Solutions for optimizing the performance of large-scale social simulations:
- Hardware Selection: At least A100 and other high-performance GPUs are required, and it is recommended to use a cloud computing platform for elastic capacity expansion.
- parameter tuning: Rationalization
OasisSimulatorParameters such as the number of intelligences (batch simulation is recommended), type of action, etc. in the - distributed computing: By
pip install camel-oasisInstallation of extension modules to support multi-node parallel computing - cluster of intelligencesHierarchical simulation architecture to manage 100,000+ intelligences in groups, reducing communication overheads
Tests show that the above method can increase the simulation speed of millions of intelligences by 3-5 times under the same hardware conditions. It is recommended to use the system's built-in performance monitoring tool to optimize resource allocation in real time.
This answer comes from the articleCAMEL-AI: An Open Source Framework for Building Multi-Intelligent Collaborative SystemsThe
May not be reproduced without permission:AI productivity tools " Addressing Performance Bottlenecks in CAMEL-AI Large-Scale Social Simulation
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