2025

  1. One Does Not Simply Cache: A Study on Distributed Caches for AI Training in HPCFerreira, A., Sousa, G., Ruhela, A., Cazes, J., Bhimani, J., Rangaswami, R., Macedo, R., Brito, C., & Paulo, J.In Workshop on Reliable Large-scale Data Management (RLDM’25), colocated with SRDS. 2025.

  2. Exploiting Trusted Execution Environments And Distributed Computation for Genomic Association TestsBrito, C. V., Ferreira, P. G., & Paulo, J.IEEE Journal of Biomedical and Health Informatics. 2025.

2023

  1. Privacy-Preserving Machine Learning on Apache SparkBrito, C. V., Ferreira, P. G., Portela, B. L., Oliveira, R. C., & Paulo, J.IEEE Access. 2023.

  2. SOTERIA: Preserving Privacy in Distributed Machine LearningBrito, C., Ferreira, P., Portela, B., Oliveira, R., & Paulo, J.In Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing (SAC). ACM, 2023.

2022

  1. Accelerating Deep Learning Training Through Transparent Storage TieringDantas, M., Leitão, D., Cui, P., Macedo, R., Liu, X., Xu, W., & Paulo, J.In 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid). IEEE, 2022.

2021

  1. The Case For Storage Optimization Decoupling In Deep Learning FrameworksMacedo, R., Correia, C., Dantas, M., Brito, C., Xu, W., Tanimura, Y., Haga, J., & Paulo, J.In Workshop on Re-envisioning Extreme-Scale I/O for Emerging Hybrid HPC Workloads (REX-IO), colocated with CLUSTER. IEEE, 2021.

  2. Monarch: Hierarchical Storage Management For Deep Learning FrameworksDantas, M., Leitao, D., Correia, C., Macedo, R., Xu, W., & Paulo, J.In Workshop on Re-envisioning Extreme-Scale I/O for Emerging Hybrid HPC Workloads (REX-IO), colocated with CLUSTER. IEEE, 2021.