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Feature Article This month we write about an important piece of mostly invisible internet infrastructure: data centres. They are rarely seen and little is known of them by the general public. By Dr David Maddison Data Centres, Servers & Cloud Computing E very time you use a search engine, watch an online video, use an email service, use social media, read or write blogs, buy products online, use an AI system, or even read Practical Electronics or most other magazines or newspapers online, you are almost certainly using a data centre. Data centres contain large numbers of computer servers where information is received, stored, managed, processed and disseminated. A server is a computer on which software runs remotely, to ‘serve’ other computers called ‘clients’ over a network. Such software applications include web servers, email servers, databases, custom servers and more. Small companies might start with their own central computer system with an in-house server to store and process their data. As they grow, it might become more economical to move these services to offsite data centres, especially for companies with multiple locations. Companies can: ● pay a data centre to host their own hardware ● rent hardware from a third party but manage the software themselves 58 ● have their off-site hardware and software managed entirely by a thirdparty or multiple parties More and more these days, individuals also pay companies to manage offsite services and data for them, often referring to those services as being in ‘the cloud’. For example, you might be a Google customer and use Google Docs, Gmail, Google Drive etc; or an Apple customer using iCloud, Apple Mail etc; or a Microsoft customer using OneDrive, Office 365 etc. Those services may use local apps (or run in a web browser) but most of the ‘heavy lifting’ is done in servers located in data centres. In most cases, those servers are distributed around the world, so there will always be a local server for fast access (and also so that the entire service doesn’t go down due to one network outage). In some cases (or in certain areas), it is also necessary to store data locally to comply with local laws. Cloud services providers can be huge; they might contain tens of thousands of servers, or even millions, as they service numerous compa- nies (and individuals) from all over the world. The origins of data centres Early computers were room-sized, used large amounts of power and needed a specialised environment with air conditioning, raised floors for cables, provision of a large power system and a building capable of taking the weight of the computer. Such computers were known as “mainframes” (see Fig.1). They were typically accessed via a ‘dumb terminal’, as shown in Fig.2. That was the case from the late 1940s through to the 1970s. Only large businesses, government organisations and scientific establishments could afford such computers. Due to the cost, computing was often done through ‘timesharing’ arrangements, where many users accessed a portion of the power of one large computer through a terminal at their desk or some common location. In the 1970s, the microcomputer was invented, and it was popularised in the 1980s. Software could then be run by individuals from their personal Practical Electronics | March | 2026 Data Centres Fig.1: the NASA Mission Control computer room in 1962 which used two IBM 7094-11 computers. Source: https://archive.org/details/S66-15331 computer (PC), which is also where data was stored. Software was developed that did not need specialised training to use (it was more ‘user-friendly’). Unfortunately, having a computer on every desk led to other problems, such as organisations losing control of their IT resources. This created an incentive to again centralise computing resources. Some larger government and corporate entities still maintained special rooms with traditional mainframe computers where critical data was stored, even with the rollout and acceptance of microcomputers. Still, by and large, desktop PCs were widely used throughout the 1980s and 1990s until the internet started to expand rapidly. The expansion of the internet and the resulting vast requirement for data storage and e-commerce created a need for centralised computing and data storage. This coincided with the socalled ‘dot.com bubble’, from about 1995 to 2000, with large investments in IT-related companies. Central data storage was expensive, and eCommerce companies needed a fast internet connection, which at the time was costly. There was also the need for backup power for the computers and dedicated staff to maintain the systems. It thus became preferable for organisations to subcontract their data storage and computing requirements Practical Electronics | March | 2026 to an external organisation, such as