A5092252108- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- Neural Networks and Reservoir Computing
- Parallel Computing and Optimization Techniques
- CCD and CMOS Imaging Sensors
- Embedded Systems Design Techniques
- Photoreceptor and optogenetics research
IMEC
2023-2024
Neuromorphic processors aim to emulate the biological principles of brain achieve high efficiency with low power consumption. However, lack flexibility in most neuromorphic architecture designs results significant performance loss and inefficient memory usage when mapping various neural network algorithms. This paper proposes SENECA, a digital that balances trade-offs between using hierarchical-controlling system. A SENECA core contains two controllers, flexible controller (RISC-V) an...
Neuromorphic processors promise low-latency and energy-efficient processing by adopting novel brain-inspired design methodologies. Yet, current neuromorphic solutions still struggle to rival conventional deep learning accelerators' performance area efficiency in practical applications. Event-driven data-flow near/in-memory computing are the two dominant trends of processors. However, there remain challenges reducing overhead event-driven increasing mapping computing, which directly impacts...