems. Finally, we discuss how NVMs could unlock new opportunities for next-generation LUT-based computing.

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Publication Details

Journal
ACM Computing Surveys
Published
2025-12-06
DOI
https://doi.org/10.1145/3779417
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Lookup Table-based Computing: A Survey from Software Implementations to Hardware Architectures

Shunfen Li, Houpeng Chen, Sannian Song, Weibang Dai et al.
ACM Computing Surveys
Parallel Computing and Optimization Techniques
article

Lookup Table-based Computing: A Survey from Software Implementations to Hardware Architectures

Shunfen Li, Houpeng Chen, Sannian Song, Weibang Dai, Zhitang Song, Tao Hong, Xiaogang Chen
article en

Abstract

For decades, memory-based computation has been overshadowed by processor-centric paradigms. However, memory-based computation offers distinct advantages, including high-speed operation and energy efficiency. As a representative and powerful type of memory-based computation, lookup table (LUT)-based computing has seen a resurgence in interest. Recent advancements in memory technologies, particularly cost reduction in memories and the rise of emerging non-volatile memories (NVMs), have spurred widespread adoption of LUT-based approaches. In this article, we first trace the historical evolution of LUT-based computation, then systematically analyze its modern applications across two domains: (1) software implementations, including LUT-based function evaluation and LUT-based neural networks; and (2) hardware architectures, such as LUT in FPGA and LUT-based processing-in-memory (PIM) systems. Finally, we discuss how NVMs could unlock new opportunities for next-generation LUT-based computing.

ACM Computing SurveysVol. 58(7)
Shanghai Institute of Microsystem and Information Technology (CN), University of Chinese Academy of Sciences (CN)
Openalex Percentile: Top 57%
Parallel Computing and Optimization Techniques
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