Manage, freeze and restore GPU processes quickly (github.com)

A new project called gpusched has been launched, allowing users to manage GPU processes with unprecedented speed and efficiency. This tool enables freezing and restoring GPU processes in milliseconds, significantly reducing the overhead associated with loading large language models (LLMs) from scratch, which typically takes 15-30 seconds. By utilizing NVIDIA's cuda-checkpoint, gpusched temporarily moves a process's VRAM to host RAM and then frees up the GPU, making it available for other tasks. If necessary, older snapshots can also be evicted to disk, with processes that can be resumed quickly when needed. This development is particularly significant for the AI and ML community, as it optimizes GPU resource management, which is critical for high-performance computing environments. The current implementation demonstrates impressive freeze and thaw times, showcasing a reduction in load time by 25-30 times compared to traditional methods. Gpusched features a terminal dashboard for real-time monitoring and allows operations such as freezing, thawing, and migrating processes seamlessly. Future enhancements could include an HTTP API for remote control, integration with Kubernetes, and improved eviction policies, promising to make GPU resource management even more robust and user-friendly.