While AMD voluntarily exited the server processor arena in the wake of Intel’s onslaught with the “Nehalem” Xeon processors during the Great Recession, it never stopped innovating with its graphics processors and it kept enough of a hand in smaller processors used in consumer and selected embedded devices to start making money again in PCs and to take the game console business away from IBM’s Power chip division. …
What goes around comes around. After fighting so hard to drive volume economics in the HPC arena with relatively inexpensive X86 clusters in the past twenty years, those economies of scale are running out of gas. …
We are still chewing through all of the announcements and talk at the GPU Technology Conference that Nvidia hosted in its San Jose stomping grounds last week, and as such we are thinking about the much bigger role that graphics processors are playing in datacenter compute – a realm that has seen five decades of dominance by central processors of one form or another. …
Graphics chip maker Nvidia has taken more than a year and carefully and methodically transformed its GPUs into the compute engines for modern HPC, machine learning, and database workloads. …
While it is always best to have the right tool for the job, it is better still if a tool can be used by multiple jobs and therefore have its utilization be higher than it might otherwise be. …
There is an arms race in the nascent market for GPU-accelerated databases, and the winner will be the one that can scale to the largest datasets while also providing the most compatibility with industry-standard SQL. …
Like other major hyperscale web companies, China’s Tencent, which operates a massive network of ad, social, business, and media platforms, is increasingly reliant on two trends to keep pace. …
The hyperscalers of the world are increasingly dependent on machine learning algorithms for providing a significant part of the user experience and operations of their massive applications, so it is not much of a surprise that they are also pushing the envelope on machine learning frameworks and systems that are used to deploy those frameworks. …
Nvidia has staked its growth in the datacenter on machine learning. …
There is something to be said for being at the right place at the right time. …
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