Exploring shared memory architectures for end-to-end gigapixel deep learning.
Lucas W. RemediosLeon Y. CaiSamuel W. RemediosKarthik RamadassAravind R. KrishnanRuining DengCan CuiShunxing BaoLori A. CoburnYuankai HuoBennett A. LandmanPublished in: CoRR (2023)
Keyphrases
- end to end
- deep learning
- shared memory
- parallel architectures
- parallel algorithm
- heterogeneous platforms
- message passing
- distributed memory
- unsupervised learning
- parallel computing
- parallel computers
- parallel programming
- congestion control
- machine learning
- mental models
- weakly supervised
- address space
- data mining
- shared memory multiprocessor
- higher order