httpv://www.youtube.com/watch?v=veozohzLjPk
In this video, SC10 SCinet Chair Jamie Van Randwyk explains how SC10’s SCinet will become the fastest network in the world and why such extreme bandwidth is necessary.
In this guest article, our friends at Intel discuss how accelerated computing has diversified over the past several years given advances in CPU, GPU, FPGA, and AI technologies. This innovation drives the need for an open and cross-platform language that allows developers to realize the potential of new hardware, minimizes development cost and complexity, and maximizes reuse of their software investments.
In this new whitepaper from our friends over at Exxact Corporation we take a look at the important topic of deep learning for Natural Language Processing (NLP) and choosing the right GPU for the job. Focus is given to the latest developments in neural networks and deep learning systems, in particular a neural network architecture called transformers. Researchers have shown that transformer networks are particularly well suited for parallelization on GPU-based systems.
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