SHF:Small:Data Structures and Transactions for Emerging Nonvolatile Memory

无论是为了长期访问，还是为了从系统崩溃中恢复，需要持久保存的数据传统上都保存在磁盘和闪存驱动器上，这两种驱动器速度都很慢。在接下来的几年里，预计将以合理的价格广泛使用速度更快的持久性内存，这增加了文件系统可能被简单地“始终可用”的内存取代的可能性，至少在一定程度上如此。该项目在智力上的优点在于解决了这种“始终可用内存”的两个关键挑战：第一，确保系统崩溃后内存中的值始终相互一致，尽管传统高速缓存经常无序地将数据传递到内存；第二，保护持久数据的结构完整性，尽管有错误的程序可能会错误地修改任意内存位置。该项目更广泛的意义和重要性在于承诺显著改善可编程性、可靠性和系统性能，并能够以比以前低得多的成本经受住停电和硬件故障的考验。后一种好处可能对物联网中无处不在的传感器特别重要。该项目建立在主要研究人员和同事先前工作的基础上，他们已经为持久数据制定了正式的正确性标准，以及确保这种正确性的自动方法。目前的项目正在进行三个主要的研究推动力。首先，它正在开发一个可重复使用的高性能持久数据结构库，特别强调利用高级语义来最大限度地减少检测开销，维护足够的信息以在程序或系统崩溃后完成或撤消部分操作，以及形式化和证明正确性。其次，该项目正在开发将持久操作组合成更大的原子事务的技术。这项工作建立在过去硬件和软件事务内存经验的基础上，包括非阻塞和基于锁的方法。特别强调的是“增强”持久性数据结构的操作，以便它们可以充当事务系统的可逆高级操作。第三，该项目正在开发机制(包括用户级守护程序、基于编译器的沙箱、细粒度内存保护和使用虚拟化硬件)，以确保持久性数据仅由受信任的库代码修改，从而在存在缺陷的应用程序中保护其结构完整性。

Data that need to be persistent, either for the sake of long-term access or for recovery from system crashes, have traditionally been kept on disk and flash drives, which are very slow. Within the next few years, much faster persistent memory is expected to be widely available at reasonable cost, raising the possibility that file systems might be replaced, at least in part, by memory that is simply "always available." The intellectual merits of the project lie in addressing two key challenges to such "always available memory": first, ensuring that the values in memory in the wake of a system crash are always mutually consistent, despite the possibility that traditional caches often pass data to the memory out of order; second, safeguarding the structural integrity of persistent data despite the possibility that buggy programs may erroneously modify arbitrary memory locations. The project's broader significance and importance lie in the promise of significant improvements in programmability, reliability, and system performance, and in the ability to survive power outages and hardware failures at much lower cost than has previously been possible. This latter benefit may be of particular importance for ubiquitous sensors in the Internet of Things.The project builds on prior work by the principal investigator and colleagues, which has developed formal correctness criteria for persistent data, together with automatic methods to guarantee this correctness. The current project is pursuing three major research thrusts. First, it is developing a library of reusable, high-performance persistent data structures, with particular emphasis on exploiting high-level semantics to minimize instrumentation overhead, maintaining sufficient information to complete or undo partial operations in the wake of a program or system crash, and formalizing and proving correctness. Second, the project is developing techniques to compose persistent operations into larger atomic transactions. This work builds on past experience with hardware and software transactional memory, and encompasses both nonblocking and lock-based approaches. Particular emphasis is being placed on "boosting" the operations of persistent data structures so that they can serve as reversible high-level operations of a transactional system. Third, the project is developing mechanisms (including user-level daemons, compiler-based sandboxing, fine-grain memory protection, and the use of virtualization hardware) to ensure that persistent data is modified only by trusted library code, thereby safeguarding its structural integrity in the presence of buggy applications.