Search Results - "Fursin, Grigori"

Collective knowledge: organizing research projects as a database of reusable components and portable workflows with common interfaces by Fursin, Grigori

“…This article provides the motivation and overview of the Collective Knowledge Framework (CK or cKnowledge). The CK concept is to decompose research projects…”
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Rapidly Selecting Good Compiler Optimizations using Performance Counters by Cavazos, John, Fursin, Grigori, Agakov, Felix, Bonilla, Edwin, O'Boyle, Michael F. P., Temam, Olivier

“…Applying the right compiler optimizations to a particular program can have a significant impact on program performance. Due to the non-linear interaction of…”
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Enabling more efficient and cost-effective AI/ML systems with Collective Mind, virtualized MLOps, MLPerf, Collective Knowledge Playground and reproducible optimization tournaments by Fursin, Grigori

“…In this white paper, I present my community effort to automatically co-design cheaper, faster and more energy-efficient software and hardware for AI, ML and…”
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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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Federated benchmarking of medical artificial intelligence with MedPerf by Karargyris, Alexandros, Umeton, Renato, Sheller, Micah J., Aristizabal, Alejandro, George, Johnu, Wuest, Anna, Pati, Sarthak, Kassem, Hasan, Zenk, Maximilian, Baid, Ujjwal, Narayana Moorthy, Prakash, Chowdhury, Alexander, Guo, Junyi, Nalawade, Sahil, Rosenthal, Jacob, Kanter, David, Xenochristou, Maria, Beutel, Daniel J., Chung, Verena, Bergquist, Timothy, Eddy, James, Abid, Abubakar, Tunstall, Lewis, Sanseviero, Omar, Dimitriadis, Dimitrios, Qian, Yiming, Xu, Xinxing, Liu, Yong, Goh, Rick Siow Mong, Bala, Srini, Bittorf, Victor, Puchala, Sreekar Reddy, Ricciuti, Biagio, Samineni, Soujanya, Sengupta, Eshna, Chaudhari, Akshay, Coleman, Cody, Desinghu, Bala, Diamos, Gregory, Dutta, Debo, Feddema, Diane, Fursin, Grigori, Huang, Xinyuan, Kashyap, Satyananda, Lane, Nicholas, Mallick, Indranil, Mascagni, Pietro, Mehta, Virendra, Moraes, Cassiano Ferro, Natarajan, Vivek, Nikolov, Nikola, Padoy, Nicolas, Pekhimenko, Gennady, Reddi, Vijay Janapa, Reina, G. Anthony, Ribalta, Pablo, Singh, Abhishek, Thiagarajan, Jayaraman J., Albrecht, Jacob, Wolf, Thomas, Miller, Geralyn, Fu, Huazhu, Shah, Prashant, Xu, Daguang, Yadav, Poonam, Talby, David, Awad, Mark M., Howard, Jeremy P., Rosenthal, Michael, Marchionni, Luigi, Loda, Massimo, Johnson, Jason M., Bakas, Spyridon, Mattson, Peter

“…Medical artificial intelligence (AI) has tremendous potential to advance healthcare by supporting and contributing to the evidence-based practice of medicine,…”
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Milepost GCC: Machine Learning Enabled Self-tuning Compiler by Fursin, Grigori, Kashnikov, Yuriy, Memon, Abdul Wahid, Chamski, Zbigniew, Temam, Olivier, Namolaru, Mircea, Yom-Tov, Elad, Mendelson, Bilha, Zaks, Ayal, Courtois, Eric, Bodin, Francois, Barnard, Phil, Ashton, Elton, Bonilla, Edwin, Thomson, John, Williams, Christopher K. I., O’Boyle, Michael

“…Tuning compiler optimizations for rapidly evolving hardware makes porting and extending an optimizing compiler for each new platform extremely challenging…”
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Collective Knowledge: organizing research projects as a database of reusable components and portable workflows with common APIs by Fursin, Grigori

