Search Results - "Lokhmotov, Anton"

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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Collective Knowledge: Towards R&D sustainability by Fursin, Grigori, Lokhmotov, Anton, Plowman, Ed

“…Research funding bodies strongly encourage research projects to disseminate discovered knowledge and transfer developed technology to industry. Unfortunately,…”
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PENCIL: A Platform-Neutral Compute Intermediate Language for Accelerator Programming by Baghdadi, Riyadh, Beaugnon, Ulysse, Cohen, Albert, Grosser, Tobias, Kruse, Michael, Reddy, Chandan, Verdoolaege, Sven, Betts, Adam, Donaldson, Alastair F., Ketema, Jeroen, Absar, Javed, Van Haastregt, Sven, Kravets, Alexey, Lokhmotov, Anton, David, Robert, Hajiyev, Elnar

“…Programming accelerators such as GPUs with low-level APIs and languages such as OpenCL and CUDA is difficult, error-prone, and not performance-portable…”
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GEMMbench: a framework for reproducible and collaborative benchmarking of matrix multiplication by Lokhmotov, Anton

“…The generic matrix-matrix multiplication (GEMM) is arguably the most popular computational kernel of the 20th century. Yet, surprisingly, no common methodology…”
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Dynamic Network selection for the Object Detection task: why it matters and what we (didn't) achieve by Vitali, Emanuele, Lokhmotov, Anton, Palermo, Gianluca

“…In this paper, we want to show the potential benefit of a dynamic auto-tuning approach for the inference process in the Deep Neural Network (DNN) context,…”
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Introducing ReQuEST: an Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments by Moreau, Thierry, Lokhmotov, Anton, Fursin, Grigori

“…Co-designing efficient machine learning based systems across the whole hardware/software stack to trade off speed, accuracy, energy and costs is becoming…”
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MLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from Microwatts to Megawatts for Sustainable AI by Tschand, Arya, Rajan, Arun Tejusve Raghunath, Idgunji, Sachin, Ghosh, Anirban, Holleman, Jeremy, Kiraly, Csaba, Ambalkar, Pawan, Borkar, Ritika, Chukka, Ramesh, Cockrell, Trevor, Curtis, Oliver, Fursin, Grigori, Hodak, Miro, Kassa, Hiwot, Lokhmotov, Anton, Miskovic, Dejan, Pan, Yuechao, Manmathan, Manu Prasad, Raymond, Liz, John, Tom St, Suresh, Arjun, Taubitz, Rowan, Zhan, Sean, Wasson, Scott, Kanter, David, Reddi, Vijay Janapa

“…Rapid adoption of machine learning (ML) technologies has led to a surge in power consumption across diverse systems, from tiny IoT devices to massive…”
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A model-driven approach for a new generation of adaptive libraries by Cianfriglia, Marco, Vella, Flavio, Nugteren, Cedric, Lokhmotov, Anton, Fursin, Grigori

“…ACM Transactions on Architecture and Code Optimization 2021 Efficient high-performance libraries often expose multiple tunable parameters to provide highly…”
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A Collective Knowledge workflow for collaborative research into multi-objective autotuning and machine learning techniques by Fursin, Grigori, Lokhmotov, Anton, Savenko, Dmitry, Upton, Eben

“…Developing efficient software and hardware has never been harder whether it is for a tiny IoT device or an Exascale supercomputer. Apart from the ever growing…”
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Proceedings of the DATE Friday Workshop on Heterogeneous Architectures and Design Methods for Embedded Image Systems (HIS 2015) by Hannig, Frank, Fey, Dietmar, Lokhmotov, Anton

“…This volume contains the papers accepted at the DATE Friday Workshop on Heterogeneous Architectures and Design Methods for Embedded Image Systems (HIS 2015),…”
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Benchmarking TinyML Systems: Challenges and Direction by Banbury, Colby R, Reddi, Vijay Janapa, Lam, Max, Fu, William, Fazel, Amin, Holleman, Jeremy, Huang, Xinyuan, Hurtado, Robert, Kanter, David, Lokhmotov, Anton, Patterson, David, Pau, Danilo, Seo, Jae-sun, Sieracki, Jeff, Thakker, Urmish, Verhelst, Marian, Yadav, Poonam

“…Recent advancements in ultra-low-power machine learning (TinyML) hardware promises to unlock an entirely new class of smart applications. However, continued…”
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Collective Mind, Part II: Towards Performance- and Cost-Aware Software Engineering as a Natural Science by Fursin, Grigori, Memon, Abdul, Guillon, Christophe, Lokhmotov, Anton

“…Nowadays, engineers have to develop software often without even knowing which hardware it will eventually run on in numerous mobile phones, tablets, desktops,…”
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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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PENCIL: Towards a Platform-Neutral Compute Intermediate Language for DSLs by Baghdadi, Riyadh, Cohen, Albert, Guelton, Serge, Verdoolaege, Sven, Inoue, Jun, Grosser, Tobias, Kouveli, Georgia, Kravets, Alexey, Lokhmotov, Anton, Nugteren, Cedric, Waters, Fraser, Donaldson, Alastair F

“…We motivate the design and implementation of a platform-neutral compute intermediate language (PENCIL) for productive and performance-portable accelerator…”
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