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Florian Freye
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2020 – today
- 2024
- [j1]Jie Lou
, Florian Freye
, Christian Lanius
, Tobias Gemmeke
:
An Energy Efficient All-Digital Time-Domain Compute-in-Memory Macro Optimized for Binary Neural Networks. IEEE Trans. Circuits Syst. I Regul. Pap. 71(1): 287-298 (2024) - [c6]Florian Freye, Jie Lou, Christian Lanius, Tobias Gemmeke:
Merits of Time-Domain Computing for VMM - A Quantitative Comparison. ISQED 2024: 1-8 - [i1]Florian Freye, Jie Lou, Christian Lanius, Tobias Gemmeke:
Merits of Time-Domain Computing for VMM - A Quantitative Comparison. CoRR abs/2403.18367 (2024) - 2023
- [c5]Jie Lou
, Florian Freye
, Christian Lanius
, Tobias Gemmeke
:
Scalable Time-Domain Compute-in-Memory BNN Engine with 2.06 POPS/W Energy Efficiency for Edge-AI Devices. ACM Great Lakes Symposium on VLSI 2023: 665-670 - [c4]Christian Lanius, Florian Freye, Shutao Zhang, Tobias Gemmeke:
Hardware Trojans in fdSOI. ISLPED 2023: 1-6 - [c3]Yi Chen, Jie Lou, Christian Lanius, Florian Freye, Johnson Loh, Tobias Gemmeke:
An Energy-Efficient and Area-Efficient Depthwise Separable Convolution Accelerator with Minimal On-Chip Memory Access. VLSI-SoC 2023: 1-6 - 2022
- [c2]Jie Lou, Christian Lanius, Florian Freye, Tim Stadtmann, Tobias Gemmeke
:
All-Digital Time-Domain Compute-in-Memory Engine for Binary Neural Networks With 1.05 POPS/W Energy Efficiency. ESSCIRC 2022: 149-152 - [c1]Michael Gansen, Jie Lou, Florian Freye
, Tobias Gemmeke
, Farhad Merchant, Albert Zeyer, Mohammad Zeineldeen, Ralf Schlüter
, Xin Fan:
Discrete Steps towards Approximate Computing. ISQED 2022: 1-6
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