Defect-tolerance and testing for configurable nano-crossbars

Moore\u27s Law speculated a trend in computation technology in terms of number of transistors per unit area that would double roughly every two years. Even after 40 years of this prediction, current technologies have been following it successfully. There are however, certain physical limitations of current CMOS that would result in fundamental obstructions to continuation of Moore\u27s Law. Although there is a debate amongst experts on how much time it would take for this to happen, it is certain that some entirely new paradigms for semiconductor electronics would be needed to replace CMOS and to delay the end of Moore\u27s Law. Silicon nanowires (SiNW) and Carbon nanotubes (CNT) possess significant promise to replace current CMOS --Abstract, page iv

TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

We present TriviaQA, a challenging reading comprehension dataset containing over 650K question-answer-evidence triples. TriviaQA includes 95K question-answer pairs authored by trivia enthusiasts and independently gathered evidence documents, six per question on average, that provide high quality distant supervision for answering the questions. We show that, in comparison to other recently introduced large-scale datasets, TriviaQA (1) has relatively complex, compositional questions, (2) has considerable syntactic and lexical variability between questions and corresponding answer-evidence sentences, and (3) requires more cross sentence reasoning to find answers. We also present two baseline algorithms: a feature-based classifier and a state-of-the-art neural network, that performs well on SQuAD reading comprehension. Neither approach comes close to human performance (23% and 40% vs. 80%), suggesting that TriviaQA is a challenging testbed that is worth significant future study. Data and code available at -- http://nlp.cs.washington.edu/triviaqa/Comment: Added references, fixed typos, minor baseline updat