摘要
The calculation principle of non‑positional stochastic number (SN) is a promising technique for realizing high‑performance computing owing to its extremely low hardware cost. This paper introduces detailly the origin, develop-ment process and the domestic and foreign development present situation. However, a disadvantage of stochastic bitstream is that the computing latency, and information‑carrying efficiency and so on. We presented a hybrid stochastic computing (HSC) based on a hybrid bitstream to solve these problems, which achieves a lower hardware cost, better accuracy, and fast-er speed. The HSC neural networks is fabricated by 40 nm low‑power CMOS process, with a core area of 0.73 mm × 0.73 mm, power of 102.3 mW and clock of 400 MHz, which has 4 544 multiply and accumulation (MAC). The proposed Hybrid stochastic computing is tested by FPGA and ASIC. Compared with other stochastic computing method, the method proposed gains 50×, 2.5×,and 3.26× energy efficiency than other methods of traditional stochastic computing.
| 投稿的翻译标题 | Stochastic Computing and Hybrid Stochastic Computing |
|---|---|
| 源语言 | 繁体中文 |
| 页(从-至) | 428-440 |
| 页数 | 13 |
| 期刊 | Tien Tzu Hsueh Pao/Acta Electronica Sinica |
| 卷 | 52 |
| 期 | 2 |
| DOI | |
| 出版状态 | 已出版 - 2月 2024 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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可持续发展目标 7 经济适用的清洁能源
关键词
- computing performance
- deep neural network
- energy efficiency
- hybrid stochastic computing
- hybrid stochastic number
- stochastic computing
- stochastic number
指纹
探究 '概率计算及混合概率计算' 的科研主题。它们共同构成独一无二的指纹。引用此
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