Scaling GPU-to-CPU Migration for Efficient Distributed Execution on CPU Clusters
Abstract
The growing demand for GPU resources has led to widespread shortages in data centers, prompting the exploration of CPUs as an alternative for executing GPU programs. While prior research supports executing GPU programs on single CPUs, these approaches struggle to achieve competitive performance due to the computational capacity gap between GPUs and CPUs.
Fields of Study & Subjects
Parallel Computing and Optimization Techniques
Distributed and Parallel Computing Systems
Cloud Computing and Resource Management
Publication details
- Journal / source
- ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
- Pages
- 355–368
- Publication date
- 28 January 2026