a data centre, where economies of scale helped to minimise costs. In a way, the modern data centre represents a return to the earliest days of computing via centralised systems with dedicated staff. What is a data centre? A data centre is a dedicated facility that houses computers, storage media, networking, power & telecommunications infrastructure, cooling systems, fire suppression systems, security systems, staff facilities and anything else required to run networked computers. What is “the cloud”? This expression is often used in reference to computers running in data centres. ‘The cloud’ represents the availability of computing resources to an end user anywhere that an internet connection exists. That generally implies that the resources are located in one or more data centres. While cloud resources could be hosted in one central location, more likely, they will be distributed over a range of locations for redundancy, to reduce bandwidth requirements over long-distance connections and to reduce latency (access time). Most commonly, a ‘cloud’ service is a type of Software as a Service (SaaS), as per the following section on delivery models. That means that both the cloud hardware and software (includ- Fig.2: a typical way to interact with a computer in the early 1960s was via a printing Teletype, such as this ASR-33 model, introduced in 1963. Source: https://w.wiki/B5fn ing the operating system, applications etc) are managed by a third party. All the customer has to do is access it. It is a somewhat nebulous concept (like a cloud!). Clouds may be public, such as many of the services operated by Microsoft, Google and Apple, or ‘private’, where only specific customers with contracts can access them. Hybrid clouds contain a mix of public and private data and/or services. Service delivery models A data centre or cloud can be managed in various ways, as shown in Fig.3. It can either be completely in-house, or with infrastructure as a service (IaaS), platform as a service (PaaS) or software (applications) as a service (SaaS) representing reducing levels of customer management and increasing levels of data centre or cloud provider management. As an example, the Silicon Chip website (and some of our other software) use the IaaS model. They chose this model to retain maximum control over our systems, without having to worry about provisioning high-speed internet, backup power, cooling etc. It also saves money because they only need a fraction of the power of a computer, so they can share hardware with others to split the costs. Tenancy refers to the sharing of resources. Multi-tenancy is popular on public cloud services, such as Microsoft Azure. In this case, an 59 Feature Article Fig.3: four different data centre service delivery models (related to the concept of tenancy). Original source: https://w.wiki/B5fq individual customer’s data remains invisible and inaccessible to others, but they share hardware, networking, other infrastructure, databases and memory. In that case, there are limited possibilities for the customisation of application software. Examples of multi-tenancy software providers include Google Apps, Salesforce, Dropbox, Mailchimp, HubSpot, DocuSign and Zendesk. With single-tenancy, there is no sharing of resources, which means maximum control over the software – see Fig.4. Virtual machines and servers A virtual machine or virtual server is an emulated version of a physical computer running within a physical computer. To put it another way, from the customer’s perspective, they have access to an entire computer, with which they can do whatever they like. But it doesn’t exist as a physical computer; instead, it is software running on a physical computer, alongside many other customers’ virtual machines. Businesses can create their own virtual server, which can run software and operating systems, store data, perform networking functions and do other computing functions as though it was a real physical computer. This virtual server runs under a software layer known as a ‘hypervisor’, which manages the memory, CPU, storage, networking and other physical resources of the physical computer and allocates them to the virtual machines as required. ● lower latency and faster transfer speeds ● hardware maintenance performed by third parties with access to experts and parts ● multi-tenancy allows costs and resources to be shared among a large pool of users ● data centres typically have a lot of redundancy, making them resistant to power outages and natural or humaninduced disasters Why use the cloud? These reasons include those for using a data centre, plus: ● device independence; applications can be typically via a web browser, so will work from any operating system, including mobile devices ● software maintenance, including updates, performed by expert third parties ● performance monitoring and