Blog - High Performance Computing - XNV

Tagged in High Performance ComputingStay up-to-date on the latest trends in High-performance computing (HPC).

Consumer vs Server-Grade Hardware and why you can't do Business-Grade work with the former02 June, 2021

In any market or industry, quality work at scale requires purpose-built high-performance tools. In a previous article (The Eight Challenges You'll Face With On-Premise Artificial Intelligence [https://amalgam.ai/posts/the-eight-challenges-youll-face-with-on-premise-artificial-intelligence/] ), we promised to cover this topic more in-depth in a separate post. Well, we like to keep our promises, so here we are. It turns out that 3 of the Challenges we listed (Servers, Networking, and Storage) ar

Adriano Marques

Distributed learning in an on-premise cluster08 January, 2021

Have you tried any distributed learning algorithms? If you are just starting out in this area, I have my doubts, but if you have been on this path for a few years, you might have faced one of those models. The incredible development of the machine learning area in the last decade has not only brought a new state of the art to several problems but has also taken processing optimization and parallelization to another level. With increasingly larger models, any common machine or even a single sup

Is it a good idea to run data centers underwater?24 November, 2020

There are major infrastructural challenges in running large scale data centers. One is providing sufficient electric power to keep the facility running. A datacenter running tens of thousands of servers consumes roughly 10 Megawatts of power. Servers not only consume vast amounts of energy, they also generate a lot of heat. The air inside a data center will become sweltering unless you cool it down. Servers cannot function reliably in high temperatures. The cooling solution needs to be both hi

Adriano Marques

AI Infrastructure Alternatives for your Business13 October, 2020

With cloud offerings becoming more abundant and diverse, cloud infrastructure seems to offer a much cheaper and simpler alternative to an on-premises data center. Many organizations, that need Artificial Intelligence to help with decision-making, problem-solving, etc. face a complicated decision: what is the best infrastructure deployment for AI workloads? Generally speaking, there are three possible deployment options. You can run your AI on-premises in your own datacenter, rent some space at

Adriano Marques

What Kind of AI Infrastructure is Best for my Business?30 September, 2020

In this week's Exponential Chats, some of the team members responsible for Amalgam's development will have a chat about the various infrastructure alternatives available when it comes to training and deployment of Artificial Intelligence models. Between Cloud, Colocation, and On-Premise which one would you say is the best infrastructure for your AI needs? Come join us and participate by asking questions or giving your opinion in the live chat. - Adriano Marques is the founder and CEO of Exponen

Adriano Marques

The Eight Challenges You'll Face With On-Premise Artificial Intelligence18 September, 2020

As glamorous as it is to have your own Artificial Intelligence Optimized On-Premise Data Center, it doesn't come easy. It is absolutelly true that if done right it boasts much better performance and much lower costs than resorting to the cloud or even using co-location to perform your processing workload when creating AI driven solutions. However, most people are not aware of what really makes an AI Optimized Data Center and end up building an expensive half-baked solution that can't perform o

Adriano Marques