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Unified Virtual Memory (UVM) was recently introduced on recent NVIDIA GPUs.Through software and hardware support, UVM provides a coherent shared memoryacross the entire heterogeneous node, migrating data as appropriate. The olderCUDA programming style is akin to older large-memory UNIX applications whichused to directly load and unload memory segments. Newer CUDA programs havestarted taking advantage of UVM for the same reasons of superiorprogrammability that UNIX applications long ago switched to assuming thepresence of virtual memory. Therefore, checkpointing of UVM will becomeincreasingly important, especially as NVIDIA CUDA continues to gain widerpopularity: 87 of the top 500 supercomputers in the latest listings areGPU-accelerated, with a current trend of ten additional GPU-basedsupercomputers each year.  A new scalable checkpointing mechanism, CRUM (Checkpoint-Restart for UnifiedMemory), is demonstrated for hybrid CUDA/MPI computations across multiplecomputer nodes. CRUM supports a fast, forked checkpointing, which mostlyoverlaps the CUDA computation with storage of the checkpoint image in stablestorage. The runtime overhead of using CRUM is 6% on average, and the time forforked checkpointing is seen to be a factor of up to 40 times less thantraditional, synchronous checkpointing.

CRUM: Checkpoint-Restart Support for CUDA's Unified Memory