The memBrain™ technology is pioneering advancements in neuromorphic computing by optimizing neural network inference at the edge. By incorporating analog compute-in-memory techniques, memBrain™ efficiently handles deep neural networks' substantial Multiply-Accumulate (MAC) operations, pivotal for AI applications like video and voice recognition. This integration significantly enhances system performance by reducing system bus latencies and power consumption—achieving up to 20-fold power savings compared to conventional digital DSP methods.\n\nUtilizing SuperFlash® technology, memBrain™ stores significant synaptic weights within the floating gate, mitigating the need for off-chip storage and streamlining processing capabilities. The result is a reduction in both cost and system complexity, making advanced AI inferencing capabilities widely accessible. As AI applications evolve to require more efficient storage management, memBrain™ stands out as a solution that economizes power without compromising on performance.\n\nmemBrain™ is particularly influential in scenarios requiring efficient weight storage and MAC operations, such as large-scale neural systems. By employing a tile-based architecture, it supports numerous configurations tailored to specific application needs, ensuring scalability and adaptability in diverse AI models, from edge devices to broader AI systems. This adaptability positions memBrain™ as a forefront technology for edge AI innovations, offering robust solutions across various sectors from industrial to consumer applications.
