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Found 4 papers, 2 papers with code
TACCL: Guiding Collective Algorithm Synthesis using Communication Sketches
TACCL uses a novel communication sketch abstraction to get crucial information from the designer to significantly reduce the search space and guide the synthesizer towards better algorithms.
Cloud Collectives: Towards Cloud-aware Collectives forML Workloads with Rank Reordering
ML workloads are becoming increasingly popular in the cloud.
Scaling Distributed Machine Learning with In-Network Aggregation
Training machine learning models in parallel is an increasingly important workload.
Parameter Hub: a Rack-Scale Parameter Server for Distributed Deep Neural Network Training
Distributed deep neural network (DDNN) training constitutes an increasingly important workload that frequently runs in the cloud.
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