Search Results - "Jablin, Thomas B."

Ten Lessons From Three Generations Shaped Google's TPUv4i : Industrial Product by Jouppi, Norman P., Hyun Yoon, Doe, Ashcraft, Matthew, Gottscho, Mark, Jablin, Thomas B., Kurian, George, Laudon, James, Li, Sheng, Ma, Peter, Ma, Xiaoyu, Norrie, Thomas, Patil, Nishant, Prasad, Sushma, Young, Cliff, Zhou, Zongwei, Patterson, David

“…Google deployed several TPU generations since 2015, teaching us lessons that changed our views: semi-conductor technology advances unequally; compiler…”
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MLPerf Inference Benchmark by Reddi, Vijay Janapa, Cheng, Christine, Kanter, David, Mattson, Peter, Schmuelling, Guenther, Wu, Carole-Jean, Anderson, Brian, Breughe, Maximilien, Charlebois, Mark, Chou, William, Chukka, Ramesh, Coleman, Cody, Davis, Sam, Deng, Pan, Diamos, Greg, Duke, Jared, Fick, Dave, Gardner, J. Scott, Hubara, Itay, Idgunji, Sachin, Jablin, Thomas B., Jiao, Jeff, John, Tom St, Kanwar, Pankaj, Lee, David, Liao, Jeffery, Lokhmotov, Anton, Massa, Francisco, Meng, Peng, Micikevicius, Paulius, Osborne, Colin, Pekhimenko, Gennady, Rajan, Arun Tejusve Raghunath, Sequeira, Dilip, Sirasao, Ashish, Sun, Fei, Tang, Hanlin, Thomson, Michael, Wei, Frank, Wu, Ephrem, Xu, Lingjie, Yamada, Koichi, Yu, Bing, Yuan, George, Zhong, Aaron, Zhang, Peizhao, Zhou, Yuchen

“…Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded…”
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Automatic execution of single-GPU computations across multiple GPUs by Cabezas, Javier, Vilanova, Lluis, Geladeno, Isaac, Jablin, Thomas B., Navarro, Nacho, Wen-mei Hwu

“…We present AMGE, a programming framework and runtime system to decompose data and GPU kernels and execute them on multiple GPUs concurrently. AMGE exploits the…”
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Warp-aware trace scheduling for GPUs by Jablin, James A., Jablin, Thomas B., Mutlu, Onur, Herlihy, Maurice

“…GPU performance depends not only on thread/warp level parallelism (TLP) but also on instruction-level parallelism (ILP). It is not enough to schedule…”
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Speculatively exploiting cross-invocation parallelism by Jialu Huang, Prabhu, Prakash, Jablin, Thomas B., Ghosh, Soumyadeep, Apostolakis, Sotiris, Lee, Jae W., August, David I.

“…Automatic parallelization has shown promise in producing scalable multi-threaded programs for multi-core architectures. Most existing automatic techniques…”
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Automatic Parallelization for GPUs by Jablin, Thomas B

“…GPUs are flexible parallel processors capable of accelerating real applications. To exploit them, programmers rewrite programs in new languages using intimate…”
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Chai: Collaborative heterogeneous applications for integrated-architectures by Gomez-Luna, Juan, Hajj, Izzat El, Chang, Li-Wen, Garcia-Flores, Victor, de Gonzalo, Simon Garcia, Jablin, Thomas B., Pena, Antonio J., Hwu, Wen-mei

“…Heterogeneous system architectures are evolving towards tighter integration among devices, with emerging features such as shared virtual memory, memory…”
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A collaborative dependence analysis framework by Johnson, Nick P., Fix, Jordan, Beard, Stephen R., Taewook Oh, Jablin, Thomas B., August, David I.

“…Compiler optimizations discover facts about program behavior by querying static analysis. However, developing or extending precise analysis is difficult. Some…”
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Automatic Parallelization for GPUs by Jablin, Thomas B

“…GPUs are flexible parallel processors capable of accelerating real applications. To exploit them, programmers rewrite programs in new languages using intimate…”
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Automatically exploiting cross-invocation parallelism using runtime information by August, David I., Huang, Jialu, Beard, Stephen R., Johnson, Nick P., Jablin, Thomas B.

