With the increasing popularity of AI software & technologies, there is a need for specialized hardware units to provide high performance to AI services. Traditional processors like CPUs and GPUs often struggle with the massive computational load required by advanced machine learning models. Neural Processing Units (NPUs), often known as AI accelerators or DL(Deep Learning) Accelerators, are the answer to this problem. NPUs are specialized hardware designed to boost AI tasks by optimizing performance and energy efficiency. These purpose-built processors are revolutionizing AI application performance and data processing.
NPUs perform various complex computational operations required by AI efficiently compared to GPUs which are more power-consuming and come at cost. NPUs have dedicated hardware circuits for training models on Trillions of parameters. Currently, GPUs are gaining popularity due to their performance in training the models. But upcoming NPUs are disrupting this trend providing much more performance than GPUs.NPUs implement in-memory computing architecture allowing them to replicate human brain-like working.
source : AWS
These devices can help build the most complex neural networks and vision applications. Implementing the circuit for performing three types of computations (scalar, vector, tensor) makes them the elite hardware for next-generation computers. Companies like Google, Intel, and AWS have already begun constructing their NPUs dedicated for computing devices and cloud infrastructures.AWS Inferentia & Trainium are the NPUs powering modern AI workloads in Cloud infrastructure.
With the research still going on to develop more efficient NPUs it is interesting to see what next things will come to the AI evolution.
Top comments (1)
NPUs have been around for a while now, 2017 for example in the Apple A11 SoC (iPhone 8).