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GPGPUs (General Purpose Graphic Processing Units) provide massive computational power. However, applying GPGPU technology to real-time computing is challenging due to the non-preemptive nature of GPGPUs. Especially, a job running in a GPGPU or a data copy between a GPGPU and CPU is non-preemptive. As a result, a high priority job arriving in the middle of a low priority job execution or memory copy suffers from priority inversion. To address the problem, the authors present a new lightweight approach to supporting preemptive memory copies and job executions in GPG- PUs. Moreover, in their approach, a GPGPU job and memory copy between a GPGPU and the hosting CPU are run concurrently to enhance the responsiveness.
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