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Found 2 papers, 1 papers with code
Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach
Driven by the technological trend, this paper focuses on hierarchical resource partitioning on modern GPUs, and as an example, we utilize a combination of two different features available on recent NVIDIA GPUs in a hierarchical manner: MPS (Multi-Process Service), a finer-grained logical partitioning; and MIG (Multi-Instance GPU), a coarse-grained physical partitioning.
Federated Learning via Decentralized Dataset Distillation in Resource-Constrained Edge Environments
In federated learning, all networked clients contribute to the model training cooperatively.
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