security by expert third parties ● scalability and elasticity so resources can be increased as required How many data centres exist? There are currently around 523 data centres in the United Kingdom and approximately 139 in Ireland. Europe has approximately 3346 data centres spread among 44 countries. Worldwide, there are approximately 11,000 data centres, with the United States of America having the most at 5387. Data centre infrastructure Data centres have major network infrastructure to connect the data centre to the outside world with plenty of bandwidth. The internal network is also handy for transferring data between multiple computers operated by the same customer (and sometimes even different customers, eg, web crawlers for search engines). There is also significant storage infrastructure for storing data and software; it may be integrated with the computing nodes, or separate and accessed through internal high-speed networking. Of course, there are plenty of computing resources for data processing with onboard memory, with connections to data and applications storage, plus internet infrastructure. These are supported by cooling systems, power supplies and fire suppression systems. The work of a data centre is done in various forms of processing units: Why use a data centre? We touched on this earlier when we explained why we use IaaS, but there are other reasons, including: ● lower costs (due to economies of scale) 60 Fig.4: the single tenancy vs multi-tenancy models for data centres. DB is short for database. Original source: https://resources.igloosoftware.com/blog/multitenancy-database Practical Electronics | March | 2026 Data Centres Fig.5: the NVIDIA GH200 Grace Hopper platform, based on the Grace Hopper Superchip. This board is capable of four petaflops (4 × 1015 floating point operations per second) and includes 72 ARM CPUs, 96GB of HBM3 memory for the CPUs plus 576GB for the GPUs. Source: TechSpot – https://pemag.au/link/ ac19 CPUs (central processing units) CPUs are at the heart of traditional computers and generally continue to be, including in data centres. They may be supplemented by GPUs, TPUs and DPUs (each described below) to improve performance or provide new capabilities. An example of a CPU designed for data centres is the fourth-generation AMD EPYC based on the x86 architecture, as used in most PCs and servers (Fig.7). It is designed to be energy efficient, secure and give high performance. Each of these processors may include up to 128 Zen 4 or Zen 4c cores, allowing each server to potentially handle thousands of requests at any time. GPUs (graphics processing units) GPUs are special processors to accelerate the rendering of images, including 3D scenes. They are also capable of image processing. While they were originally designed for graphics applications, they are highly suitable for non-graphics applications such as parallel processing, accelerated computing and neural networks as needed in machine learning and artificial intelligence (AI). As such, they are commonly found in AI systems. The term ‘accelerated computing’ refers to using specialised hardware such as GPUs to more efficiently performing complex computing tasks than traditional CPUs can. An example of a GPU used in accelerated computing and AI data centres is the NVIDIA Grace Hopper Superchip processor, which forms part of the GH200 Grace Hopper platform (Fig.5). It is specifically designed for accelerated computing and generative AI, primarily in data centres. It utilises the latest HBM3e high bandwidth memory technology that provides 10TB/sec of memory bandwidth. TPUs (tensor processing units) TPUs are proprietary ASICs (application specific integrated circuits) by Google, optimised for neural network machine learning and artificial intelligence. Various versions have been produced since 2015. They are designed for high computational throughput at low precision, handling numbers with as few as eight bits. The chips (see Fig.6) are designed specifically for Google’s TensorFlow framework for machine learning and artificial intelligence, and are incorporated into ‘packages’, as shown in Fig.8. Fig.7: a range of AMD fourth-generation EPYC processors designed specifically for data centre applications. Source: www.amd.com/en/products/processors/ server/epyc/4th-generation-9004-and-8004-series.html Practical Electronics | March | 2026 Fig.6: Google’s v5p TPU chip. Source: https://thetechportal.com/2024/04/09/ google-ai-chip A notable application was Google’s use of TPUs to find and process all the text in the pictures of Google’s Street View database in under five days. Google has developed what they call the Cloud TPU v5p AI Hypercomputer (Fig.9). DPUs (data processing units) DPUs, also called infrastructure processing units (IPUs) or SmartNICs (NIC stands for network interface controller) are used to optimise data