Among the greatest component shortages bedeviling everyone is that of GPUs, both from Nvidia and AMD. GPUs are used in Bitcoin farming, and with massive farms around the world gobbling up every GPU card, getting one is nigh impossible or prohibitively expense.\nSo customers need to squeeze every last cycle out of the GPUs they have in service. An Israeli company called Run:AI claims it has a fix with a pair of technologies that pool GPU resources and maximize their use.\nThe technologies are called Thin GPU Provisioning and Job Swapping. Not the most creative of names but they describe what the two do in tandem to automate the allocation and utilization of GPUs.\nData scientists and other AI researchers often receive an allocation of GPUs, with the GPUs reserved for individuals to run their processes and no one else's. That\u2019s how high performance computing (HPC) and supercomputers operate, and getting processor allocation just right is something of a black art for administrators.\nWith Thin GPU Provisioning and Job Swapping, whenever a running workload is not utilizing its allocated GPUs, those resources are pooled and can be automatically provisioned for use by a different workload. It\u2019s similar to the thin provisioning first introduced by VMware for storage-area networks, where available storage disk space is allocated but not provisioned until necessary, according to a statement by Run:AI.\nThin GPU Provisioning creates over-provisioned GPUs, while Job Swapping uses preset priorities to reassign unused GPU capacity. Together, Run:AI says, the two technologies maximize overall GPU utilization.\nData Scientists, whose specialties aren\u2019t always technical, don\u2019t have to deal with scheduling and provisioning. At the same time, IT departments have control over GPU utilization across their networks, the company says.\n\u201cResearchers are no longer able to \u2018hug\u2019 GPUs\u2014making them unavailable for use by others,\u201d said Dr. Ronen Dar, CTO and co-founder of Run:AI in a statement. \u201cThey simply run their jobs and Run:AI\u2019s quota management, Thin GPU Provisioning and Job Swapping features seamlessly allocate resources efficiently without any user intervention.\u201d\nThin GPU Provisioning and Job Swapping are currently in testing in Run:AI customer labs. They are expected to be generally available in Q4 2021.\nRun:AI was founded in 2018 and has $43 million in funding.