PaSE: Parallelization Strategies for Efficient DNN Training von Elango, Venmugil

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Spatial adaptive sampling in multiscale simulation von Rouet-Leduc, Bertrand, Barros, Kipton, Cieren, Emmanuel, Elango, Venmugil, Junghans, Christoph, Lookman, Turab, Mohd-Yusof, Jamaludin, Pavel, Robert S., Rivera, Axel Y., Roehm, Dominic, McPherson, Allen L., Germann, Timothy C.

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REDUCING TRAINING TIMES OF DEEP NEURAL NETWORKS THROUGH EFFICIENT HYBRID PARALLELISM von ELANGO, Venmugil

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Beyond reuse distance analysis: Dynamic analysis for characterization of data locality potential von Fauzia, Naznin, Elango, Venmugil, Ravishankar, Mahesh, Ramanujam, J, Rastello, Fabrice, Rountev, Atanas, Pouchet, Louis-Noel, Sadayappan, P

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On Using the Roofline Model with Lower Bounds on Data Movement von Elango, Venmugil, Sedaghati, Naser, Rastello, Fabrice, Pouchet, Louis-Noël, Ramanujam, J., Teodorescu, Radu, Sadayappan, P.

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Beyond reuse distance analysis: Dynamic analysis for characterization of data locality potential von Fauzia, Naznin, Elango, Venmugil, Ravishankar, Mahesh, Ramanujam, J., Rastello, Fabrice, Rountev, Atanas, Pouchet, Louis-Noël, Sadayappan, P.

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REDUCING TRAINING TIMES OF DEEP NEURAL NETWORKS THROUGH EFFICIENT HYBRID PARALLELISM von ELANGO VENMUGIL

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ACCELERATING LINEAR ALGEBRA KERNELS FOR ANY PROCESSOR ARCHITECTURE von Ravishankar, Mahesh, Grover, Vinod, Elango, Venmugil, Rubin, Norman

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SYSTEMS AND METHODS FOR SPARSE MATRIX MULTIPLICATION von CHUNG, Eric S, ELANGO, Venmugil, DARVISH ROUHANI, Bita, BURGER, Douglas Christopher

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SYSTEMS AND METHODS FOR SPARSE MATRIX MULTIPLICATION von CHUNG, Eric S, ELANGO, Venmugil, DARVISH ROUHANI, Bita, BURGER, Douglas Christopher

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Microscaling Data Formats for Deep Learning von Rouhani, Bita Darvish, Zhao, Ritchie, More, Ankit, Hall, Mathew, Khodamoradi, Alireza, Deng, Summer, Choudhary, Dhruv, Cornea, Marius, Dellinger, Eric, Denolf, Kristof, Dusan, Stosic, Elango, Venmugil, Golub, Maximilian, Heinecke, Alexander, James-Roxby, Phil, Jani, Dharmesh, Kolhe, Gaurav, Langhammer, Martin, Li, Ada, Melnick, Levi, Mesmakhosroshahi, Maral, Rodriguez, Andres, Schulte, Michael, Shafipour, Rasoul, Shao, Lei, Siu, Michael, Dubey, Pradeep, Micikevicius, Paulius, Naumov, Maxim, Verrilli, Colin, Wittig, Ralph, Burger, Doug, Chung, Eric

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With Shared Microexponents, A Little Shifting Goes a Long Way von Rouhani, Bita, Zhao, Ritchie, Elango, Venmugil, Shafipour, Rasoul, Hall, Mathew, Mesmakhosroshahi, Maral, More, Ankit, Melnick, Levi, Golub, Maximilian, Varatkar, Girish, Shao, Lei, Kolhe, Gaurav, Melts, Dimitry, Klar, Jasmine, L'Heureux, Renee, Perry, Matt, Burger, Doug, Chung, Eric, Deng, Zhaoxia, Naghshineh, Sam, Park, Jongsoo, Naumov, Maxim

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Hierarchical and shared exponent floating point data types von Liu, Ming Gang, Darvish Rouhani, Bita, Xi, Jinwen, Burger, Douglas C, Elango, Venmugil, Fowers, Jeremy, Chung, Eric S, Shafipour, Rasoul

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DATA-AWARE MODEL PRUNING FOR NEURAL NETWORKS von CHUNG, Eric S, ELANGO, Venmugil, BURGER, Douglas C, GOLUB, Maximilian, DARVISH ROUHANI, Bita

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DATA-AWARE MODEL PRUNING FOR NEURAL NETWORKS von CHUNG, Eric S, ELANGO, Venmugil, BURGER, Douglas C, GOLUB, Maximilian, DARVISH ROUHANI, Bita

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HIERARCHICAL AND SHARED EXPONENT FLOATING POINT DATA TYPES von CHUNG, Eric S, SHAFIPOUR, Rasoul, XI, Jinwen, ELANGO, Venmugil, BURGER, Douglas C, DARVISH ROUHANI, Bita, FOWERS, Jeremy, LIU, Ming Gang

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SPARSIFYING NARROW DATA FORMATS FOR NEURAL NETWORKS von More, Ankit, Heddes, Mattheus C, Burger, Douglas C, DARVISH ROUHANI, Bita, Elango, Venmugil, Shah, Nishit, Chung, Eric S, Shafipour, Rasoul

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SPARSIFYING NARROW DATA FORMATS FOR NEURAL NETWORKS von CHUNG, Eric S, SHAFIPOUR, Rasoul, ELANGO, Venmugil, BURGER, Douglas C, MORE, Ankit, DARVISH ROUHANI, Bita, SHAH, Nishit, HEDDES, Mattheus C

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ACCELERATING LINEAR ALGEBRA KERNELS FOR ANY PROCESSOR ARCHITECTURE von Ravishankar, Mahesh, Grover, Vinod K, Elango, Venmugil, Rubin, Norman

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On Characterizing the Data Access Complexity of Programs von Elango, Venmugil, Rastello, Fabrice, Pouchet, Louis-Noël, Ramanujam, J., Sadayappan, P.

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