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Evangelos Georganas
Evangelos Georganas
Intel Labs, Parallel Computing Lab
Bestätigte E-Mail-Adresse bei intel.com - Startseite
Titel
Zitiert von
Zitiert von
Jahr
A study of BFLOAT16 for deep learning training
D Kalamkar, D Mudigere, N Mellempudi, D Das, K Banerjee, S Avancha, ...
arXiv preprint arXiv:1905.12322, 2019
3672019
A whole-genome shotgun approach for assembling and anchoring the hexaploid bread wheat genome
JA Chapman, M Mascher, A Buluç, K Barry, E Georganas, A Session, ...
Genome biology 16, 1-17, 2015
3102015
Critical assessment of metagenome interpretation: the second round of challenges
F Meyer, A Fritz, ZL Deng, D Koslicki, TR Lesker, A Gurevich, G Robertson, ...
Nature methods 19 (4), 429-440, 2022
2532022
Mixed precision training of convolutional neural networks using integer operations
D Das, N Mellempudi, D Mudigere, D Kalamkar, S Avancha, K Banerjee, ...
arXiv preprint arXiv:1802.00930, 2018
2102018
Anatomy of high-performance deep learning convolutions on SIMD architectures
E Georganas, S Avancha, K Banerjee, D Kalamkar, G Henry, H Pabst, ...
SC '18 Proceedings of the International Conference for High Performance …, 0
140*
Distgnn: Scalable distributed training for large-scale graph neural networks
V Md, S Misra, G Ma, R Mohanty, E Georganas, A Heinecke, D Kalamkar, ...
Proceedings of the International Conference for High Performance Computing …, 2021
1272021
Parallel de bruijn graph construction and traversal for de novo genome assembly
E Georganas, A Buluç, J Chapman, L Oliker, D Rokhsar, K Yelick
SC'14: Proceedings of the International Conference for High Performance …, 2014
1092014
HipMer: An extreme-scale de novo genome assembler
E Georganas, A Buluç, J Chapman, S Hofmeyr, C Aluru, R Egan, L Oliker, ...
International Conference for High Performance Computing, Networking, Storage …, 2015
1002015
merAligner: A Fully Parallel Sequence Aligner
E Georganas, A Buluc, J Chapman, L Oliker, D Rokhsar, K Yelick
Parallel and Distributed Processing Symposium (IPDPS), 2015 IEEE …, 2015
632015
Communication avoiding and overlapping for numerical linear algebra
E Georganas, J González-Domínguez, E Solomonik, Y Zheng, J Tourino, ...
SC'12: Proceedings of the International Conference on High Performance …, 2012
602012
Terabase-scale metagenome coassembly with MetaHipMer
S Hofmeyr, R Egan, E Georganas, AC Copeland, R Riley, A Clum, ...
Scientific reports 10 (1), 10689, 2020
582020
Optimizing deep learning recommender systems training on cpu cluster architectures
D Kalamkar, E Georganas, S Srinivasan, J Chen, M Shiryaev, A Heinecke
SC20: International Conference for High Performance Computing, Networking …, 2020
552020
A communication-optimal n-body algorithm for direct interactions
M Driscoll, E Georganas, P Koanantakool, E Solomonik, K Yelick
2013 IEEE 27th International Symposium on Parallel and Distributed …, 2013
542013
Extreme scale de novo metagenome assembly
E Georganas, R Egan, S Hofmeyr, E Goltsman, B Arndt, A Tritt, A Buluc, ...
SC '18 Proceedings of the International Conference for High Performance …, 0
49*
Harnessing deep learning via a single building block
E Georganas, K Banerjee, D Kalamkar, S Avancha, A Venkat, ...
2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2020
252020
Tensor processing primitives: A programming abstraction for efficiency and portability in deep learning workloads
E Georganas, D Kalamkar, S Avancha, M Adelman, C Anderson, A Breuer, ...
Proceedings of the International Conference for High Performance Computing …, 2021
222021
The parallelism motifs of genomic data analysis
K Yelick, A Buluç, M Awan, A Azad, B Brock, R Egan, S Ekanayake, ...
Philosophical Transactions of the Royal Society A 378 (2166), 20190394, 2020
222020
Efficient and generic 1d dilated convolution layer for deep learning
N Chaudhary, S Misra, D Kalamkar, A Heinecke, E Georganas, B Ziv, ...
arXiv preprint arXiv:2104.08002, 2021
192021
FPGA-based AI smart NICs for scalable distributed AI training systems
R Ma, E Georganas, A Heinecke, S Gribok, A Boutros, E Nurvitadhi
IEEE Computer Architecture Letters 21 (2), 49-52, 2022
142022
Optimizing deep learning rnn topologies on intel architecture
K Banerjee, E Georganas, DD Kalamkar, B Ziv, E Segal, C Anderson, ...
Supercomputing Frontiers and Innovations 6 (3), 64-85, 2019
122019
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