标题： RTGPU：使用图形处理单元的实时计算 显示英文标题

标题： RTGPU: Real-Time Computing with Graphics Processing Units

摘要： 在本工作中，我们调查了GPU在实时系统中的作用。 最初为并行图形工作负载设计，由于其高计算吞吐量，GPU现在被广泛用于时间关键的应用程序，如机器学习、自动驾驶汽车和机器人。 它们的并行架构非常适合在严格的定时约束下加速复杂任务。 然而，将它们集成到实时系统中带来了几个挑战，包括不可抢占的执行、执行时间的变化性和资源竞争；这些因素可能导致不可预测的延迟和截止时间违规。 我们检查了现有解决这些问题的方案，包括调度算法、资源管理技术和同步方法，并强调了改善GPU在实时环境中可预测性和性能的开放研究方向。 显示英文摘要

摘要： In this work, we survey the role of GPUs in real-time systems. Originally designed for parallel graphics workloads, GPUs are now widely used in time-critical applications such as machine learning, autonomous vehicles, and robotics due to their high computational throughput. Their parallel architecture is well-suited for accelerating complex tasks under strict timing constraints. However, their integration into real-time systems presents several challenges, including non-preemptive execution, execution time variability, and resource contention; factors that can lead to unpredictable delays and deadline violations. We examine existing solutions that address these challenges, including scheduling algorithms, resource management techniques, and synchronization methods, and highlight open research directions to improve GPU predictability and performance in real-time environments.