Li, Jiajun, Louri, Ahmed, Karanth, Avinash, and Bunescu, Razvan. GCNAX: A Flexible and Energy-efficient Accelerator for Graph Convolutional Neural Networks. Retrieved from https://par.nsf.gov/biblio/10227172. 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA) . Web. doi:10.1109/HPCA51647.2021.00070.

Li, Jiajun, Louri, Ahmed, Karanth, Avinash, & Bunescu, Razvan. GCNAX: A Flexible and Energy-efficient Accelerator for Graph Convolutional Neural Networks. 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA), (). Retrieved from https://par.nsf.gov/biblio/10227172. https://doi.org/10.1109/HPCA51647.2021.00070

Li, Jiajun, Louri, Ahmed, Karanth, Avinash, and Bunescu, Razvan. "GCNAX: A Flexible and Energy-efficient Accelerator for Graph Convolutional Neural Networks". 2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA) (). Country unknown/Code not available. https://doi.org/10.1109/HPCA51647.2021.00070. https://par.nsf.gov/biblio/10227172.

@article{osti_10227172,
place = {Country unknown/Code not available}, title = {GCNAX: A Flexible and Energy-efficient Accelerator for Graph Convolutional Neural Networks}, url = {https://par.nsf.gov/biblio/10227172}, DOI = {10.1109/HPCA51647.2021.00070}, abstractNote = {}, journal = {2021 IEEE International Symposium on High-Performance Computer Architecture (HPCA)}, author = {Li, Jiajun and Louri, Ahmed and Karanth, Avinash and Bunescu, Razvan}, editor = {null} }