In this article today, we will know that What is NPU?. What is the need of NPU and its benefits and use of NPU in mobile phones. NPU Processing ML / AI is the new fancy word for workload. Not useful for very specific, general purpose tasks. Common tasks can of course, but be overkill, also require compiler support.
Design philosophy changes based on what they are targeted at. To handle AI / ML workload Neural Processing Unit In Faster memory / more memory / more computational elements are used. If you understand that CPU, GPU How NPU works is not much different than I know.
It is designed specifically for ML / AI workloads and it would be great for it in other (CPU, GPU, DSP) Is not the case. In the end it all boils down to how fast an ML / AI workload can be executed with the least amount of power.
What is NPU?
Neural processing unit (NPU) One microprocessor Which is machine learning algorithm Specializes in acceleration, usually artificial neural network (ANN) or random forest (RFs) Like works on predictive model. this neural processor also known as.
It is important to note that its Central Processing Unit (CPU) Such as cannot be done for general purpose computing. This is mainly because software support is not developed for this class of processors that can be used for any computing purpose. In fact, developing such a software / compiler can be a challenge and, at the same time, it may give low performance for tasks for which it is not designed.
What is another name for NPU?
CPU And GPU Are different. GPU does not come in the main processing. It comes in Graphic display of computer. The NPU does not have more processors than the GPU. Rather it is a special GPU designed for neural network based AI applications.
Therefore, it is not a successor of the GPU. This is a version of the GPU. If you want a successor to the GPU, this Tensor Processing Unit (TPU) is.
What is the need of NPU?
We have made incredible progress in machine learning application and have left humans behind in some tasks such as playing games like Go and Chess.
At the same time, Machine learning application Taking human life to the next level. Some applications include:
Self Driving Car
Monitoring a system or area from threats such as a security system with real time facial recognition.
Improving health care by accurate analysis and treatment.
And many more
All of these have rapidly increased the number of computations involved and previous approaches to using the GPU may not scale well. This paved the way for designing a processor that would outperform the GPU and counter the progress we are making in the field of machine learning.
Examples of NPU
The real-life implementations of Neural Processing Units (NPU) are:
- TPU by Google
- Sophon by bitmain
- NVDLA by Nvidia
- AWS Inferentia by Amazon
- NNP, Myriad, EyeQ by Intel
What is the purpose of NPU?
Accelerate the calculation of machine learning tasks by leaps and bounds (about 10K times) compared to GPU.
Improve less power and resource usage for machine learning tasks compared to GPU and CPU.
What is NPU’s FULL FORM?
NPU Full Form “Neural processing unit” it happens. Neural processing unit (NPU) is based on a software API for interacting with the AI accelerator chip and platform. This creates a form of machine learning known as intensive learning for mobile devices.
- N – Neural
- P – Processing
- U – Unit
What is NPU Network?
NPU stands for- Neural Network Processing is. “Neural network” may sound a bit confusing, but it “Artificial IntelligenceIs more familiar with. The NPU is the hardware on the phone that specializes in in-depth study of AI. By reading this many of us can think of the first NPE on the Qualcomm Snapdragon 820. In fact, the NPE and NPU are similar.
NPE stands for “Neural Processing Engine”. Both NPE and NPU can handle similar tasks. But NPE is software level and NPU is hardware level. If we choose a computer as an example, the graphics card is its image processor, hardware and frost, confusion, EGO, etc. All game engines are still software.
NPE is still performed with the help of CPU and GPU. Because neural network algorithms and machine learning need to incorporate large amounts of information processing, and the current CPU / GPU cannot achieve such efficient processing capabilities, a separate processing chip is required to do so.
Benefits of NPU
The phone can help the NPU detect the scene more accurately and quickly. Allow the phone to choose the most appropriate image processing algorithm, making the phone more accurate for edge blur when double camera background is blurred and recently very hot AR camera. NPU can greatly improve the speed of reducing and reducing power consumption.
What is Samrtphones using NPU?
Our mobile phone could not know what was in the picture except our face. Now, with the help of NPU, the phone can find out after the learning period to automatically implement some tasks for users in certain scenarios, where users are often doing things, knowing the user’s usage habits. Analyze it. By which the memory storage of the mobile phone and the system resource optimization in time can be optimized.