Uniting Analytics and AI workloads with HPC technology and Enterprise MLOps
The convergence of analytics and AI workloads with simulation or classical high performance computing (HPC) workloads in the cloud are becoming requirements for the model-driven businesses of the future. For many companies today, these siloed environments limit performance at the production scale necessary for truly transformative data science innovation.
In this session, Revati Kulkarni, technology head of the HPC and AI group at Tata Consultancy Services (TCS), along with Thomas Robinson, VP of strategic partnerships at Domino, discuss role-based use cases they’ve seen in enterprise customers. Learn best practices for building a heterogeneous platform to unite analytics and AI workloads, backed by the HPC technology for production level workflows.
- Learn best practices from real-world customer use cases for scaling data science, and how enterprises have reduced non-productive time for data scientists.
- Critical decisions and technological choices required for modern, collaborative data science.
- How the TCS HPC A3 solution, a converged, managed service, powered by Domino's Enterprise MLOps platform, NVIDIA DGX systems, & TCS' Enterprise Cloud, can accelerate time-to-value.