centre workloads and to manage networking, security and storage. They relieve system CPUs of these workloads. An example is the SolidNET DPU, an ARM-based software-defined DPU with a PCIe half-height-half-length (HHHL) format. It is based on an offthe-shelf 16-core NXP LX2161A System on Card (SOC) and uses open standards (see Fig.10). For more information, see https://pemag.au/link/ac0b Power supply A typical data centre power system includes: ● transformer(s) to reduce the utility voltage, if necessary ● automatic switching gear to switch to backup power sources such as a generator in the event of a utility failure Fig.8: Google’s TPU v4 board. It has 4 PCIe connectors and 16 OSFP connectors. Source: https://w.wiki/B5fr 61 Feature Article ● a UPS (uninterruptible power supply) supplied by a battery bank to provide backup power in the event of a utility failure, until the generator starts, as well as to condition power and remove voltage spikes in normal operation ● power distribution units (PDU), an electrical board to distribute power from the UPS to equipment locations ● a remote power panel (RPP), an electrical sub-board to distribute power from the PDU to individual rack-mounted power distribution units (rPDU) rPDUs are much like power boards. Individual servers or other equipment are plugged into them. Some of these components may be absent, depending on the size and sophistication of the data centre. All of the above has cables, wiring, circuit breaker boards etc. Some data centres use flywheel energy storage rather than a battery-­ based UPS (see https://pemag.au/link/ ac1b). They can be slightly more costly to install, but they don’t degrade over time as much as batteries do. Power consumption Data centres, especially AI data centres, use an enormous amount of electrical power. That’s both to power the computers themselves, particularly their CPUs, GPUs and TPUs, as well as their cooling systems. So it is important that these be designed to be as efficient as possible to minimise power consumption. Data centres need access to inexpensive, reliable 24/7 power supplies. They consume a significant amount of the world’s electrical power; one es- timate is 1%-1.5% (https://pemag.au/ link/ac0i). According to another estimate (https://pemag.au/link/ac0j), AI currently uses 8% of the world’s electrical energy. The IEA predicts that data centres will consume 6% of electrical power in the United States by 2026, and 32% in Ireland by 2026, up from 17% in 2022 (https://pemag.au/link/ac0k). A typical ‘hyperscale’ data centre consumes up to 100MW according to Oper8 Global (the largest is up to 960MW). But that is just internal consumption. Given a power usage effectiveness (PUE) of 1.3, 130MW will need to be provided from the grid. At a time when dispatchable (on demand) power capacity is diminishing in many countries and being replaced with intermittent solar and wind production, plus the energy demand for charging electric vehicles, it is not clear where all this power will come from. The shortage of power has been recognised. According to the CBRE Group (https://pemag.au/link/ac0l): A worldwide shortage of available power is inhibiting growth of the global data center market. Sourcing enough power is a top priority of data center operators across North America, Europe, Latin America and Asia-­Pacific. Certain secondary markets with robust power supplies stand to attract more data center operators. Data centres are being set up in New Zealand with access to 200MW of relatively inexpensive hydroelectric, gas and geothermal energy, from which 79% of New Zealand’s total production is derived (https://pemag. au/link/ac0m). In the United States, Equinix, a data centre provider, signed a 20-year nonbinding agreement with Oklo to purchase up to 500MW of nuclear power (https://pemag.au/link/ac0n). Microsoft is proposing to use nuclear power for its data centres (see https://pemag.au/link/ac0o), as is Google (https://pemag.au/link/ac0p). Amazon purchased a nuclear-­powered data centre in Salem Township, Pennsylvania, USA (https://pemag.au/link/ ac0q). It consumes an almost unbelievable 960MW of electrical power. According to Funds Europe, the rapid growth of data centres is putting an unsustainable strain on the European electrical grid (https://pemag.au/ link/ac0r). They already use 2.7% of their power, expected to increase to 3.2% by 2030. It has been suggested they use small modular reactors (SMR) and micro modular reactors (MMR) to power data centres. There is a growing interest in using nuclear power for AI data centres: https:// pemag.au/link/ac0j Cooling One of the most critical aspects of a data centre, apart from the computing resources, is the provision of cooling. This is because the vast majority of the enormous amount of power used by data centres ultimately gets converted into heat. Data centres are