Data centres have been at the forefront of tech innovation and transformation for quite some time now. One of the most significant shifts they have experienced in recent years has been the move from general-purpose computing to accelerated computing. This shift has been driven by the demand for faster processing speeds, improved efficiency, and the need to handle complex workloads such as artificial intelligence, machine learning, and big data analytics.
General-purpose computing, which relies on traditional central processing units (CPUs), has long been the standard in data centres. However, as the volume and complexity of data continue to grow exponentially, CPUs have struggled to keep up with the processing demands. This has led to a search for alternative solutions that can offer higher performance and efficiency.
Accelerated computing leverages specialised hardware such as graphics processing units (GPUs), field programmable gate arrays (FPGAs), and application-specific integrated circuits (ASICs) to offload specific tasks from the CPU. These accelerators are designed to handle parallel processing tasks more efficiently, making them ideal for workloads that require massive computational power.
As artificial intelligence-related applications continue to grow, billions of dollars of capex are slated to be spent by data centre operators on accelerated computing hardware over the next decade.
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