Name
Title | ||
|---|---|---|
ADROIT: An Adaptive Dynamic Refresh Optimization Framework for DRAM Energy Saving In DNN Training |
Abstract | ||
|---|---|---|
To achieve high accuracy, DNN training usually consumes and generates myriads of data, which requires a large DRAM for efficient processing. The refresh power consumption in large DRAM has become a severe problem. Previous refresh energy saving methods have drawbacks on usability, flexibility or training supporting. We propose ADROIT, an adaptive dynamic refresh optimization framework for various DNNs and processing platforms. ADROIT dynamically adjusts the refresh rates for different types of data according to runtime loss feedback in DNN training. Data idle time, lifetime and size are taken into consideration to reduce the search space of refresh rate and remove most refresh operations. Experimental results show that ADROIT can reduce the refresh energy and total DRAM energy in DNN training by up to 98.9% and 24.7% respectively, while maintaining the accuracy. Moreover, ADROIT can automatically apply to different DNNs and hardware platforms without tedious manual configuration. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/DAC18074.2021.9586265 | 2021 58TH ACM/IEEE DESIGN AUTOMATION CONFERENCE (DAC) |
Keywords | DocType | ISSN |
DNN Training, Energy Efficiency, Refresh Optimization, Approximate DRAM, Dynamic Optimization | Conference | 0738-100X |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinhan Lin | 1 | 11 | 2.62 |
| Liang Sun | 2 | 0 | 0.34 |
| Fengbin Tu | 3 | 71 | 8.62 |
| leibo liu | 4 | 816 | 116.95 |
| Xiangyu Li | 5 | 27 | 10.25 |
| Shaojun Wei | 6 | 555 | 102.32 |
| shouyi yin | 7 | 579 | 99.95 |