Panasas Adapts To The Ebbs And Flows Of Enterprise HPC

With enterprises increasing embracing HPC environments to help manage the tidal wave of data that’s washing over them and the rise of AI and machine learning workloads, tech vendors selling into the market need to demonstrate both flexibility and adaptability. Most of these organizations are going to start slowly with


Automagically Moving Legacy Hadoop To The Cloud

Always on the lookout for the kernel of a new platform, we chronicled the steady rise and sharp fall of Hadoop as the go-to open source analytics platform. In fact, we watched it morph into a relational database of sorts only to end up being cheap storage for unstructured data.


Google Stands Up Exascale TPUv4 Pods On The Cloud

It is Google I/O 2022 this week, among many other things, and we were hoping for an architectural deep dive on the TPUv4 matrix math engines that Google hinted about at last year’s I/O event. But, alas, no such luck. But the search engine and advertising giant, which also happens


Intel Unrolls DPU Roadmap, With A Two Year Cadence

There is a fundamental disconnect between the cadence that chip makers want for their devices and what the hyperscalers and cloud builders would prefer. And it looks like they are working together to split the difference and accept a two year cadence for the architectural upgrade cycle for all key

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More Analysis


Turning A Million-Qubit Quantum Computing Dream Into Reality

James Clarke believes quantum computing won’t become practical until the industry is making chips crammed with upwards of a million error-corrected quantum bits. The goal of making a quantum system with that many qubits isn’t unique to any one company — IBM, Google and startups like PsiQuantum have all stated


How Much Of A Premium Will Nvidia Charge For Hopper GPUs?

There is increasing competition coming at Nvidia in the AI training and inference market, and at the same time, researchers at Google, Cerebras, and SambaNova are showing off the benefits of porting sections of traditional HPC simulation and modeling code to their matrix math engines, and Intel is probably not


Rethinking The Edge In A Multicloud World

For the past decade or so, unless enterprises wanted to build more of their own datacenters, the cloud providers were the only game in town to tackle new workloads at massive scale. That capacity was available under a pay-as-you-go consumption model, which was great, until the bill arrived. In many


Lawrence Livermore Kicks In Funds to Foster Omni-Path Networking

Decades before there were hyperscalers and cloud builders started creating their own variants of compute, storage, and networking for their massive distributed systems, the major HPC centers of the world fostered innovative technologies that may have otherwise died on the vine and never been propagated in the market at large.


Embracing The Inevitable Move From Hardware To Services

When Amazon Web Services, Microsoft Azure, and other hyperscale public cloud providers started becoming a force in IT almost a decade ago, questions arose about what the future looked like for traditional datacenter hardware providers like Dell and Hewlett Packard Enterprise. The response was a sharp shift toward software and