Govind Tekale
Sambanova Systems and Lawrence Livermore National Laboratory (LLNL) are scaling the collaboration to introduce Sambanova’s spatial data flow accelerator into LLNL’s Computer Center. Aiming to improve the speed and accuracy of scientific research, the enhancement of LLN’s cognitive simulation program is the objective of the collaboration.
A leading federal research institution, LLNL utilizes high-performance computing (HPC) for various endeavors. LLNL has undertaken exploration of how deep neural network hardware architecture can accelerate physics-based simulation as part of NASA’s Advanced Simulation and Computing program.
Computer modeling and experimentation in scientific research face challenges related to fidelity and data volume. While managing large amounts of data through the leveraging of cognitive simulation (CogSim) and Sambanova systems by LLNL researchers, the challenges are being addressed and model fidelity is being enhanced.
Sambanova Systems provides domain-specific, pre-trained foundation models for generative artificial intelligence. Benefiting scientific research in terms of speed and accuracy, the cognitive simulation program at LLNL is being upgraded through the collaboration with Sambanova.
A significant challenge is that cognitive simulations that improve the connection between experimental data and underlying physics are facilitated by the Sambanova system. Begun as a proof-of– concept, the collaboration between Sambanova and LLNL has evolved to develop prototypes of the final solution.
Enhancing overall speed, performance, and productivity, AI calculations were led by the integration of Sambanova DataScale hardware into LLNL’s Corona supercomputing cluster. Combining Sambanovaa’s system with LLNL’s supercomputing cluster to support efficient CogSim
Enabling a wider selection of workloads and expanding the possible use cases, the next stage of the collaboration allows for a less tightly integrated heterogeneous system. The aim of LLNL is to leverage AI to improve speed, energy efficiency, and data management.
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LLNL is leveraging a unique approach for CogSim offered by Sambanova’s architecture, which differs from CPU- or GPU-based systems, through the combination of Sambanova’s Datascale with their supercomputing clusters. The partnership between Sambanova and LLNL aims to solve complex scientific issues through speed, accuracy, and collaboration.
Sambanova’s agility, power, and flexibility contribute to the LLNL‘s mission of science in the national interest. LLNL’s adoption of Sambanova’s architecture highlights the need for a full-stack AI solution to address critical use cases in the scientific community.
The collaboration between Sambanova and LLNL demonstrates the opportunity to leverage AI to improve scientific research in terms of speed, accuracy, and data management. The introduction of Sambanova’s spatial data flow accelerator into LLNL’s Computing Center represents a significant advancement in scientific research capabilities. The website at Sambanova.ai can be visited for more information about cognitive simulation and the contribution of Sambanova Systems.
