DARKSIDE: A Heterogeneous RISC-V Compute Cluster for Extreme-Edge On-Chip DNN Inference and Training
On-chip deep neural network (DNN) inference and training at the Extreme-Edge (TinyML) impose strict latency, throughput, accuracy, and flexibility requirements. Heterogeneous clusters are promising solutions to meet the challenge, combining the flexibility of DSP-enhanced cores with the performance...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
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| Series: | IEEE Open Journal of the Solid-State Circuits Society |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9903915/ |