“…Automatic parallelization is a promising approach to producing scalable multi-threaded programs for multicore architectures. Many existing automatic techniques…”
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MLPerf Inference Benchmark by Reddi, Vijay Janapa, Cheng, Christine, Kanter, David, Mattson, Peter, Schmuelling, Guenther, Wu, Carole-Jean, Anderson, Brian, Breughe, Maximilien, Charlebois, Mark, Chou, William, Chukka, Ramesh, Coleman, Cody, Davis, Sam, Deng, Pan, Diamos, Greg, Duke, Jared, Fick, Dave, Gardner, J. Scott, Hubara, Itay, Idgunji, Sachin, Jablin, Thomas B, Jiao, Jeff, John, Tom St, Kanwar, Pankaj, Lee, David, Liao, Jeffery, Lokhmotov, Anton, Massa, Francisco, Meng, Peng, Micikevicius, Paulius, Osborne, Colin, Pekhimenko, Gennady, Rajan, Arun Tejusve Raghunath, Sequeira, Dilip, Sirasao, Ashish, Sun, Fei, Tang, Hanlin, Thomson, Michael, Wei, Frank, Wu, Ephrem, Xu, Lingjie, Yamada, Koichi, Yu, Bing, Yuan, George, Zhong, Aaron, Zhang, Peizhao, Zhou, Yuchen

“…Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded…”
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A survey of the practice of computational science by Prabhu, Prakash, Jablin, Thomas B., Raman, Arun, Yun Zhang, Jialu Huang, Hanjun Kim, Johnson, Nick P., Feng Liu, Ghosh, Soumyadeep, Beard, Stephen, Taewook Oh, Zoufaly, Matthew, Walker, David, August, David I.

“…Computing plays an indispensable role in scientific research. Presently, researchers in science have different problems, needs, and beliefs about computation…”
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Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling by Shen, Jonathan, Nguyen, Patrick, Wu, Yonghui, Chen, Zhifeng, Chen, Mia X, Jia, Ye, Kannan, Anjuli, Sainath, Tara, Cao, Yuan, Chiu, Chung-Cheng, He, Yanzhang, Chorowski, Jan, Hinsu, Smit, Laurenzo, Stella, Qin, James, Firat, Orhan, Macherey, Wolfgang, Gupta, Suyog, Bapna, Ankur, Zhang, Shuyuan, Pang, Ruoming, Weiss, Ron J, Prabhavalkar, Rohit, Liang, Qiao, Jacob, Benoit, Liang, Bowen, Lee, HyoukJoong, Chelba, Ciprian, Jean, Sébastien, Li, Bo, Johnson, Melvin, Anil, Rohan, Tibrewal, Rajat, Liu, Xiaobing, Eriguchi, Akiko, Jaitly, Navdeep, Ari, Naveen, Cherry, Colin, Haghani, Parisa, Good, Otavio, Cheng, Youlong, Alvarez, Raziel, Caswell, Isaac, Hsu, Wei-Ning, Yang, Zongheng, Wang, Kuan-Chieh, Gonina, Ekaterina, Tomanek, Katrin, Vanik, Ben, Wu, Zelin, Jones, Llion, Schuster, Mike, Huang, Yanping, Chen, Dehao, Irie, Kazuki, Foster, George, Richardson, John, Macherey, Klaus, Bruguier, Antoine, Zen, Heiga, Raffel, Colin, Kumar, Shankar, Rao, Kanishka, Rybach, David, Murray, Matthew, Peddinti, Vijayaditya, Krikun, Maxim, Bacchiani, Michiel A. U, Jablin, Thomas B, Suderman, Rob, Williams, Ian, Lee, Benjamin, Bhatia, Deepti, Carlson, Justin, Yavuz, Semih, Zhang, Yu, McGraw, Ian, Galkin, Max, Ge, Qi, Pundak, Golan, Whipkey, Chad, Wang, Todd, Alon, Uri, Lepikhin, Dmitry, Tian, Ye, Sabour, Sara, Chan, William, Toshniwal, Shubham, Liao, Baohua, Nirschl, Michael, Rondon, Pat

“…Lingvo is a Tensorflow framework offering a complete solution for collaborative deep learning research, with a particular focus towards sequence-to-sequence…”
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