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Mariana Martins Miranda
Projects
PAStor
The PAStor project aims at providing a novel Software-Defined Storage (SDS) solution for HPC that can efficiently handle I/O flows from multiple AI workloads by automatically adjusting storage configurations and resources to dynamically meet application requirements. The proposed solution will be crucial to address the current storage performance bottleneck and fairness challenges of HPC infrastructures. The research output from PAStor will be released as an open-source prototype that will provide the first building block towards a novel storage architecture suited for the exascale computing infrastructure. By gathering the expertise of INESC TEC and Hood College researchers in the AI and distributed storage fields, and by including researchers from TACC and MACC with experience on managing HPC infrastructures, the project will produce new high quality research findings and advance the state-of-the-art for storage solutions currently deployed at HPC centers.
BigHPC
BigHPC aims at simplifying the management of computing and storage resources at HPC infrastructures, supporting Big Data and parallel computing applications, through a novel framework that can be seamlessly integrated with existing HPC centers and software stacks. The contributions of the project are expected to have a direct impact on science, industry and society, by accelerating scientific breakthroughs in different fields and increasing the competitiveness of companies through better data analysis and improved decision-support processes.
Publications
Distributed and Dependable Software-Defined Storage Control Plane for HPC
Miranda, M;
2023
2023 IEEE/ACM 23RD INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND INTERNET COMPUTING WORKSHOPS, CCGRIDW
Taming Metadata-intensive HPC Jobs Through Dynamic, Application-agnostic QoS Control
Macedo, R;Miranda, M;Tanimura, Y;Haga, J;Ruhela, A;Harrell, SL;Evans, RT;Pereira, J;Paulo, J;
2023
2023 IEEE/ACM 23RD INTERNATIONAL SYMPOSIUM ON CLUSTER, CLOUD AND INTERNET COMPUTING, CCGRID
Protecting Metadata Servers From Harm Through Application-level I/O Control
MacEdo, R;Miranda, M;Tanimura, Y;Haga, J;Ruhela, A;Harrell, SL;Evans, RT;Paulo, J;
2022
Proceedings - IEEE International Conference on Cluster Computing, ICCC
Protecting Metadata Servers From Harm Through Application-level I/O Control
Macedo, R;Miranda, M;Tanimura, Y;Haga, J;Ruhela, A;Harrell, SL;Evans, RT;Paulo, J;
2022
2022 IEEE INTERNATIONAL CONFERENCE ON CLUSTER COMPUTING (CLUSTER 2022)