18075332. RECONFIGURABLE COMPUTING PODS USING OPTICAL NETWORKS simplified abstract (GOOGLE LLC)
RECONFIGURABLE COMPUTING PODS USING OPTICAL NETWORKS
Organization Name
Inventor(s)
Nishant Patil of Sunnyvale CA (US)
Xiang Zhou of Sunnyvale CA (US)
Andrew Swing of Los Gatos CA (US)
RECONFIGURABLE COMPUTING PODS USING OPTICAL NETWORKS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18075332 titled 'RECONFIGURABLE COMPUTING PODS USING OPTICAL NETWORKS
Simplified Explanation
The patent application describes a method, system, and apparatus for generating clusters of compute nodes using an optical network. The method involves receiving request data specifying the desired compute nodes for a computing workload and the target arrangement of these nodes. A selection is made from a set of building blocks, each containing a specific arrangement of compute nodes, that match the target arrangement. The building blocks are connected to an optical network with optical circuit switches. A workload cluster is then generated by combining the selected building blocks and configuring routing data for the optical circuit switches.
- The patent application proposes a method for generating clusters of compute nodes using an optical network.
- The method involves receiving request data specifying the desired compute nodes and their target arrangement.
- A selection is made from a set of building blocks, each containing a specific arrangement of compute nodes, that match the target arrangement.
- The building blocks are connected to an optical network with optical circuit switches.
- A workload cluster is generated by combining the selected building blocks and configuring routing data for the optical circuit switches.
Potential Applications
- High-performance computing: This technology can be used to efficiently generate clusters of compute nodes for high-performance computing tasks, such as scientific simulations or data analysis.
- Cloud computing: The method can be applied in cloud computing environments to dynamically create clusters of compute nodes based on user requests and workload requirements.
- Data centers: This technology can be utilized in data centers to optimize the arrangement and connectivity of compute nodes, improving overall performance and resource utilization.
Problems Solved
- Scalability: The method allows for the generation of clusters of compute nodes with a desired arrangement, enabling scalability and flexibility in computing environments.
- Efficient resource utilization: By selecting and combining building blocks that match the target arrangement, this technology optimizes the use of compute nodes and reduces resource wastage.
- Network connectivity: The use of an optical network with optical circuit switches improves the connectivity and communication between compute nodes, enhancing overall performance.
Benefits
- Flexibility: The method allows for the generation of clusters with a specific arrangement, providing flexibility in meeting different workload requirements.
- Scalability: By utilizing building blocks and an optical network, this technology enables the easy scaling of compute clusters based on workload demands.
- Improved performance: The use of an optical network and optimized connectivity enhances the performance and efficiency of compute clusters, leading to faster processing and reduced latency.
Original Abstract Submitted
Methods, systems, and apparatus, including an apparatus for generating clusters of building blocks of compute nodes using an optical network. In one aspect, a method includes receiving request data specifying requested compute nodes for a computing workload. The request data specifies a target n-dimensional arrangement of the compute nodes. A selection is made, from a superpod that includes a set of building blocks that each include an m-dimensional arrangement of compute nodes, a subset of the building blocks that, when combined, match the target n-dimensional arrangement specified by the request data. The set of building blocks are connected to an optical network that includes one or more optical circuit switches. A workload cluster of compute nodes that includes the subset of the building blocks is generated. The generating includes configuring, for each dimension of the workload cluster, respective routing data for the one or more optical circuit switches.
