A Guide To Accelerated Computing

guide to accelerated computing

The amount of data that different businesses and organizations have to work with has grown massively in recent years, with the size of data models and their parameters increasing at the same time. Huge data sets with more data points to work with mean that businesses and organizations need improved capabilities to analyze the data and make sense of it. Accelerated computing is the obvious answer as it provides the computing power one would need to work with these massive amounts of data. This guide is meant to give you a high-level overview of accelerated computing as there are lots of technicalities, tangents, and developments outside the scope of this discussion.

What Is Accelerated Computing? 

Accelerated computing entails the use of special hardware to speed up different workflows, usually those involving vast amounts of data. All this power can also be harnessed for tasks that require a lot of computational power. The specialized hardware is often a combination of accelerators and CPUs to achieve better computational power and capabilities. Accelerated computing usually uses parallel processing that handles multiple streams of processes which can cripple most CPUs as these are specialized to handle serial instead of parallel data. 

Adoption Of Accelerated Computing 

Accelerated computing was born in the PC and matured when supercomputers became a thing. Now, this technology is being used in our smartphones, cloud hosting services, and even in cryptocurrency mining. Some businesses are already harnessing the power of accelerated computing hardware to provide bitcoin hosting where users can rent mining power for whatever they need. Accelerated computing is also being used in various business processes such as predicting customer behavior and preventing credit card fraud. 

Looking Under The Hood 

Accelerated computing can use AI chips for parallelism or GPUs. GPUs are widely used to provide a balanced system that is capable of data crunching, visualization, data analytics, machine learning and so much more. Although GPUs have been used for this for a long time, Data Processing Units are taking over. Each of the Data Processing Units is paired with a host CPU as part of the larger system. While the CPU handles things like scheduling and ensuring data streams do not get entangled, the Data Processing Units do all the heavy lifting. 

Where Is Accelerated Computing Being Used? 

Accelerated computing is being used anywhere where large amounts of data are being processed. For example, the credit card industry crunches a lot of data on a single day to determine who is eligible for credit through the analysis of numerous factors to determine credit scores, fraudulent charges, and stolen cards. 

IBM is using this technology to predict the weather. This might seem trivial, but more accurate weather forecasts are important for farmers, transportation networks, and numerous types of businesses that are affected by weather changes. 

In business, it is being used to improve customer experience, predict shopping carts, and in recommendation systems. It has also been used to enable faster graphics rendering during movie editing. 

Computing Conclusion

As we increasingly rely on technology for different things in our lives, many of us will use the power of accelerated computing without knowing it. The technology is already being used where analysis of massive amounts of data is required, as well as in smaller scales such as in our smartphones.

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