Introduction to Hardware Accelerators in Artificial Intelligence

A doodle/sketch of the hyped-up topic: machine learning and GPUs!

All about Machine Learning

​Machine Learning is a branch of study all about training a machine (computer for example) to do complete tasks without explicitly programming it. Image classification is an excellent example to explain machine learning. If you want a computer to classify a specific image as a cat, you would train your computer to learn certain features of the cat that are distinguishable from another animal. Another example is being able to detect if your email is spam or not. So you basically need to feed in large amounts of data to your machine learning model for it to learn patterns from that data, and accurately predict future datasets. This requires lots of algorithms and processes, which is where deep learning comes into play. Deep Learning uses an algorithm called neural networks to process, classify and make predictions on data sets. In order to get accurate results, you need LOTS of data. When you need more datasets, its gonna take a long time to efficiently analyze the data. This is where accelerating the ‘analysis’ of data comes into play: and hardware processors can take care of that.

Central Processing Unit

A CPU is basically the brain of a computer: the Central Processing Unit. It essentially executes and performs all of the instructions (in a program, software, application..etc.) such as logical operations, arithmetic, and I/O (input/output — communication between devices). A long time ago, CPUs were built with one core — which means they could only perform one task at a time. However, due to advancements in technology, we can now build multi-core CPUs — which means they are able to perform a couple more tasks at a time.

Graphical Processing Unit

A GPU is called a Graphical Processing Unit, and it's designed differently compared to the CPU. A GPU has many, many more cores, and they are much smaller compared to the ones in the CPU. The cores are designed like this so that parallel, but simple computation (since the cores are smaller) can be performed, and many tasks can my completed simultaneously. GPUs are used a lot in the gaming industry, for image processing and computer graphics (hence the term “Graphics Processing Unit”). In general, the design of the GPU makes algorithms more efficient, compared to the design of a CPU.

--

--

Hello! I’m a student at the University at Texas in Austin. Welcome to my collection of thoughts. I like to write and blog. rushiblogs.weebly.com

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Aarushi Ramesh

Hello! I’m a student at the University at Texas in Austin. Welcome to my collection of thoughts. I like to write and blog. rushiblogs.weebly.com