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Found 2 papers, 1 papers with code
Analytical Characterization and Design Space Exploration for Optimization of CNNs
Moving data through the memory hierarchy is a fundamental bottleneck that can limit the performance of core algorithms of machine learning, such as convolutional neural networks (CNNs).
PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization
Non-negative Matrix Factorization (NMF) is a key kernel for unsupervised dimension reduction used in a wide range of applications, including topic modeling, recommender systems and bioinformatics.
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