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A long short-term memory（LSTM）neural network edge computing accelerator based on distributed systolic array architecture was proposed on the resource limited edge computing devices. The design distributes input data storage to reduce data movement and power consumption, while data transmission in a systolic manner minimizes the idle rate of computing units and enhances computational efficiency. Experimental validation on a VU13P field-programmable gate array（FPGA）shows that the proposed LSTM accelerator achieves an effective computing power of 179.2 GOPS at an operating frequency of 200 MHz, with a dynamic power consumption of 0.343 W and an energy efficiency of 522.4 GOPS/W. Compared with typical existing designs, the proposed accelerator improves energy efficiency by more than 34%.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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