Data-centric applications (e.g., data analytics, machine learning, deep learning) running at HPC centers require efficient access to digital information in order to provide accurate results and new insights. Users typically store this information on a shared parallel file system (e.g., Lustre, GPFS), which is available at HPC infrastructures. This is Read more…
Following the challenges addressed in our first blog post, BigHPC will design and implement a new framework for monitoring and managing the infrastructure, data and applications of current and next-generation HPC data centers. The proposed solution aims at enabling both traditional HPC and Big Data applications to be deployed on Read more…
HPC centers are no longer solely targeted for highly parallel modeling and simulation tasks. Indeed, the computational power offered by these systems is now being used to support advanced Big Data analytics for fields such as healthcare, agriculture, environmental sciences, smart cities, and fraud detection1,2. By combining both types of Read more…