
The Shape Of Supermicro Machine Learning Iron To Come
If it isn’t obvious, we like hardware here at The Next Platform. …
If it isn’t obvious, we like hardware here at The Next Platform. …
By definition, HPC is always at the cutting edge of computing, driving innovations in processor, system, and software design that eventually find their way into more mainstream computing systems. …
This week we have heard much about the inference side of the deep learning workload, with a range of startups emerging at the AI Hardware Summit. …
On the hardware side, the next frontier for deep learning innovation will be in getting the performance, efficiency, and accuracy needed for inference at scale. …
Gentlemen (and women), start your inference engines.
One of the world’s largest buyers of systems is entering evaluation mode for deep learning accelerators to speed services based on trained models. …
When it comes to machine learning, a lot of the attention in the past six years has focused on the training of neural networks and how the GPU accelerator radically improved the accuracy of networks, thanks to its large memory bandwidth and parallel compute capacity relative to CPUs. …
Over the last several years we have seen many new hardware architectures emerge for deep learning training but this year, inference will have its turn in the spotlight. …
Historically and traditionally, academic supercomputing centers have been very open about the architecture and setup of their HPC systems, and it makes sense if you think about it. …
It doesn’t take a machine learning algorithm to predict that server makers are trying to cash in on the machine learning revolution at the major nexus points on the global Internet. …
With Moore’s Law running out of steam, the chip design wizards at Intel are going off the board to tackle the exascale challenge, and have dreamed up a new architecture that could in one fell swoop kill off the general purpose processor as a concept and the X86 instruction set as the foundation of modern computing. …
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