Nvidia’s Tesla Volta GPU Is The Beast Of The Datacenter
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. …
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. …
Scaling the performance of machine learning frameworks so they can train larger neural networks – or so the same training a lot faster – has meant that the hyperscalers of the world who are essentially creating this technology have had to rely on increasingly beefy compute nodes, these days almost universally augmented with GPUs. …
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. …
Increasing parallelism is the only way to get more work out of a system. …
After years of planning and delays after a massive architectural change, the Blue Waters supercomputer at the National Center for Supercomputing Applications at the University of Illinois finally went into production in 2013, giving scientists, engineers and researchers across the country a powerful tool to run and solve the most complex and challenging applications in a broad range of scientific areas, from astrophysics and neuroscience to biophysics and molecular research. …
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. …
If Nvidia’s Datacenter business unit was a startup and separate from the company, we would all be talking about the long investment it has made in GPU-based computing and how the company has moved from the blade of the hockey stick and rounded the bend and is moving rapidly up the handle with triple-digit revenue growth and an initial public offering on the horizon. …
We spend a lot of time contemplating what technologies will be deployed at the heart of servers, storage, and networks and thereby form the foundation of the next successive generations of platforms in the datacenter for running applications old and new. …
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