一句话：针对 GPU 多任务下共运行应用相互干扰导致公平性与 QoS 下降的问题，提出 HSM 机制。
论文关注 GPU 在云中加速计算密集型任务时的资源利用率问题。单应用独占 GPU 常导致资源利用不充分，因此采用多任务方式可提升利用率，但共运行应用之间会产生破坏性干扰，进而引发公平性问题并违反服务质量（QoS）要求。标题 HSM 暗示论文提出一种硬件或混合调度机制来应对该问题。然而，给出的摘要仅阐述了问题背景，未具体说明 HSM 的设计、实现方法与评估结果；因此其核心贡献需结合正文进一步确认。
Graphics Processing Units (GPUs) are increasingly widely used in the cloud to accelerate compute-heavy tasks. However, GPU-compute applications stress the GPU architecture in different ways --- leading to suboptimal resource utilization when a single GPU is used to run a single application. One solution is to use the GPU in a multitasking fashion to improve utilization. Unfortunately, multitasking leads to destructive interference between co-running applications which causes fairness issues and Quality-of-Service (QoS) violations.