Search Results - "Loncar, Vladimir"

Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors by Coelho, Claudionor N., Kuusela, Aki, Li, Shan, Zhuang, Hao, Ngadiuba, Jennifer, Aarrestad, Thea Klaeboe, Loncar, Vladimir, Pierini, Maurizio, Pol, Adrian Alan, Summers, Sioni

“…Although the quest for more accurate solutions is pushing deep learning research towards larger and more complex algorithms, edge devices demand efficient…”
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Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider by Govorkova, Ekaterina, Puljak, Ema, Aarrestad, Thea, James, Thomas, Loncar, Vladimir, Pierini, Maurizio, Pol, Adrian Alan, Ghielmetti, Nicolò, Graczyk, Maksymilian, Summers, Sioni, Ngadiuba, Jennifer, Nguyen, Thong Q., Duarte, Javier, Wu, Zhenbin

“…To study the physics of fundamental particles and their interactions, the Large Hadron Collider was constructed at CERN, where protons collide to create new…”
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Distance-Weighted Graph Neural Networks on FPGAs for Real-Time Particle Reconstruction in High Energy Physics by Iiyama, Yutaro, Cerminara, Gianluca, Gupta, Abhijay, Kieseler, Jan, Loncar, Vladimir, Pierini, Maurizio, Qasim, Shah Rukh, Rieger, Marcel, Summers, Sioni, Van Onsem, Gerrit, Wozniak, Kinga Anna, Ngadiuba, Jennifer, Di Guglielmo, Giuseppe, Duarte, Javier, Harris, Philip, Rankin, Dylan, Jindariani, Sergo, Liu, Mia, Pedro, Kevin, Tran, Nhan, Kreinar, Edward, Wu, Zhenbin

“…Graph neural networks have been shown to achieve excellent performance for several crucial tasks in particle physics, such as charged particle tracking, jet…”
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Symbolic Regression on FPGAs for Fast Machine Learning Inference by Tsoi, Ho Fung, Pol, Adrian Alan, Loncar, Vladimir, Govorkova, Ekaterina, Cranmer, Miles, Dasu, Sridhara, Elmer, Peter, Harris, Philip, Ojalvo, Isobel, Pierini, Maurizio

“…The high-energy physics community is investigating the potential of deploying machine-learning-based solutions on Field-Programmable Gate Arrays (FPGAs) to…”
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Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml by Khoda, Elham E, Rankin, Dylan, Teixeira de Lima, Rafael, Harris, Philip, Hauck, Scott, Hsu, Shih-Chieh, Kagan, Michael, Loncar, Vladimir, Paikara, Chaitanya, Rao, Richa, Summers, Sioni, Vernieri, Caterina, Wang, Aaron

“…Abstract Recurrent neural networks have been shown to be effective architectures for many tasks in high energy physics, and thus have been widely adopted…”
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Ultrafast jet classification at the HL-LHC by Odagiu, Patrick, Que, Zhiqiang, Duarte, Javier, Haller, Johannes, Kasieczka, Gregor, Lobanov, Artur, Loncar, Vladimir, Luk, Wayne, Ngadiuba, Jennifer, Pierini, Maurizio, Rincke, Philipp, Seksaria, Arpita, Summers, Sioni, Sznajder, Andre, Tapper, Alexander, Årrestad, Thea K

“…Abstract Three machine learning models are used to perform jet origin classification. These models are optimized for deployment on a field-programmable gate…”
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Jet Single Shot Detection by Pol, Adrian Alan, Aarrestad, Thea, Govorkova, Katya, Halily, Roi, Kopetz, Tal, Klempner, Anat, Loncar, Vladimir, Ngadiuba, Jennifer, Pierini, Maurizio, Sirkin, Olya, Summers, Sioni

“…We apply object detection techniques based on Convolutional Neural Networks to jet reconstruction and identification at the CERN Large Hadron Collider. In…”
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Large-Scale Distributed Training Applied to Generative Adversarial Networks for Calorimeter Simulation by Vlimant, Jean-Roch, Pantaleo, Felice, Pierini, Maurizio, Loncar, Vladimir, Vallecorsa, Sofia, Anderson, Dustin, Nguyen, Thong, Zlokapa, Alexander

“…In recent years, several studies have demonstrated the benefit of using deep learning to solve typical tasks related to high energy physics data taking and…”
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C and Fortran OpenMP programs for rotating Bose–Einstein condensates by Kishor Kumar, Ramavarmaraja, Lončar, Vladimir, Muruganandam, Paulsamy, Adhikari, Sadhan K., Balaž, Antun

“…We present OpenMP versions of C and Fortran programs for solving the Gross–Pitaevskii equation for a rotating trapped Bose–Einstein condensate (BEC) in two…”
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CUDA programs for solving the time-dependent dipolar Gross–Pitaevskii equation in an anisotropic trap by Lončar, Vladimir, Balaž, Antun, Bogojević, Aleksandar, Škrbić, Srdjan, Muruganandam, Paulsamy, Adhikari, Sadhan K.

