Source URL: https://www.theregister.com/2024/11/18/llnl_oxide_compute/
Source: The Register
Title: LLNL looks to make HPC a little cloudier with Oxide’s rackscale compute platform
Feedly Summary: System to serve as a proof of concept for applying API-driven automation to scientific computing
SC24 Oxide Computing’s 2,500 pound (1.1 metric ton) rackscale blade servers are getting a new home at the Department of Energy’s Lawrence Livermore National Laboratory (LNLL).…
AI Summary and Description: Yes
Summary: The text describes a partnership between Oxide Computing and Lawrence Livermore National Laboratory (LLNL) involving innovative rackscale blade servers that adopt a cloud-oriented approach for high-performance computing (HPC). This deployment may redefine how research environments manage compute resources, emphasizing API-driven virtualization and user-specific resource allocation.
Detailed Description:
The text focuses on the deployment of Oxide Computing’s novel rackscale blade servers at LLNL, highlighting their innovative architecture and potential implications for cloud computing and HPC environments. Here are the key points:
– **Novel Hardware Design**: Oxide’s servers utilize an integrated backplane and chassis design, differing from the traditional rack configurations. Each unit hosts 32 compute nodes, eliminating the need for extensive cabling and enhancing connectivity.
– **Performance Specifications**: The full rack configuration features:
– 2048 AMD Epyc cores
– 16TB of RAM
– NVMe storage capabilities
– A power draw of up to 15 kilowatts
– **Custom Hardware and Software**:
– Oxide has developed its own baseboard management controller (BMC) and operates on a Rust-based operating system named Hubris, moving away from standard solutions like ASpeed BMC.
– The architecture is intended to support new user-facing services, indicating a shift towards more flexible and dynamic HPC environments.
– **API-Driven Virtualization**: The lab aims to implement an API-driven strategy that supports automation, deployment, and management of virtualized services, which can help streamline operations and improve user experience.
– **Potential for Modularity and Security**:
– The ability to silo users within the rack is highlighted as a key advantage, potentially allowing more secure and isolated computing environments.
– Current constraints due to rigid network zoning may be mitigated through the proposed fully virtualized systems discussed by Gamblin.
– **Future Exploration of GPU Integration**: While GPUs are not part of the current setup, Oxide is exploring their integration to enhance computational capabilities.
– **Broader Impact on Research Labs**:
– The deployment at LLNL is not isolated; it will be accessible to researchers at Los Alamos and Sandia National Labs, promoting collaborative research and enhancing disaster recovery capabilities across multiple locations.
– **Open Source Advantage**: The open-source nature of Oxide’s stack fosters deeper integration and facilitates future improvements in the virtualization architecture.
Overall, this text is particularly significant for professionals in AI, cloud, and infrastructure security domains as it illustrates how emerging technologies can redefine resource management and security protocols in high-performance computing environments. The flexible, API-driven approach sets a foundation for more dynamic and secure computing infrastructures that could influence future enterprise solutions.