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pro vyhledávání: '"Satish, Nadathur Rajagopalan"'
Autor:
Patwary, Md. Mostofa Ali, Satish, Nadathur Rajagopalan, Sundaram, Narayanan, Liu, Jialin, Sadowski, Peter, Racah, Evan, Byna, Suren, Tull, Craig, Bhimji, Wahid, Prabhat, Dubey, Pradeep
Computing $k$-Nearest Neighbors (KNN) is one of the core kernels used in many machine learning, data mining and scientific computing applications. Although kd-tree based $O(\log n)$ algorithms have been proposed for computing KNN, due to its inherent
Externí odkaz:
http://arxiv.org/abs/1607.08220
Autor:
Sundaram, Narayanan, Satish, Nadathur Rajagopalan, Patwary, Md Mostofa Ali, Dulloor, Subramanya R, Vadlamudi, Satya Gautam, Das, Dipankar, Dubey, Pradeep
Given the growing importance of large-scale graph analytics, there is a need to improve the performance of graph analysis frameworks without compromising on productivity. GraphMat is our solution to bridge this gap between a user-friendly graph analy
Externí odkaz:
http://arxiv.org/abs/1503.07241
Akademický článek
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Autor:
Patwary, Md. Mostofa Ali, Satish, Nadathur Rajagopalan, Sundaram, Narayanan, Park, Jongsoo, Anderson, Michael J., Vadlamudi, Satya Gautam, Das, Dipankar, Pudov, Sergey G., Pirogov, Vadim O., Dubey, Pradeep
Publikováno v:
High Performance Computing: 30th International Conference, ISC High Performance 2015, Frankfurt, Germany, July 12-16, 2015, Proceedings; 2015, p48-57, 10p
Autor:
Taft, Rebecca, Vartak, Manasi, Satish, Nadathur Rajagopalan, Sundaram, Narayanan, Madden, Samuel, Stonebraker, Michael
Publikováno v:
Proceedings of the 2014 ACM SIGMOD International Conference Management of Data; 6/18/2014, p177-188, 12p