Timothy Prickett Morgan is a Co-Editor at The Register. He focuses on themes such as technology, software, artificial intelligence, machine learning, cybersecurity, and privacy, with particular interest in deep learning, MLOps, software development, and Software as a Service (SaaS). Timothy's insights and analyses have been featured in The Next Platform and Guild Companies, Inc.
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Timothy Prickett Morgan's coverage predominantly focuses on the technology industry, particularly in relation to software and SaaS. His articles often cite data and announcements, making him likely interested in pitches that offer unique insights or expert commentary related to these topics.
Given his focus on specific companies such as HPE, Juniper Networks, and IBM i, he may be more responsive to sources who can provide insider perspectives or analysis into developments within these organizations. Additionally, given his emphasis on citing data and industry-specific content, providing concrete evidence or statistics to support pitches may enhance their appeal.
While Timothy does not have a specified geographic focus, it is clear from his coverage that he takes an international view of the technology sector with attention to significant developments regardless of location.
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By: Timothy Prickett Morgan
Right off the bat, let's give a shout out to the mathematician propeller-heads who create the transformations that make it possible to do all kinds of high performance computing to simulate, model, and generate insight from massive amounts of noisy data.
By: Timothy Prickett Morgan
The rise in prices for CPUs, GPUs, DRAM memory, and flash storage have counterbalanced the imbalance between supply and demand such that the overall server market had only a slight sequential decline in the first quarter of 2026. This is not only amazing, but perhaps also intentional on the part of the OEMs and ODMs that bend metal around components to make servers.
If you are trying to get new servers for you company, you better brace yourself for some very serious sticker shock. It’s crazy town out there. The GenAI boom has gone from chemical explosions to nuclear ones, and the hyperscalers, cloud builders, and now the AI model builders are ponying up huge sums for AI systems, driving the total market to an expected $330 billion this year. And all that AI server buying puts these tech titans at the front of the line for DRAM main memory, flash storage, CPUs, and GPUs.
By: Timothy Prickett Morgan
As you well know by now, prices for CPUs, GPUs, main memory, and flash storage have gone completely bonkers thanks to the GenAI system buildout, with systems specially designated for AI workloads now comprising 70.2 percent of the $122.6 billion in system revenues during the first quarter. AI sales would be even larger, and so would sales of traditional systems, had it not been for component shortages that have been consequently driving prices higher. But if there was no shortages to begin with, maybe revenues would also not be so crazy, too, and shipments would be maybe 30 percent to 50 percent higher.
Necessity is always the mother of invention, and if you are trying to create an indigenous compute engine design and manufacturing capability, as China certainly is, then it stands to reason that the Middle Kingdom's eight national computing centers would not only build homegrown accelerators for their supercomputers, but also create all-CPU machines that do not have an offload model and that simply use MPI to spread calculations across traditional scale out networks.
By: Timothy Prickett Morgan
It has been nine years since a Chinese HPC supercomputer was at the top of the High Performance Linpack performance rankings, but as we all know,
The memory market – by which we mean dynamic main memory as well as flash persistent memory – has be ...
There is a crisis building in the datacenter, and it is centered around the scarcity of and ridiculously high prices for DRAM main memory. The GenAI boom has caused the hyperscalers, cloud builders, AI model builders, and neoclouds to hog what has become the limited capacity coming out of the memory foundries of Micron Technology, Samsung, and SK Hynix, and the demand shock is causing unprecedented price hikes.
Yes, that simple question is, in the modern Nvidia world that has come to dominate AI training and to a certain extent HPC simulation and modeling, heretical. But given that CPUs are in many cases starting to look more like GPUs, with their hybrid vector and matrix math engines, mixed precision support, in some cases HBM stacked and high bandwidth memory as well as fatter DRAM main memory, and integrated interconnects, it is also a logical question.
The smartest thing that online bookseller and e-tailing giant Amazon ever did was let you pay for its enormous IT expenses as the company was growing at a crazy pace. You did this by renting compute and storage capacity on the nascent Amazon Web Services cloud. It is not a “public cloud,” it is a private compute utility that people rent capacity on and a massively profitable one at that.