“…This article provides the motivation and overview of the Collective Knowledge framework (CK or cKnowledge). The CK concept is to decompose research projects…”
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The Collective Knowledge project: making ML models more portable and reproducible with open APIs, reusable best practices and MLOps by Fursin, Grigori

“…This article provides an overview of the Collective Knowledge technology (CK or cKnowledge). CK attempts to make it easier to reproduce ML&systems research,…”
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SysML'19 demo: customizable and reusable Collective Knowledge pipelines to automate and reproduce machine learning experiments by Fursin, Grigori

“…Reproducing, comparing and reusing results from machine learning and systems papers is a very tedious, ad hoc and time-consuming process. I will demonstrate…”
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Invited Talk Abstract: Introducing ReQuEST: An Open Platform for Reproducible and Quality-Efficient Systems-ML Tournaments by Fursin, Grigori

“…Co-designing efficient machine learning based systems across the whole application/hardware/software stack to trade off speed, accuracy, energy and costs is…”
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Collective Tuning Initiative by Fursin, Grigori

“…Computing systems rarely deliver best possible performance due to ever increasing hardware and software complexity and limitations of the current optimization…”
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Portable compiler optimisation across embedded programs and microarchitectures using machine learning by Dubach, Christophe, Jones, Timothy M., Bonilla, Edwin V., Fursin, Grigori, O'Boyle, Michael F. P.

“…Building an optimising compiler is a difficult and time consuming task which must be repeated for each generation of a microprocessor. As the underlying…”
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Collective Mind: cleaning up the research and experimentation mess in computer engineering using crowdsourcing, big data and machine learning by Fursin, Grigori

“…Software and hardware co-design and optimization of HPC systems has become intolerably complex, ad-hoc, time consuming and error prone due to enormous number…”
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CodeReef: an open platform for portable MLOps, reusable automation actions and reproducible benchmarking by Fursin, Grigori, Guillou, Herve, Essayan, Nicolas

“…We present CodeReef - an open platform to share all the components necessary to enable cross-platform MLOps (MLSysOps), i.e. automating the deployment of ML…”
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Poster: Collective Tuning: Novel Extensible Methodology, Framework and Public Repository to Collaboratively Address Exascale Challenges by Fursin, Grigori

“…Designing and optimizing novel computing systems became intolerably complex, ad-hoc, costly and error prone due to an unprecedented number of available tuning…”
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Abstract: cTuning.org: Novel Extensible Methodology, Framework and Public Repository to Collaboratively Address Exascale Challenges by Fursin, Grigori

“…Innovation in science and technology is vital for our society and requires faster, more power efficient and reliable computer systems. However, designing and…”
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A Community Roadmap for Scientific Workflows Research and Development by da Silva, Rafael Ferreira, Casanova, Henri, Chard, Kyle, Altintas, Ilkay, Badia, Rosa M, Balis, Bartosz, Coleman, Taina, Coppens, Frederik, Di Natale, Frank, Enders, Bjoern, Fahringer, Thomas, Filgueira, Rosa, Fursin, Grigori, Garijo, Daniel, Goble, Carole, Howell, Dorran, Jha, Shantenu, Katz, Daniel S., Laney, Daniel, Leser, Ulf, Malawski, Maciej, Mehta, Kshitij, Pottier, Loic, Ozik, Jonathan, Peterson, J. Luc, Ramakrishnan, Lavanya, Soiland-Reyes, Stian, Thain, Douglas, Wolf, Matthew

“…The landscape of workflow systems for scientific applications is notoriously convoluted with hundreds of seemingly equivalent workflow systems, many isolated…”
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Proceedings of the 5th International Workshop on Adaptive Self-tuning Computing Systems 2015 (ADAPT'15) by Dubach, Christophe, Fursin, Grigori

“…This is the proceedings of the 5th International Workshop on Adaptive Self-tuning Computing Systems 2015 (ADAPT'15)…”
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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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Community-driven reviewing and validation of publications by Fursin, Grigori, Dubach, Christophe

“…In this report, we share our practical experience on crowdsourcing evaluation of research artifacts and reviewing of publications since 2008. We also briefly…”
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