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SamurAI: A 1.7MOPS-36GOPS Adaptive Versatile IoT Node with 15, 000× Peak-to-Idle Power Reduction, 207ns Wake-Up Time and 1.3TOPS/W ML Efficiency.

, , , , , , , , , , , , , , , , , , , , и . VLSI Circuits, стр. 1-2. IEEE, (2020)

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Benoît Cordonnier

Non-Newtonian effects in silicate liquids and crystal bearing melts: implication for magma dynamics. Uni München, (2009)

Benoît Mindzeng

Benoît Vaugon

Benoît Delahaye

Benoît Bertholon

 

Другие публикации лиц с тем же именем

Exploration and Generation of Efficient FPGA-based Deep Neural Network Accelerators., , , и . SiPS, стр. 123-128. IEEE, (2021)A Fine-Grain Variation-Aware Dynamic Vdd-Hopping AVFS Architecture on a 32 nm GALS MPSoC., , , , , , , , , и 4 other автор(ы). IEEE J. Solid State Circuits, 49 (7): 1475-1486 (2014)SamurAI: A 1.7MOPS-36GOPS Adaptive Versatile IoT Node with 15, 000× Peak-to-Idle Power Reduction, 207ns Wake-Up Time and 1.3TOPS/W ML Efficiency., , , , , , , , , и 11 other автор(ы). VLSI Circuits, стр. 1-2. IEEE, (2020)A fine grain variation-aware dynamic Vdd-hopping AVFS architecture on a 32nm GALS MPSoC., , , , , , , , , и 3 other автор(ы). ESSCIRC, стр. 57-60. IEEE, (2013)SamurAI: A Versatile IoT Node With Event-Driven Wake-Up and Embedded ML Acceleration., , , , , , , , , и 10 other автор(ы). IEEE J. Solid State Circuits, 58 (6): 1782-1797 (2023)Deep Neural Networks Characterization Framework for Efficient Implementation on Embedded Systems., , , , и . SiPS, стр. 1-6. IEEE, (2020)A Self-reconfigurable FPGA-Based Platform for Prototyping Future Pervasive Systems., , и . ICES, том 6274 из Lecture Notes in Computer Science, стр. 262-273. Springer, (2010)PNeuro: A scalable energy-efficient programmable hardware accelerator for neural networks., , , , , , , , и . DATE, стр. 1039-1044. IEEE, (2018)