Professional CUDA C Programming

By John Cheng, M. Grossman, T. McKercher. 2014

320 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d7011869ba77b81f2b2504494ced6fd068a43e9b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Simone Pezzuto
2. Peter Kal'avský
3. A. Auricchio
4. F. Prinzen
5. R. Krause
6. Keith M. Chugg
7. Mark Potse
8. Peter Anthony Beerel

Citations in the corpus

• Pre-Defined Sparsity for Low-Complexity Convolutional Neural Networks (2020, methodology): “The COO format [42] uses three vectors to represent a sparse matrix: a data vector which keeps the values of non-zero elements, a row vector which stores the row indices of non-zero elements, and finally, a column vector which keeps track of column indices of non-zero elements.”
• Evaluation of a Rapid Anisotropic Model for ECG Simulation (2017, methodology): “The solvers were implemented in C and C++ with CUDA extension (Nickolls et al., 2008; Cheng et al., 2014), version 8.”