发表机构
EPFL（洛桑联邦理工学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
ThreadShift利用MPK实现线程级透明卸载，支持细粒度检查点，在瞬时云资源上降低成本达56%，检查点速度比CRIU快三个数量级。
AI 中文摘要
瞬时云资源可显著节省成本，但其不可预测性使其难以用于在资源回收后无法安全重启的应用程序。现有方法需要修改应用程序或依赖粗粒度的检查点，其成本限制了收益。我们提出了ThreadShift，一个能够透明地将未修改的Linux应用程序的计算密集型线程卸载到廉价瞬时资源，并在资源回收时保持正确性的系统。通过在线程粒度上操作，ThreadShift实现了快速、细粒度的检查点，并且只卸载那些能从瞬时执行中受益的线程。主要挑战是在存在跨线程依赖的情况下对单个线程进行检查点。ThreadShift通过高效跟踪内存依赖、识别每线程内存写入并维护跨机器的一致性来解决这一问题。内存保护密钥（MPKs）的三项新用途使这些机制高效，能够在不暂停整个应用程序的情况下实现快速增量检查点。我们在x86-64 Linux上实现了ThreadShift，并在包括机器学习推理、密码任务和内存数据处理等工作负载上进行了评估。ThreadShift在低至164微秒内卸载线程，检查点速度比CRIU快多达三个数量级，并在商用云上将部署成本降低高达56%。
英文摘要
Transient cloud resources offer significant cost savings, but their unpredictability makes them hard to use for applications that cannot be safely restarted after reclamation. Existing approaches require application changes or rely on coarse-grained checkpointing, whose cost limits its benefits. We present ThreadShift, a system that transparently offloads compute-intensive threads of unmodified Linux applications to cheap transient resources while preserving correctness under reclamation. By operating at thread granularity, ThreadShift enables fast, fine-grained checkpointing and offloads only the threads that benefit from transient execution. The main challenge is to checkpoint individual threads despite cross-thread dependencies. ThreadShift does so by efficiently tracking memory dependencies, identifying per-thread memory writes, and maintaining coherence across machines. Three novel uses of Memory Protection Keys (MPKs) make these mechanisms efficient, enabling fast incremental checkpoints without pausing the entire application. We implement ThreadShift on x86-64 Linux and evaluate it on workloads including machine-learning inference, cryptographic tasks, and in-memory data processing. ThreadShift offloads threads in as little as 164 us, performs checkpointing up to three orders of magnitude faster than CRIU, and reduces deployment cost by up to 56% on commodity clouds.