cooled by air conditioning the rooms the computers are in, and also possibly some type of liquid cooling of the servers themselves. A data centre can be designed with hot and cold aisles between server racks to help maximise the efficiency of the cooling system. Cold air may be delivered from beneath perforated floor tiles and into the server racks Fig.9: inside part of Google’s ‘hypercomputer’ based on v5p TPUs arranged into ‘pods’. Each pod contains 8960 v5p TPUs. Source: Axios – https://pemag. au/link/ac1a Fig.10: a SolidRun SolidNET Software-Defined DPU (data processing unit). Source: www. storagereview.com/news/ solidrun-solidnet-software-defineddpu-for-the-edge-unveiled 62 Practical Electronics | March | 2026 Data Centres before being discharged into the hot aisles (see Fig.12). Alternatively, hot air may be collected at the top of the server racks rather than being blown into an aisle. Some data centres are using emerging technologies such as immersing the computer equipment in a fluid to efficiently remove heat (Fig.13). In two-phase cooling, a volatile cooling liquid boils and condenses on a coil which is connected to a heat exchanger to remover heat, after which it drips down into the coolant pool. Silicon Chip magazine published an article in the November 2018 issue on the DownUnder GeoSolutions supercomputer in Perth that was immersed in an oil bath for cooling at https:// siliconchip.au/Article/11300 Water usage Some data centres, especially those used for AI, consume water for cooling and hydroelectric generation as well. One would think that cooling a data centre would mostly involve a closed loop system, like a typical car. But apparently that is not always the case, as many data centres use large amounts of water. Nature magazine states: ...in July 2022, the month before OpenAI finished training the model, the cluster used about 6% of the district’s water. As Google and Microsoft prepared their Bard and Bing large language models, both had major spikes in water use — increases of 20% and 34%, respectively, in one year, according to the companies’ environmental reports... demand for water for AI could be half that of the United Kingdom by 2027 – https://doi.org/10.1038/ d41586-024-00478-x Details of Microsoft’s water consumption for AI is at https://pemag. au/link/ac0u About 2/3 of the water used by Amazon data centres evaporates; the rest is used for irrigation (https://pemag.au/link/ ac0v). That source also states that the amount of water to be consumed by a proposed Google data centre is regarded as a trade secret! Fire detection and suppression Due to the very high electrical power density inside a data centre, if a fire breaks out, it could get serious very quickly. Fire detection systems need to give early warning to prevent major damage, and fire extinguishing systems Practical Electronics | March | 2026 Fig.11: part of the elaborate plumbing for the cooling system for the Google data centre in Douglas County, Georgia. Source: www.google.com/about/ datacenters/gallery Fig.12: one possible configuration of a data centre using the concept of hot and cold aisles between rows of servers. Original source: www.techtarget.com/ searchdatacenter/How-to-design-and-build-a-data-center Fig.13: the concept of twophase immersion cooling for server equipment Source: www.gigabyte. com/Solutions/ liquidstack-twophase Vapor condenses on coil or lid condenser Fluid recirculates passively to bath Vapor rises to top Heat generated on chip and fluid turns into vapor 63 Feature Article Fig.14: a comparison of the VESDA early warning smoke detection to conventional fire detection systems. Source: https://xtralis.com/product_ subcategory/2/VESDA-Aspirating-Smoke-Detection need to cause minimal damage to electrical equipment. VESDA (Very Early Smoke Detection Apparatus) is a highly sensitive smoke detector (Fig.14), at least 1000 times more sensitive than a typical smoke alarm. It sucks air through perforated pipes that are routed around a protected area, then analyses the sample for the presence of smoke with sensitive detectors. It is an Australian invention in use in many data centres for the early detection of fires. Victaulic Vortex is a fire suppression system used in many data centres (Fig.15). It is a combined water and nitrogen fire extinguishing system. Tiny droplets of water and nitrogen gas, like a fog, are discharged from nozzles to absorb heat, reduce oxygen and extinguish the fire. It causes minimal or no wetting and therefore no equipment damage, avoiding a costly clean-up. After rectifying the fire damage, the data centre can be quickly returned to operation. Security Physical security, data security, environmental security (avoiding flooding, earthquakes etc) and power supply security are all important considerations for data centres. Human entry usually requires some type of biometric