There is a simple test to figure out just how seriously social network Facebook is taking machine learning, and it has nothing to do with research papers or counting cat pictures automagically with neural networks. …
Every supercomputing center in the world is wrestling with the issues of power, cooling, and compute density, but some have tighter constraints than others and need to have more energy efficient machines than they can get with standard clusters of rack servers. …
IBM did not just stake the future of its Power chip and the systems business on which it depends on the OpenPower Foundation, a consortium now with 160 members after more than two years of cultivation by Big Blue and its key early partners – Google, Nvidia, Mellanox Technologies, and Tyan. …
The progression in performance per watt for Nvidia’s Tesla line of GPU coprocessors is continuing apace now that the graphics chip maker is delivering two shiny new devices based on its “Maxwell” generation of chips. …
For more than a decade, graphics processor maker Nvidia has been championing the adoption of GPU accelerators as heavy-lifting compute engines for an increasing array of applications that can take advantage of the parallel processing inherent in a GPU. …
For certain kinds of modeling, simulation, and machine learning workloads, the advent of GPU coprocessors has been a watershed event. …
Every evolution in computing hardware brings with it big challenges for software developers. …
Lining up the architectures of future supercomputers is interesting because it gives us a glimpse of what may be in the corporate datacenter many more years out. …
In-memory databases are all the rage for very fast query processing, but you have to have the right balance of compute and memory for queries against in-memory databases to really scream. …
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