The United Arab Emirates (UAE) government is in a phase of rapid growth in terms of the adoption and development of AI services.
Computer Vision and NLP
The branches of AI including machine learning, computer vision and NLP have seen unprecedented growth in the past 10 years. The rapid development of these technologies was a result of the growth in computation power, memory, and their affordability. In addition, there is a unanimous agreement from governments, industries and academia across the world on the fact that developing AI holds significant benefits to society and the economy. The market size for AI is rapidly expanding and is expected to grow even faster. In anticipation for that growth, the UAE government took the initiative by appointing the first ever minister of Artificial Intelligence in October of 2017. This was followed by releasing the UAE AI strategy which outlines a vision for the UAE to be one of the leading nations in AI by the year 2031.
40 Government, Private and Academic entities
Brief and Methodology
Network and Hardware Infrastructure
There are a number of key enablers to build a successful and efficient ecosystem to support innovation and research in AI. Some of the key enablers come in the form of the infrastructure to support entities developing, deploying and researching AI. The main pillars of the AI infrastructure can be categorized into three main items
Data infrastructure: Generally, refers to the availability of data and the high-performance storage platforms that synergizes with AI applications.
Network: Specialized high-performance networking systems that connect the compute servers amongst themselves and to storage units.
Hardware infrastructure: The computing platforms and computer chips that accelerate the process of training and deploying AI applications as well as supporting a large amount of memory.
benchmark: A software or set of tasks that is run by computers to evaluate their performance.
CPU vs GPU for AI Workloads
CPUs (Central Processing Unit) are the main processing units of any computing machine, these components are designed to be a general-purpose processing unit that are able to execute a wide variety of workloads. Building a platform that is mainly composed of CPUs adds a large degree of versatility to the platform making it suitable for data center and generic cloud workloads. This is mainly due to its design choices making it well suited for serial tasks by having limited number of more capable cores. Furthermore, CPUs can also perform AI algorithm training tasks albeit at a much lower performance than preferred. CPUs can also be provisioned/assigned in finer grained resources to perform smaller tasks. Overall, expanding a platform CPU count is a safe choice to steadily increase its processing performance (given that there are no other bottlenecks in the system).
The UAE is a growing leader
Existing AI Hardware Infrastructure in the UAE
The UAE is a growing leader when it comes to AI infrastructure. In fact, the UAE (at the time of writing) has the 36th most powerful high-performance computer in the world5. The UAE’s AI infrastructure ecosystem is dominated by the private sector owning 89% of the total AI related processing power in the UAE. The academic community comes in second and is home to some large-scale state of the art systems, for example NYUAD hosts “Dalma”, a supercomputer composed of more than 870 CPUs and 30 GPUs. These are not the only AI systems in the UAE according to our survey. On the contrary, our survey identified more than 10 high-end systems owned by the government, academia and the private sector. Below is a compiled summary of their combined resources.
Distribution of Computation Resources in the UAE
The international benchmark and ranking for supercomputers focus mainly on the total processing power of the system. The most notable list containing information on the most powerful supercomputers in the world is “Top500”3 list. The UAE currently ranks 36 globaly with the “Artemis” high performance computing cluster owned by G42.
Country Ranking per number of systems on the TOP500
Countries having more supercomputers on the top500 list will rank higher
Ranking of countries on the top500 list ordered by country’s fastest supercomputers
Repeating countries were filtered out.