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Towards Resource-Efficient Compound AI Systems
We propose a vision for resource-efficient Compound AI Systems through a declarative workflow programming model and an adaptive runtime system for dynamic scheduling and resource-aware decision-making.
Treehouse: A Case For Carbon-Aware Datacenter Software
The end of Dennard scaling and the slowing of Moore's Law has put the energy use of datacenters on an unsustainable path.
Efficient Strong Scaling Through Burst Parallel Training
As emerging deep neural network (DNN) models continue to grow in size, using large GPU clusters to train DNNs is becoming an essential requirement to achieving acceptable training times.
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