“…In this paper we present new versions of previously published numerical programs for solving the dipolar Gross–Pitaevskii (GP) equation including the contact…”
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OpenMP, OpenMP/MPI, and CUDA/MPI C programs for solving the time-dependent dipolar Gross–Pitaevskii equation by Lončar, Vladimir, Young-S., Luis E., Škrbić, Srdjan, Muruganandam, Paulsamy, Adhikari, Sadhan K., Balaž, Antun

“…We present new versions of the previously published C and CUDA programs for solving the dipolar Gross–Pitaevskii equation in one, two, and three spatial…”
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OpenMP GNU and Intel Fortran programs for solving the time-dependent Gross–Pitaevskii equation by Young-S., Luis E., Muruganandam, Paulsamy, Adhikari, Sadhan K., Lončar, Vladimir, Vudragović, Dušan, Balaž, Antun

“…We present Open Multi-Processing (OpenMP) version of Fortran 90 programs for solving the Gross–Pitaevskii (GP) equation for a Bose–Einstein condensate in one,…”
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A Reconfigurable Neural Network ASIC for Detector Front-End Data Compression at the HL-LHC by Guglielmo, Giuseppe Di, Fahim, Farah, Herwig, Christian, Valentin, Manuel Blanco, Duarte, Javier, Gingu, Cristian, Harris, Philip, Hirschauer, James, Kwok, Martin, Loncar, Vladimir, Luo, Yingyi, Miranda, Llovizna, Ngadiuba, Jennifer, Noonan, Daniel, Ogrenci-Memik, Seda, Pierini, Maurizio, Summers, Sioni, Tran, Nhan

“…Despite advances in the programmable logic capabilities of modern trigger systems, a significant bottleneck remains in the amount of data to be transported…”
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Fast convolutional neural networks on FPGAs with hls4ml by Aarrestad, Thea, Loncar, Vladimir, Ghielmetti, Nicolò, Pierini, Maurizio, Summers, Sioni, Ngadiuba, Jennifer, Petersson, Christoffer, Linander, Hampus, Iiyama, Yutaro, Di Guglielmo, Giuseppe, Duarte, Javier, Harris, Philip, Rankin, Dylan, Jindariani, Sergo, Pedro, Kevin, Tran, Nhan, Liu, Mia, Kreinar, Edward, Wu, Zhenbin, Hoang, Duc

“…Abstract We introduce an automated tool for deploying ultra low-latency, low-power deep neural networks with convolutional layers on field-programmable gate…”
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Compressing deep neural networks on FPGAs to binary and ternary precision with hls4ml by Ngadiuba, Jennifer, Loncar, Vladimir, Pierini, Maurizio, Summers, Sioni, Di Guglielmo, Giuseppe, Duarte, Javier, Harris, Philip, Rankin, Dylan, Jindariani, Sergo, Liu, Mia, Pedro, Kevin, Tran, Nhan, Kreinar, Edward, Sagear, Sheila, Wu, Zhenbin, Hoang, Duc

“…We present the implementation of binary and ternary neural networks in the hls4ml library, designed to automatically convert deep neural network models to…”
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Ultrafast jet classification at the HL-LHC by Odagiu, Patrick, Que, Zhiqiang, Duarte, Javier, Haller, Johannes, Kasieczka, Gregor, Lobanov, Artur, Loncar, Vladimir, Luk, Wayne, Ngadiuba, Jennifer, Pierini, Maurizio, Rincke, Philipp, Seksaria, Arpita, Summers, Sioni, Sznajder, Andre, Tapper, Alexander, Årrestad, Thea K.

“…Three machine learning models are used to perform jet origin classification. These models are optimized for deployment on a field-programmable gate array…”
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Reliable edge machine learning hardware for scientific applications by Baldi, Tommaso, Campos, Javier, Hawks, Ben, Ngadiuba, Jennifer, Tran, Nhan, Diaz, Daniel, Duarte, Javier, Kastner, Ryan, Meza, Andres, Quinnan, Melissa, Weng, Olivia, Geniesse, Caleb, Gholami, Amir, Mahoney, Michael W., Loncar, Vladimir, Harris, Philip, Agar, Joshua, Qin, Shuyu

“…Extreme data rate scientific experiments create massive amounts of data that require efficient ML edge processing. This leads to unique validation challenges…”
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Lightweight jet reconstruction and identification as an object detection task by Pol, Adrian Alan, Aarrestad, Thea, Govorkova, Ekaterina, Halily, Roi, Klempner, Anat, Kopetz, Tal, Loncar, Vladimir, Ngadiuba, Jennifer, Pierini, Maurizio, Sirkin, Olya, Summers, Sioni

“…Abstract We apply object detection techniques based on deep convolutional blocks to end-to-end jet identification and reconstruction tasks encountered at the…”
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Real-time semantic segmentation on FPGAs for autonomous vehicles with hls4ml by Ghielmetti, Nicolò, Loncar, Vladimir, Pierini, Maurizio, Roed, Marcel, Summers, Sioni, Aarrestad, Thea, Petersson, Christoffer, Linander, Hampus, Ngadiuba, Jennifer, Lin, Kelvin, Harris, Philip

“…Abstract In this paper, we investigate how field programmable gate arrays can serve as hardware accelerators for real-time semantic segmentation tasks relevant…”
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Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml by Khoda, Elham E., Rankin, Dylan, Teixeira de Lima, Rafael, Harris, Philip, Hauck, Scott, Hsu, Shih-Chieh, Kagan, Michael, Loncar, Vladimir, Paikara, Chaitanya, Rao, Richa, Summers, Sioni, Vernieri, Caterina, Wang, Aaron

“…Abstract Recurrent neural networks have been shown to be effective architectures for many tasks in high energy physics, and thus have been widely adopted…”
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