system (like a retinal scan) via a secure doorway – see Fig.16. That shows a Circlelock door, which is described at https://pemag.au/link/ac0c Fig.15: an artist’s impression of the Victaulic Vortex fire suppression system in operation, discharging a water and nitrogen fog. Source: https://youtu.be/ qmhO7E4c0tM Fig.16: the entry lobby of a Google data centre uses a Circlelock door and retinal scan, emphasising the high security requirements of data centres. Source: www. google.com/about/datacenters/gallery 64 Server racks Server racks are standardised frames (typically made from metal) that hold computer servers, network switches or other equipment. They help to organise wiring, airflow or plumbing for cooling, provide access for service & maintenance, and sometimes physical security – see Fig.17. Server racks are mounted together in single or multiple rows in whatever number is required, as shown in Fig.18. An important feature of server racks is that they allow a very high density, with up to 42 individual systems in one standard rack, or over 100 with a ‘blade’ configuration. A server rack is designed to accommodate equipment that is 19 inches (482.6mm) wide; that standard was established in 1922 by AT&T. The height of equipment is standardised in heights representing multiples of 1.75 inches (44.45mm). A single-height unit Practical Electronics | March | 2026 Data Centres Fig.17: this server rack is mostly populated with network switches and patch panels. Source: Fourbs Group – https://pemag.au/link/ac1c Fig.18: a group of server racks in a data centre. Source: https://kpmg. com/jp/en/home/insights/2022/03/ datacenter-business.html Fig.19: removing a 1U rack-mounted server mounted with sliding rails. Source: https://youtu.be/fWaW9lA_ pA0 is designated 1U (see Fig.19), double height 2U etc. Equipment might be mounted on rails so it can easily be slid out for service. Alternatively, and more simply, it may be bolted to the edges of the rack using ‘rack ears’. Almost all aspects of server racks are covered by CEA, DIN, EIA, IEC and other standards. The so-called 19-inch rack is used for many other types of equipment as well. There are some other rack standards. One example is Open Rack, an initiative of the Open Compute Project. This rack was specifically designed for large-scale cloud deployments and has features such as a pair of 48V DC busbars at the rear to power the equipment. It is designed for equipment that is 21-inches (538mm) wide instead of 19in (482.6mm), with a vertical spacing of 1.89in (48mm) instead of 1.75in (44.45mm) to improve cooling. The racks are strong to accommodate the extra weight of equipment, all cables connect at the front rather than the back, and IT equipment is hot pluggable. See Fig.20 for a typical Open Rack configuration. au/link/ac0d), over 90% of online data stored in data centres is on hard disk, with the remainder on SSDs. Western Digital sells a drive intended for use in data centres, the Ultrastar DC HC680, with a capacity of 28TB. Seagate’s Exos X series of hard drives have capacities up to 32TB. Tape drives are also used in data centres for archiving data and backups. They have great durability and longevity, and can provide an ‘air gap’ (no physical connection to the rest of the system) to protect stored data against hacking attempts and ransom- ware. They are also low in cost for their high capacity. Enterprise and Datacenter Standard Form Factor (EDSFF) is a specification designed to address the limitations of the 2.5-inch and M.2 sizes for solid-­ state drives. EDSFF drives provide better signal integrity, can draw more power and have higher maximum read/ write speeds. Data storage While there is a general move to solid-­state drives (SSDs) for data storage, hard disk drives (HDDs) retain some advantages over SSDs such as lower price, especially for higher capacities; they last longer, with little degradation with constant read/write cycles; and data recovery is easier for certain failure modes. According to Seagate (https://pemag. Practical Electronics | March | 2026 Standards for data centres Various international standards exist for the design of data centres and their security and operational efficiency. Examples include: ● ISO/IEC 22237-series ● ANSI/TIA-942 ● ANSI/BICSI 002-2024 ● Telcordia GR-3160 Data centre ratings Data centres can be rated according to the TIA-942 standard: Rated-1: Basic Site Infrastructure The data centre has single-capacity components, a non-redundant distribution path for all equipment and limited protection against physical events. Rated-2: Redundant Component Site Infrastructure The data centre has redundant capacity components, but a non-­redundant distribution path that serves the computer equipment. Fig.20: a typical configuration for an Open Compute Project V2 rack. Original source: Mission Critical Magazine – pemag.au/link/ac1e