In-depth analyses of unified virtual memory system for GPU accelerated computing
Tyler Allen, Rong Ge
Abstract
The abstraction of a shared memory space over separate CPU and GPU memory domains has eased the burden of portability for many HPC codebases. However, users pay for the ease of use provided by systems-managed memory space with a moderate-to-high performance overhead. NVIDIA Unified Virtual Memory (UVM) is presently the primary real-world implementation of such abstraction and offers a functionally equivalent testbed for a novel in-depth performance study for both UVM and future Linux Heterogeneous Memory Management (HMM) compatible systems. The continued advocation for UVM and HMM motivates the improvement of the underlying system. We focus on a UVM-based system and investigate the root causes of the UVM overhead, which is a non-trivial task due to the complex interactions of multiple hardware and software constituents and the requirement of targeted analysis methodology.