AI is predicted to be integrated into almost all aspects of our lives over the coming years, from our homes to the workplace, and entertainment to healthcare. While it has its controversies, it is clear AI is here to stay, with far-reaching potential across industries. But in order for AI technology to meet this potential, the correct foundations must be in place.
When we talk about hosting for AI, it is often described as a singular service or product, but in reality it is a broader category. AI workloads can range from training LLMs, to image recognition, to data processing – each with specific infrastructure requirements. Just as there is huge diversity in the application of AI, there needs to be diversity in the hosting of AI workloads – a one-size-fits-all solution does not meet the majority of use cases. In this insight, we will discuss how bespoke infrastructure allows you to run your AI workloads in the most effective way, and outline the benefits of this optimisation of your platform.
The unique demands of hosting for AI workloads
McKinsey reported that 65% of respondents stated that their organisations are regularly using gen AI, and that organisations are already seeing material benefits from incorporating AI (McKinsey Global Survey). The use cases for AI in businesses are widely varied – in some instances, AI models may be a business’s primary output, while in others, AI may only be used internally to streamline processes. The infrastructure requirements for these varied use cases differ. There are several elements to consider when it comes to hosting for your AI workloads.
AI computing is resource-intensive, and requires powerful servers to provide the significant power and performance needed. Additionally, these servers will need to be hosted in data centres that are equipped to meet the increased power and cooling requirements.
To meet these needs, a high-performance computing (HPC) solution, which provides powerful performance for high-compute workloads, is often used. Industry analysts have also observed an increase in private cloud infrastructure, and a shift away from public cloud, due to the increase in AI use (CIO). This diversification in infrastructure requirements has also led many businesses to adopt a hybrid model, combining HPC, private cloud, public cloud, and on-premise environments, assigning workloads to the environment best suited to handling them.
The majority of AI models use GPU servers. Graphic processing units (GPUs) are specifically designed to handle intensive graphics rendering tasks, and analyse large amounts of data faster than computers reliant on central processing units (CPUs). However, CPU-based servers, when configured correctly, can also be effectively utilised for AI development, testing and training.
The issue with off-the-shelf hosting for AI
We have previously explored how off-the-shelf cloud hosting can present challenges for businesses due to their generic nature, as opposed to a consultative approach that delivers bespoke solutions that work more effectively. This is exacerbated when it comes to hosting for AI.
Off-the-shelf solutions generally offer either a fixed amount of resources, or ‘levels’ of resources, with specific configurations, such as GPU-only models. This can lead to significant inefficiencies.
Without the option for customisation, you may end up with either significantly more resources than you need, costing you unnecessary budget, or insufficient resources, causing performance issues for your project.
For more complex projects where you may need a mixed or hybrid infrastructure, this may either not be possible, or come at a significantly higher cost than you initially expected.
You may also run into issues when it comes to scaling your platform. As the technology continues to be developed, and integration into workplaces increases, it is likely that your AI hosting needs will grow. With standard solutions that have a low level of flexibility, scaling your resources can be slow, and come with potentially hidden costs.
The benefits of bespoke solutions for AI workloads
There are a significant number of benefits to using a bespoke solution for your AI workloads.
Bespoke infrastructure can be entirely customised, meaning you can choose the environments and components that best suit your workloads. Rather than fitting your workloads to a pre-configured environment, you fit the environment to your workloads. This optimisation means you can maximise the performance and benefits of your AI workloads, while saving money and reducing your power consumption by removing spending on unnecessary resources.
This customisation also allows you to allocate resources exactly where they are needed. Every component, whether GPU, CPU, or storage, matches the requirements of your workloads, meaning no over-provisioning and waste.
Unlike off-the-shelf solutions, bespoke AI solutions can be designed to seamlessly integrate with your existing IT infrastructure. Particularly when you use a hybrid cloud model, this reduces the complexity of your systems, providing a smoother user experience.
Case study: Designing a bespoke CPU server for Symbolic Mind
Symbolic Mind, a global company developing generative AI and artificial general intelligence architecture, required a hosting provider for training their EVA model. Their requirements were unique – unlike many AI models which only run on GPUs, EVA can use either CPU, GPU or both. For this development and testing project, they needed a CPU powered server.
Other providers Symbolic Mind approached offered off-the-shelf GPU-based solutions which did not meet their requirements. Where different providers did offer a bespoke solution, the costs were prohibitive.
They found our proposal for a bespoke 56-core CPU server was the only solution that met their needs and budget, providing the power, memory and scalability required. Following the custom build, Symbolic Mind trained their EVA LLM on the server, achieving record-breaking 3Gb per hour speeds. Hear from Symbolic Mind on how our bespoke solution met their needs in the full case study.
Why choose bespoke hosting for AI with Hyve?
The example of Symbolic Mind demonstrates the need for affordable, bespoke hosting for AI workloads. The development of AI technology is an evolving field, with new innovations requiring dynamic, flexible infrastructure. The set configurations offered by other providers cannot be flexible to meet unique and developing needs.
We offer a truly consultative approach, taking the time to understand your needs before designing your tailor-made platform. Our fully bespoke HPC and Private Cloud solutions are ideally suited to hosting AI workloads, with the capacity for fully customised architecture incorporating GPUs and CPUs as needed. With our management services, our experts design and continuously manage your infrastructure for maximum efficiency and performance.
Speak to one of our cloud experts today – fill out our contact form and we will be in touch.
