System-on-chip

A 28-nm Energy-Efficient Sparse Neural Network Processor for Point Cloud Applications Using Block-Wise Online Neighbor Searching

A 28-nm Energy-Efficient Sparse Neural Network Processor for Point Cloud Applications Using Block-Wise Online Neighbor Searching 150 150

Abstract:

Voxel-based point cloud networks composed of multiple kinds of sparse convolutions (SCONVs) play an essential role in emerging applications such as autonomous driving and visual navigation. Many researchers have proposed sparse processors for image applications. However, they cannot properly deal with three problems in the point cloud, including low efficiency …

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EMBER: Efficient Multiple-Bits-Per-Cell Embedded RRAM Macro for High-Density Digital Storage

EMBER: Efficient Multiple-Bits-Per-Cell Embedded RRAM Macro for High-Density Digital Storage 150 150

Abstract:

Designing compact and energy-efficient resistive RAM (RRAM) macros is challenging due to: 1) large read/write circuits that decrease storage density; 2) low-conductance cells that increase read latency; and 3) the pronounced effects of routing parasitics on high-conductance cell read energy. Multiple-bits-per-cell RRAM can boost storage density but has further challenges resulting from …

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Monolithic Electronic–Biophotonic System-on-Chip for Label-Free Real-Time Molecular Sensing

Monolithic Electronic–Biophotonic System-on-Chip for Label-Free Real-Time Molecular Sensing 150 150

Abstract:

Label-free miniaturized optical sensors can have a tremendous impact on highly sensitive and scalable point-of-care (PoC) diagnostics by monitoring real-time molecular interactions without any labels. However, current biophotonic platforms are limited by complex optical and external readout equipment, precluding their use in a PoC setting. In this work, we address …

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A Dynamic Execution Neural Network Processor for Fine-Grained Mixed-Precision Model Training Based on Online Quantization Sensitivity Analysis

A Dynamic Execution Neural Network Processor for Fine-Grained Mixed-Precision Model Training Based on Online Quantization Sensitivity Analysis 150 150

Abstract:

BSTcontrol As neural network (NN) training cost red has been growing exponentially over the past decade, developing high-speed and energy-efficient training methods has become an urgent task. Fine-grained mixed-precision low-bit training is the most promising way for high-efficiency training, but it needs dedicated processor designs to overcome the overhead in …

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Sustainable Status Monitoring of MOSFETs in a Fully Integrated RF Amplifier by Thermal Voltage Sensing of On-Chip Thermopile

Sustainable Status Monitoring of MOSFETs in a Fully Integrated RF Amplifier by Thermal Voltage Sensing of On-Chip Thermopile 150 150

Abstract:

In this letter, a sustainable status monitoring of MOSFETs in a fully integrated two stage RF amplifier by thermal voltage sensing of on-chip thermopile is implemented in 0.18- $\mu \text{m}$ CMOS technology. The designed micro-thermopile consists of many thermocouples electrically connected in series by Al and P-type polysilicon, which …

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