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.
Authors
- Shunfen Li (ORCID: https://orcid.org/0000-0002-2464-1414)
- Houpeng Chen (ORCID: https://orcid.org/0000-0002-5766-5746)
- Sannian Song (ORCID: https://orcid.org/0000-0001-7186-4744)
- Weibang Dai (ORCID: https://orcid.org/0009-0009-3585-8561)
- Zhitang Song (ORCID: https://orcid.org/0000-0001-7859-9429)
- Tao Hong (ORCID: https://orcid.org/0009-0005-8648-8266)
- Xiaogang Chen (ORCID: https://orcid.org/0000-0003-1478-040X)
Institutions
- Shanghai Institute of Microsystem and Information Technology (CN)
- University of Chinese Academy of Sciences (CN)
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