It was only just last month that we spoke with Google distinguished hardware engineer, Norman Jouppi, in depth about the tensor processing unit used internally at the search giant to accelerate deep learning inference, but that device—that first TPU—is already appearing rather out of fashion. …
The science fiction of a generation ago predicted a future in which humans were replaced by the reasoning might of a supercomputer. …
There may be a shortage in the supply of DRAM main memory and NAND flash memory that is having an adverse effect on the server and storage markets, but there is no shortage of vendors who are trying to push the envelope on clustered storage using a mix of these memories and others such as the impending 3D XPoint. …
We have been saying for the past two year that the impending “Skylake” Xeon processors represented the biggest platform architectural change in the Xeon processor business at Intel since the transformational “Nehalem” Xeon 5500s that debuted back in March 2009 into the gaping maw of the Great Recession. …
Petabytes are in the future of every company, and luckily, the future is always being invented by the IT ecosystem to handle it. …
There is no real middle ground when it comes to TensorFlow use cases. …
There is increasing interplay between the worlds of machine learning and high performance computing (HPC). …
Just two years ago, supercomputing was thrust into a larger spotlight because of the surge of interest in deep learning. …
Google created quite a stir when it released architectural details and performance metrics for its homegrown Tensor Processing Unit (TPU) accelerator for machine learning algorithms last week. …
If you can’t beat the largest cloud players at economies of scale, the only option is to try to outrun them in performance, capabilities, or price. …
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