10 citations · 11 across the 5 of their papers we have counts for
5 papers · 1 filter
Cost-Efficient LLM Training with Lifetime-Aware Tensor Offloading via GPUDirect Storage
Ziqi Yuan, Haoyang Zhang, Yirui Eric Zhou +4
We present the design and implementation of a new lifetime-aware tensor offloading framework for GPU memory expansion using low-cost PCIe-based solid-state drives (SSDs). Our frame…
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…
The infrastructure powering IBM's Gen AI model development
Talia Gershon, Seetharami Seelam, Brian Belgodere +143
AI Infrastructure plays a key role in the speed and cost-competitiveness of developing and deploying advanced AI models. The current demand for powerful AI infrastructure for model…
Objcache: An Elastic Filesystem over External Persistent Storage for Container Clusters
Takeshi Yoshimura, Tatsuhiro Chiba, Sunyanan Choochotkaew +3
Container virtualization enables emerging AI workloads such as model serving, highly parallelized training, machine learning pipelines, and so on, to be easily scaled on demand on…
IBM Deep Learning Service
Bishwaranjan Bhattacharjee, Scott Boag, Chandani Doshi +15
Deep learning driven by large neural network models is overtaking traditional machine learning methods for understanding unstructured and perceptual data domains such as speech, te…