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SUMMARY:Hardware for Neural Networks - Rune Holm\, Senior Principal Engine
 er\, Machine Learning Group\, ARM
DTSTART:20171127T150000Z
DTEND:20171127T163000Z
UID:TALK96358@talks.cam.ac.uk
CONTACT:Robert Mullins
DESCRIPTION:The use of neural networks has advanced the state of the art i
 n many fields\, including computer vision\, speech processing and machine 
 translation\, and there is reason to believe that more is yet to come. To 
 enable all this\, one of the key challenges is to find ways to execute neu
 ral networks efficiently on computer hardware.\n\nIn this talk\, we will d
 iscuss how neural networks map onto conventional and unconventional comput
 er architectures\, including case studies for CPUs\, GPUs and dedicated ac
 celerators. We will also look at accelerator techniques for further improv
 ing performance\, as well as look at the challenge of keeping some program
 mability to deal with future changes in the state of the art of neural net
 works.\n
LOCATION: SW01\, Computer Laboratory
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