Author

Denise Kutnick

Observed name: Kutnick, Denise

Observed institutions: Intel (United States), Friedrich Schiller University Jena

OpenAlex ID: A5086359062

Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning & HPC Workloads

2021 · Georganas, Evangelos, Kalamkar, Dhiraj, et al. · arXiv (Cornell University) · 23

Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning and HPC Workloads

2022 · Evangelos Georganas, Dhiraj Kalamkar, et al. · Frontiers in Applied Mathematics and Statistics · 7

Tensor processing primitives: a programming abstraction for efficiency and portability in deep learning workloads

2021 · Evangelos Georganas, Dhiraj Kalamkar, et al. · International Conference for High Performance Computing, Networking, Storage and Analysis (SC) · 5

Implementation of the article "Tensor processing primitives: a programming abstraction for efficiency and portability in deep learning workloads"

2021 · Menachem Adelman, Cristina Anderson, et al. · Artifact Digital Object Group

Works count: 4

Citation count: 35

H-index: 3

I10-index: 1