(Closed) BigHPC – A Management Framework for Consolidated Big Data and HPC

COMPETE 2020 Newsletter | BigHPC: A Management Framework for Consolidated Big Data and HPC

TechBit | Investment of more than 1.9 million euros to improve national supercomputers


Nowadays, it is becoming increasingly difficult to efficiently manage available computational and storage resources, to provide transparent application access to such resources, and to ensure performance isolation and fairness across different workloads. The BigHPC project will address these challenges with a novel management framework, for Big Data and parallel computing workloads.

In this sense, the BigHPC will simplify the management of Big Data applications and HPC infrastructural resources – with 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.

The project will advance the current knowledge and develop new tools to address the different challenges in HPC infrastructures, namely the monitoring, virtualization and storage management components. At the end of the project, it is expected that the BigHPC will integrate these three components in a new platform, thus allowing a more efficient use of said infrastructures and their services.



A Management Framework for Consolidated Big Data and HPC


A Management Framework for Consolidated Big Data and HPC

Expected Outcomes

  • A novel solution to manage and monitor HPC and Big Data workloads that:
    1) combines novel monitoring, virtualization and software-defined storage components;
    2) can cope with HPC’s infrastructural scale and heterogeneity; 
    3) efficiently supports different workload requirements while ensuring the holistic performance and resource usage; 
    4) can be seamlessly integrated with existing HPC infrastructures and software stacks; 
    5) will be validated with pilots running in both MACC and TACC infrastructures.
Start Date – End Date: March 31, 2020 – March 31, 2023
Scientific Area: Advanced Computing

Big Data, High Performance Computing, HPAI

Lead Beneficiary (PT): Wavecom – Soluções Rádio S.A.
INESC TEC – Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência
LIP, Laboratório de Instrumentação e Física Experimental de Particulas – Associação para a Investigação e Desenvolvimento
PIs at UT Austin: Vijay Chidambaram (Department of Computer Science)
Todd Evans (Texas Advanced Computing Center)
Other Partners: Minho Advanced Computing Center 
Total Eligible Investment (PT): 1 183 678,08 EUR
Total Eligible Investment (US): 799 998,00 USD
Funding Sources Distribution:  

In The News

Co-funded by: