What is an Accelerator Module & Things You Need to Know

 

Deloitte predicts that the annual global demand for AI chips will cross 1.5 billion units, which is exactly double the 750 million chips demanded in 2020. The sales of the AI module industry is expected to grow at a compounded annual rate of 20%, so it is definitely a no brainer that AI accelerator modules are harbingers of the future. There is no telling what these chips can do.
In fact, many experts have said that they expect AI accelerators to make their way into consumer electronics as well. Despite current applications resting in automobiles and industrial sectors, there is a lot of untapped potential for this industry. Another area where an AI module can be used is in edge devices. With the advent of the Internet of Things (IoT) tech, AI chips and edge devices become very important.

What Exactly Is an Edge Device?
Before talking about the AI accelerator module, it is very important to understand what an edge device really is. It is basically a term for a device that provides an entry point into the core network of an enterprise. An edge device is part of an edge computing framework, where all or most of the data processing is finished right at the data source.

How Do AI Modules Help Here?
Processing data directly at the source means that the system has to properly deal with a very large chunk of information. As a result of this, it is very important to have a processor equipped to deal with the leviathan volume of real time data. By applying AI modules and machine learning principles, the entire process of edge computing can be sped up considerably.
The AI accelerator module that will be applied for this kind of scenario should have a processing power of at least 20 tera-operations per second (TOPS). It is also very important to have a piece of hardware that is power efficient, since this kind of processing usually requires a lot of power. A power rating of 2-3 TOPS/W is desirable so that your energy bill is kept within reach.

Features of the AI Accelerator Module for Edge Devices: Here are some of the must-have features that you should look for while considering an AI module for your edge devices.

1. Processing Speed: The main feature to look for while choosing AI accelerator chips for your needs is processing speed. Since the volume of the input data is so large, a very high speed of processing is expected in general. Choose hardware that has a minimum capacity of 20 TOPS.
2. Power Efficiency: As mentioned before, power efficiency is also a factor that matters a lot as you choose the best AI module for your needs. A good power rating will ensure that you do not have to spend exorbitant sums of money to receive a small set of insights.
3. No. of Supported Frameworks: An AI chip would actually be useless unless it can be very well supported and compatible with a wide range of frameworks. Since the best ones are TensorFlow and ONNX, you should look for a module that is 100% in sync with these 2 products.
4. Supported Operating Systems: For industrial and enterprise uses, the OS also has to be taken into account. You should look into good AI products that are compatible with Linus, since it is the most used industrial OS. Compatibility with MS Windows and Mac is also a very good thing.

Why Are AI Chips So Great?
AI chips and accelerator modules are so great because they are able to provide a much better level of performance than a normal processor at only a small fraction of the cost. Standalone AI processors draw only 1-10 W in an hour and do as much work as a cluster of normal processors. This cluster would use 10,000 W and cost $40,000.
Final Thoughts
This is basically all you need to know about an AI accelerator module and its amazing uses in the field of edge computing. They can process huge amounts of data at a fraction of the cost and by using only a very small amount of power. You should adopt AI modules into your existing infrastructure and reap all of the amazing benefits as fast as you possibly can.