Speeding Up A.I. - USC Viterbi School of Engineering

#artificialintelligence 

With a new three-year NSF grant, Ming Hsieh Department of Electrical and Computer Engineering researchers hope to solve the problem of scalable parallelism for AI. Co-PI's Professor Viktor Prasanna, Charles Lee Powell Chair in Electrical and Computer Engineering and Professor Xuehai Qian both from USC Viterbi, along with USC Viterbi alum and assistant professor at Northeastern University Yanzhi Wang, and USC Viterbi senior research associate Ajitesh Srivastava were awarded the $800,000 grant last month. Parallelism is the ability of an algorithm to perform several computations at the same time, rather than sequentially. For artificial intelligence challenges which require fast solutions, like the image processing related to autonomous vehicles, parallelism is an essential step to make these technologies practical to every-day life. Parallelism in neural networks has been explored, but the problem has been scaling it up to a point where it's applicable in time-critical/realtime tasks.

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