Gurobi Compute Server simplifies the deployment of high-performance optimization applications across multiple servers. It allows users to seamlessly offload optimization computations onto one or more dedicated optimization servers grouped in a cluster. The software facilitates the building and deployment of modern optimization applications with advanced queuing, load balancing, monitoring, and management capabilities. The Compute Server integrates with existing interfaces, enabling users to write a single program that can run locally or offload computations to one or more servers. It supports multiple platforms, including Windows, Linux, and Mac, and clients do not need to run the same operating system as the server. Licensing is straightforward, as a Compute Server can support an unlimited number of clients without requiring client licenses. Gurobi Compute Server offers flexible deployment options, allowing users to run it on their own servers or in the cloud. Licenses can be purchased for use on personal servers, Gurobi Instant Cloud, or a combination of both. The software supports distributed optimization, with algorithms like Distributed MIP, Distributed Concurrent, and Distributed Tuning. Distributed MIP enables multiple machines to work together to solve a single MIP model, while Distributed Concurrent uses different algorithmic strategies to race to solve an LP or MIP model. Distributed Tuning utilizes multiple machines to find parameter settings that improve performance.

Features

• **Seamless Integration **Allows users to write a single program to run locally or offload computations to one or more Gurobi Compute Servers using existing interfaces.
• **Support for Multiple Platforms **Runs on Windows, Linux, and Mac, with clients not required to use the same operating system as the server.
• **Straightforward Licensing **A Compute Server supports an unlimited number of clients without client licenses.
• **Distributed Optimization **Offers three distributed algorithms: Distributed MIP, Distributed Concurrent, and Distributed Tuning, to improve performance.