3 citations · 5 across the 5 of their papers we have counts for
3 papers · 1 filter
TRANSIT: Transparent Scale-in for Multi-Node LLM Training
Hyungyo Kim, Nicholas Satchanov, Hrishi Shah +9
TRANSIT is a transparent scale-in framework to enable multi-node model training on fewer GPUs while maintaining training efficiency by transparently leveraging CPU DRAM as an exten…
Chameleon: Adaptive Caching and Scheduling for Many-Adapter LLM Inference Environments
Nikoleta Iliakopoulou, Jovan Stojkovic, Chloe Alverti +3
The widespread adoption of LLMs has driven an exponential rise in their deployment, imposing substantial demands on inference clusters. These clusters must handle numerous concurre…
Transforming the Hybrid Cloud for Emerging AI Workloads
Deming Chen, Alaa Youssef, Ruchi Pendse +42
This white paper, developed through close collaboration between IBM Research and UIUC researchers within the IIDAI Institute, envisions transforming hybrid cloud systems to meet th…