Introduction to AMD Machine Learning
AMD is new in the Game of Machine Learning; established companies like Apple and Microsoft are doing it for years on their devices. We will discuss how AMD uses the new AMD Machine Learning Algorithm through the Neural Network to get precise and intelligent output in their processors.
What is Machine Learning
Machine Learning is the algorithm of learning how to process data input logically so that execution time is lesser and output is precise. This system retains the process over time through human feedback and tries to rectify its output based on previous experience.
So basically, a system that learns from its mistake can be defined as machine learning, but it depends on the human input of what is right and what is wrong, so it can rectify itself on future executions when it is doing a similar type of works.
Deep Learning is a part of machine learning that is more efficient and does not depend on user input to learn. This self-learning algorithm is more evolved and is used in all systems in Artificial Intelligence like Satellite Street mapping, a Car navigation system, Robotics, etc.
Deep learning actually follows human learning to understand how the human brain recognizes sets of data and process them according to their datasets.
This is how humans learn to execute inputs to produce intelligent output. Machines also try to follow a similar process to process large sets of data. Although humans can process data at a complexity, which is not even 10% achieved by machines yet, machines have the advantage to process huge amounts of data at a time.
Like humans use the central nervous system to take data input, a process in their brain, similarly machines rely on a system called neural networks to classify data to separate sections and categories.
This is an algorithm that detects specific patterns or sets on which data can be classified. AMD Machine Learning uses a Deep Neural Network to process large data. Previously AMD used infinity fabric to provide this result.
How Machine Learning Works
First, Machine learning tries to separate a large group of data based on a set of instructions; a deep neural network is used in processors in AMD Machine Learning.
Improving with Feedback
Next, the system receives feedback from humans on how to improve the execution and follow that next time when it process and executes data.
AMD & Machine Learning
Keras AMD Machine Bridge
Keras is an API used for humans to execute any system with minimum user inputs. AMD machine learning uses the same principle to process data from human input through handles like Plaid ML etc.
AMD Machine Learning Algorithm
AMD Machine learning is the system AMD developed for its chips to process a large set of data and learn to execute them more efficiently as the time progresses. But mostly deep learning part of the machine learning is used in AMD Machine learning through neural networks.
Pytorch AMD GPU
Pytorch is an open source library developed by Facebook that contains codes and functions for machine learning & natural language processing. AMD hardware is using the ROCm platform to connect between AMD devices and Pytorch.
AMD Machine Learning through Tensorflow
Tensorflow is a math based open source library used in Machine Learning through neural networks. AMD Machine learning use ROCm to provide Tensorflow backend support through MIOpen and MIVisionX libraries and provide maximum computer power.
AMD Machine Learning CPU
AMD EPYC 7002 Series Server minded processor is one of the few that use the AMD Machine Learning algorithm effectively to reduce execution time as well as maximizing performance. This is a 64 Core processor that has already been awarded for excelling in many industry leading results.
AMD Machine Learning GPU
AMD Instinct™ MI50 with TSMC 7nm FinFET Chipset is the best in this segment from AMD that uses ROCm for the Deep Learning algorithm. This is a graphics card used in natural engines & machine learning rather than gaming in a Desktop Computer. It supports Open GL, Apple’s Open CL & Vulcan through the ROCm ecosystem to deliver superior accuracy & speed.
AMD Deep Learning 2020
AMD has made breakthroughs with its AMD Radeon Instinct™ MI series GPUs since its in the market with deep learning technology. The ROCm technology has made it possible to interact with libraries such as Pytorch & Tensorflow, and the GPUs have provided solutions for machine learning.
To date, deep learning technology has set many records for AMD as well as been used in many industries leading devices and systems. Tesla recently hired AMD engineers to teach their cars autopilot technology through AMD Machine Learning.
Nvidia Vs. AMD Machine Learning
Nvidia has been the industry leader so far with Nvidia-specific libraries called CUDA and cuDNN, which helped Graphics cards for machine learning & deep learning. However, with the introduction of ROCm, the platform to use Pytorch & Tensorflow libraries, the ground is being more solid for AMD Machine Learning technology.
FAQ. on AMD Machine Learning
Is AMD Ryzen good in the field of deep learning?
Ryzen is not a suitable processor for deep learning; AMD Epyc Series Server processors are optimized to provide results with deep learning technology. Even if you buy threadripper 1920x that will not solve the purpose.
How to install Keras with an AMD GPU?
You can use ML libraries like PlaidML to use Keras with an AMD GPU
How to train deep learning with a local GPU?
Local GPU is not equipped with the technology for
Should I buy a Mac for machine learning?
Yes, MAC can be used for machine learning technology as apple is one of the pioneers in this field.
What is currently the best GPU for deep learning?
AMD Radeon Instinct™ MI50 Accelerator is one of the best GPUs from the AMD lineup to be used for AMD Deep Learning.
Is AMD Ryzen good in the field of deep learning?
It was not before, but recently with the ROCm platform, AMD Ryzen can be used for deep learning. However, it is not a processor optimized for this job and will not deliver the desired result.
Why is AMD so behind NVIDIA?
AMD started late in the run, and previously they did not have any support for Pytorch & Tensorflow libraries; that’s why it was lagging behind all the time before.
Can I run the TensorFlow code in Radeon graphics?
Yes, you can, through PlaidML or a similar platform. However, you will need proper AMD Machine learning optimized GPU like AMD Radeon Instinct™ MI50 Accelerator to implement this correctly.
So far, we have discussed how AMD is one key player nowadays in the field of Machine Learning & Deep learning day by day. They have released server processors, Graphics Cards, and now a whole new lineup of Ryzen Threadripper is waiting to be released with deep learning technology to take them ahead of the game.
If you have a further interest in this topic or have any queries about this topic, please post a comment here; we will be happy to reply to all your comments regarding this topic here.
- Michael Pecht, Artificial Intelligence Trends Based on the Patents, in IEEE Access, vol. 8, 2020
- AMD Blogs, Making Sense out of Machine Learning and Deep Learning, in AMD Website, dated 14th July 2018