Rated-3: Concurrently Maintainable Site Infrastructure The data centre has redundant capacity components and redundant distribution paths that serve the computer 65 Feature Article equipment, allowing for concurrent maintainability of any piece of equipment. It also has improved physical security. Fig.21: the Google Cloud TPU v5e AI infrastructure in a data centre. Source: https://cloud.google.com/blog/products/compute/announcing-cloud-tpu-v5eand-a3-gpus-in-ga Rated-4: Fault Tolerant Site Infrastructure The data centre has redundant capacity components, active redundant distribution paths to serve the equipment and protection against single failure scenarios. It also includes the highest level of security. A ‘hyperscale’ data centre is one designed to accommodate extreme workloads. Amazon, Facebook, Google, IBM and Microsoft are examples of companies that use them. Artificial intelligence (AI) Fig.22: the Microsoft Azure infrastructure that runs ChatGPT. Source: https:// news.microsoft.com/source/features/ai/how-microsofts-bet-on-azure-unlockedan-ai-revolution Fig.23: inside a small section of the Google data centre in Douglas County, Georgia, USA. Source: www.google.com/about/datacenters/gallery 66 Some data centres are specialised for AI workloads. AI data centres are much like regular data centres in that they require large computing resources and specialised buildings. However, the resource requirements for AI are substantially more than a conventional data centre. According to Australia’s Macquarie Data Centres, conventional data centres require around 12kW per rack, but an AI data centre might require 60kW per rack. Oper8 Global (https://pemag. au/link/ac0w) states that an ‘extreme density’ rack can have a power consumption of up to 150kW! An AI data centre requires far more computing resources. Instead of mainly using CPUs, it will also contain a significant number of GPUs and TPUs. Deep learning & machine learning AI data centres can use either machine learning or deep learning. Machine learning uses algorithms to interpret and learn from data, while deep learning uses similar algorithms but structures them into layers, within an artificial neural network simulating how a brain learns. A neural network is hardware and/ or software with architecture inspired by that of the human (or other) brains. It is used for deep learning, a form of artificial intelligence. Large versions of these are run in data centres. Machine learning does not necessarily use neural networks (but it can). Machine learning is best for structured tasks with small datasets, with thousands of data points, but may Practical Electronics | March | 2026 Data Centres Fig.24: Google Cloud (Cloud CDN) locations (dots) and their interconnecting subsea cables. Source: https://cloud.google.com/ about/locations#network require human intervention if a learned prediction is incorrect. Deep learning is best for making sense of unstructured data with large datasets and millions of data points. Deep learning can determine for itself whether a prediction is wrong or not. Machine learning is relatively quick to train but less powerful; deep learning can take weeks or months to train, like a person. CPUs have advantages for implementing recurrent neural networks (RNNs). Typical applications for RNNs are for translating language, speech recognition, natural language processing and image captioning. GPUs have advantages for some fully connected neural networks. They are probably the most common type of processor used for neural networks, hence the huge stock value of companies that make GPUs like NVIDIA, which at the time of writing is one of the most valuable publicly listed companies in the world at US$2.6 trillion. Fully connected neural networks are suitable for deep learning and have applications in speech recognition, image recognition, visual art characterisation, generating art, natural language processing, drug discovery and toxicology, marketing, medical image analysis, image restoration, materials science, robot training, solving complex mathematical equations and weather prediction, among others. TPUs have advantages for convolutional neural networks (CNNs). Applications for CNNs include pattern recognition, image recognition and object detection. Fig.21 shows part of Practical Electronics | March | 2026 the Google Cloud TPU data centre artificial intelligence infrastructure. Also see the video titled “Inside a Google Cloud TPU Data Center” at https:// youtu.be/FsxthdQ_sL4 Vault), Open Rack (mentioned previously), energy-­efficient power supplies and network switches based on SONiC (Software for Open Networking in the Cloud). ChatGPT This popular AI ‘chatbot’, developed by OpenAI, is hosted on a Microsoft Azure cloud computing data centre infrastructure (see Fig.22). It runs on tens of thousands of NVIDIA’s H100 Tensor Core