
A Look at Baidu’s Industrial-Scale GPU Training Architecture
Like its U.S. counterpart, Google, Baidu has made significant investments to build robust, large-scale systems to support global advertising programs. …
Like its U.S. counterpart, Google, Baidu has made significant investments to build robust, large-scale systems to support global advertising programs. …
This month Nvidia bolstered its GPU strategy to stretch further into deep learning, high performance computing, and other markets, and while there are new options to consider, particularly for the machine learning set, it is useful to understand what these new arrays of chips and capabilities mean for users at scale. …
While many consumers in the U.S. might not have heard much about Baidu, when it comes to engineers and computer scientists, the Chinese company is on par with Google, Facebook, and their ilk when it comes to massively scaled distributed computing. …
It was absolutely inevitable that China would try to create its own GPU compute engines. …
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. …
Like their US-based counterparts, Google and Amazon, the Chinese Internet giants Baidu and Alibaba rely on GPU acceleration to drive critical parts of their AI-based services. …
When you are always looking for what platform architecture will be mainstream, you have to look at what those on the bleeding edge are doing to see what the leading edge might do, which in turn tells you what everyone else might eventually do. …
Habana Labs has unveiled the Gaudi HL-2000, a custom-built AI processor that the company claims can outrun Nvidia’s best and brightest GPUs at training neural networks. …
If this is truly the age of heterogeneous supercomputers, then the system installed earlier this month at the University of Tsukuba is its poster child. …
When it comes to machine learning, a lot of the attention in the past six years has focused on the training of neural networks and how the GPU accelerator radically improved the accuracy of networks, thanks to its large memory bandwidth and parallel compute capacity relative to CPUs. …
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