Feature: Clock and timing electronics


Even highly-optimised AI deployments typically utilise only a fraction of their available processing capacity due to


communication bottlenecks, synchronisation overhead, memory constraints and application inefficiencies


tiers, regional variants, development platforms, and validation modes while maintaining an identical PCB design. Reducing hardware variants simplifies manufacturing, streamlines product qualification, lowers inventory costs, and improves supply-chain resilience. For system architects, programmable


timing devices are increasingly enabling a shiſt from hardware-defined timing architectures to soſtware-configurable timing infrastructure. Tis approach provides the flexibility needed to support evolving standards, changing system requirements and future generations of processors and interconnects without requiring a complete hardware redesign. As platform complexity continues to increase, this adaptability is becoming one of the most valuable attributes of a modern timing architecture.


Timing as infrastructure As digital systems continue to scale beyond individual boards and chassis, timing architecture must extend far beyond local clock generation. Te growing scale and autonomy of modern infrastructure have elevated timing from a supporting component to a foundational technology layer that enables the entire system stack. Modern precision timing technologies


can deliver synchronisation accuracy measured in nanoseconds and, in many applications, sub-nanoseconds. Also important are thermal variation, power fluctuations, mechanical vibration and environmental stress, which can all affect timing stability. Advanced silicon- based timing architectures provide the


thermal robustness, long-term stability and vibration resilience required to maintain synchronisation in demanding environments, ranging from hyperscale data centres to industrial and edge deployments; see Figure 2. Te importance of precise


synchronisation becomes particularly evident in large-scale AI infrastructure. Training clusters may contain hundreds or thousands of GPUs and AI accelerators working in parallel on a common workload. To maximise utilisation and maintain deterministic execution, these systems must coordinate data transfers, synchronise barrier operations and maintain tightly- controlled communication schedules across the entire cluster. Even small synchronisation errors can introduce latency, reduce scaling efficiency and limit overall system throughput. Te same challenge exists across


high-performance computing, telecommunications and industrial networking. Technologies like MPI- based HPC fabrics, Time-Sensitive Networking and modern packet-switched communications networks all depend on a shared and highly accurate time reference to coordinate distributed operations. Precision timing provides the mechanism that allows independent systems to operate as a single coherent platform, enabling deterministic behaviour, low- latency communication and predictable performance at scale.


Performance per watt Te importance of timing becomes even more apparent in modern AI


infrastructure, a market projected to outgrow €1 trillion by 2028. As organisations invest billions in AI training and inference platforms, maximising the utilisation of every watt of power and every unit of compute capacity has become a primary design objective. However, AI infrastructure is


rarely limited by theoretical compute capability. Even highly-optimised deployments typically use only a fraction of their available processing capacity due to communication bottlenecks, synchronisation overhead, memory constraints and application inefficiencies. Any additional latency introduced by poor timing coherence further widens the utilisation gap. The consequence is directly


reflected in performance per watt (PPW), one of the most important metrics for evaluating AI infrastructure. PPW measures the amount of useful computational work delivered for a given power budget. In generative AI systems, it is commonly expressed as the number of tokens generated per second relative to the total power consumed by the platform. Improving PPW lowers operating costs, increases data centre efficiency and maximises return on infrastructure investment. Timing plays an important role in


this equation. Poor synchronisation oſten forces system designers to introduce larger timing guard bands to accommodate uncertainty between devices and subsystems. While necessary for reliable operation, these margins can reduce resource utilisation, increase latency and lower overall throughput. Conversely, highly-accurate and deterministic timing enables tighter synchronisation, smaller guard bands, more efficient resource scheduling and improved utilisation across the entire compute fabric. It is therfore clear that as digital infrastructure continues to evolve, timing will increasingly determine not just whether systems function, but how efficiently and effectively they scale.


www.electronicsworld.co.uk November 2026 25


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44