The Buck Still Stops Here For GPU Compute
It has taken untold thousands of people to make machine learning, and specifically the deep learning variety, the most viable form of artificial intelligence. …
It has taken untold thousands of people to make machine learning, and specifically the deep learning variety, the most viable form of artificial intelligence. …
There are a lot of things that compute engine makers have to do if they want to compete in the datacenter, but perhaps the most important thing is to be consistent. …
At this point in supercomputing, it’s becoming an anomaly to see an upcoming double-digit petaflops system not using AMD for CPU and GPU, but the National Renewable Energy Laboratory will be taking a more traditional route for the “Kestrel” machine. …
Software maker VMware has always been about tight partnerships with other tech vendors. …
If not for delays, the long-awaited Aurora supercomputer at Argonne National Lab would likely just be coming online. …
SPONSORED Mention GPUs these days, and you will naturally think about how they can accelerate the most challenging AI and machine learning workloads as well as how they are used in gaming platforms. …
Although there are now well-engineered systems that tightly package compute, acceleration, and data movement for deep learning training, for some users, working on time-critical AI training (and constant retraining), the backend applications and frameworks require a different way of thinking. …
About 15 years ago, as Swami Sivasubramanian was making his way from grad school back into the working world, he saw that developers and builders at enterprises were being held back not by their skills or their ideas, but by their inability to access the technology needed to bring those ideas to the fore. …
For more than three decades, researchers have used a particular simulation method for molecular dynamics called Ab initio molecular dynamics, or AIMD, which has proven itself to be the method most accurate for analyzing how atoms and molecules move and interact over a fixed time period. …
It is hard enough to chase one competitor. Imagine how hard it is to chase two different ones in different but complementary markets while at the same time those two competitors are thinking about fighting each other in those two different markets and thus bringing even more intense competitive pressure on both fronts. …
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