GPUs with NVIDIA Quantum-2 InfiniBand networking. Underwater data centres Google data centres Google is among the largest owners of data centres, storing vast amounts of the world’s data. Fig.23 shows the inside of a part of a Google data centre, while Fig.24 shows the location of Google Cloud data centres and their interconnection via undersea cables. The locations of data centres for delivering media such as videos (such as for YouTube) can be seen at https:// pemag.au/link/ac1d Open Compute Project (OCP) The OCP (www.opencompute.org) was founded in 2011 with the objective of sharing designs for data centre products and practices. Companies involved include Alibaba Group, Arm, Cisco, Dell, Fidelity, Goldman Sachs, Google, Hewlett Packard Enterprise, IBM, Intel, Lenovo, Meta, Microsoft, Nokia, NVIDIA, Rackspace, Seagate Technology and Wiwynn. Their projects include server designs, an accelerator module for increasing the speed of neural networks in AI applications, data storage modules (Open Because of the significant cooling requirements of data centres and the need for physical security, experiments have been made in placing data centres underwater. They would be constructed within a pressure-resistant waterproof container, with only electrical and data cables coming to the surface. They would not have any staff. With no people, there is no need for a breathable atmosphere, so it can be pure nitrogen to reduce corrosion of connectors and other parts. There is also no possibility of accidental damage such as people dislodging wires etc. Also, there would be no dust to clog cooling fans or get into connectors. The underwater environment has a stable temperature, resulting in fewer failures than when the temperature can vary a lot. It is much easier and more efficient to exchange heat with a fluid such as water than with air, reducing the overall power consumption. An underwater environment also provides protection from some forms of nuclear radiation, which can cause errors in ICs, as water is a good absorber of certain types of radiation. Water can also absorb electromagnetic pulses (EMP) from nuclear explosions. The fact that the electronics are also effectively housed in a Faraday cage will also help with disaster resistance. 67 Feature Article Fig.25: cleaning Microsoft’s underwater data centre after being on the seabed for two years, off the Orkney Islands in Scotland. Source: https://news. microsoft.com/source/features/ sustainability/project-natickunderwater-datacenter Fig.26: an IBM modular data centre built into a standard 40ft (12.2m) long shipping container. Source: https://w.wiki/B5ft Fig.27: looking like somewhere where Superman might live, this 65-storey data centre is proposed to be built in Iceland. Source: www.yankodesign. com/2016/04/01/the-internetsfortress-of-solitude Physical security is improved as being underwater, even if a diver could get to it, there would be no practical way to get inside without flooding the whole container. An underwater data centre can also contribute to reduced latency (response time) because half the world’s population lives within 200km of the sea, so they can be optimally placed near population centres and possibly undersea cables. Underwater data centre projects include: ● Microsoft Project Natick (https:// natick.research.microsoft.com), an experiment first deployed in 2015 with a data centre built within a pressure vessel 12.2m long, 3.18m in diameter, and is about the same size as a standard 40ft (12.2m) shipping container – see Fig.25. Its power consumption was 240kW. It had 12 racks containing 864 standard Microsoft data centre servers with FPGA acceleration and 27.6 petabytes of storage. The atmosphere was 100% nitrogen at one bar. Its planned operational period without maintenance was five years. ● Subsea Cloud (www.subseacloud. com) is proposing to put data centres 3km below sea level for physical security. ● Chinese company Highlander plans to build a commercial undersea data centre at the Hainan Island free trade zone, with a facility for 100 airtight pressure vessels on the seabed. Modular data centres A modular data centre is designed to be portable and is built into a structure like a shipping container – see Fig.26. They might be used to supplement the capacity of an existing data centre, for disaster recovery, humanitarian purposes or for any other reasons where a data centre has to be moved into a place it is needed. Iceland data centre A 65-storey data centre has been proposed to be built in the Arctic (see Fig.27). It was designed by Valeria Mercuri and Marco Merletti. If built in Iceland, it could take advantage of inexpensive geothermal energy and be close to international cable networks. The low temperatures would minimise cooling costs, and the vertical design would minimise land usage. PE 68 Practical Electronics | March | 2026