The Akida Neuromorphic IP is the first neuromorphic IP available in the market. Inspired by the biological function of neurons but engineered on a digital logic process, this event-based spiking neural network (SNN) IP is inherently lower power than traditional convolutional neural networks (CNN) accelerator IP. When using the unique BrainChip CNN2SNN conversion flow, the event-based nature of SNNs enable converted CNNs to be implemented with very low power consumption and high throughput. Because the IP is based upon neuromorphic SNN, it enables unsupervised learning allowing for autonomous edge applications. The Akida Neuromorphic IP contains interfaces through a standard AXI bus making it easily integrated with any ASIC controller.
BrainChip’s AI IP is an event-based technology that is inherently lower power when compared to conventional neural network accelerators. BrainChip IP allows incremental learning and high-speed inferencing in a wide variety of use cases with high throughput and unsurpassed performance-per-watt.
BrainChip’s IP can be configured to perform convolutions (CNP) and fully connect (FNP) layers. Weight bit-precision is programmable to optimize throughput or accuracy and each weight is stored locally in embedded SRAM inside each NPU. The entire neural networks can be placed into the fabric, removing the need to swap weights in and out of DRAM resulting in a reduction of power consumption while increasing throughput.
BrainChip’s IP fabric can be placed either in a parallelized manner that would be ideal for ultimate performance, or space-optimized in order to reduce silicon utilization and further reduce power consumption. Additionally, users can modify clock frequency to optimize performance and power consumption further.