The Internet-of-Things requires end-nodes with ultra-low-power always-on capability for long battery lifetime, as well as high performance, energy efficiency, and extreme flexibility to deal with complex and fast-evolving near-sensor analytics algorithms (NSAAs). We present Vega, an always-on IoT end-node SoC capable of scaling from a 1.7mu W fully retentive COGNITIVE sleep mode up to 32.2GOPS (@49.4mW) peak performance on NSAAs, including mobile DNN inference, exploiting 1.6MB of state- retentive SRAM, and 4MB of non-volatile MRAM. To meet the performance and flexibility requirements of NSAAs, the SoC features 10 RISC-V cores: one core for SoC and IO management and a 9-core cluster supporting multi-precision SIMD integer and floating- poin...
Binary Neural Networks (BNNs) have been shown to be robust to random bit-level noise, making aggress...
A wide range of Internet of Things (IoT) applications require powerful, energy-efficient, and flexib...
Embedding intelligence in extreme edge devices allows distilling raw data acquired from sensors int...
The Internet-of-Things requires end-nodes with ultra-low-power always-on capability for long battery...
Binary Neural Networks (BNNs) have been shown to be robust to random bit-level noise, making aggress...
This paper presents Mr. Wolf, a parallel ultra-low power (PULP) system on chip (SoC) featuring a hie...
Endpoint devices for Internet-of-Things not only need to work under extremely tight power envelope o...
International audienceIoT node application requirements are torn between sporadic data-logging and e...
Preventing device obsolescence in Internet-ofthings (IoT) is mandatory for its massive deployment to...
Heavily quantized fixed-point arithmetic is becoming a common approach to deploy Convolutional Neura...
The IoT is changing the way we live. However, challenges remain for a sustainable deployment of hund...
Current ultra-low power smart sensing edge devices, operating for years on small batteries, are limi...
International audienceIncreased capabilities such as recognition and self-adaptability are now requi...
IoT end-nodes require extreme performance and energy efficiency coupled with high flexibility to dea...
The Internet of Medical Things (IoMT) paradigm is becoming mainstream in multiple clinical trials an...
Binary Neural Networks (BNNs) have been shown to be robust to random bit-level noise, making aggress...
A wide range of Internet of Things (IoT) applications require powerful, energy-efficient, and flexib...
Embedding intelligence in extreme edge devices allows distilling raw data acquired from sensors int...
The Internet-of-Things requires end-nodes with ultra-low-power always-on capability for long battery...
Binary Neural Networks (BNNs) have been shown to be robust to random bit-level noise, making aggress...
This paper presents Mr. Wolf, a parallel ultra-low power (PULP) system on chip (SoC) featuring a hie...
Endpoint devices for Internet-of-Things not only need to work under extremely tight power envelope o...
International audienceIoT node application requirements are torn between sporadic data-logging and e...
Preventing device obsolescence in Internet-ofthings (IoT) is mandatory for its massive deployment to...
Heavily quantized fixed-point arithmetic is becoming a common approach to deploy Convolutional Neura...
The IoT is changing the way we live. However, challenges remain for a sustainable deployment of hund...
Current ultra-low power smart sensing edge devices, operating for years on small batteries, are limi...
International audienceIncreased capabilities such as recognition and self-adaptability are now requi...
IoT end-nodes require extreme performance and energy efficiency coupled with high flexibility to dea...
The Internet of Medical Things (IoMT) paradigm is becoming mainstream in multiple clinical trials an...
Binary Neural Networks (BNNs) have been shown to be robust to random bit-level noise, making aggress...
A wide range of Internet of Things (IoT) applications require powerful, energy-efficient, and flexib...
Embedding intelligence in extreme edge devices allows distilling raw data acquired from sensors int...