SHF: Small: Multicore Data-Structures: Relaxed, Flat, and Randomized

目前在并行软件中设计和使用的大多数多核数据结构都是过去顺序数据结构的并发版本。 它们继续工作得相当好，因为主流多核机器提供的并行级别仍然很低。 然而，随着机器规模的增长，这些传统结构的局限性将变得明显：它们具有固有的顺序瓶颈，需要严格的同步，并且不容易分布。 该项目将开发新的并行数据结构，将联合收割机宽松的规范与高度分散的随机实现相结合，克服现有结构的缺点，并提供更好的适应未来的大规模并行众核机器设计。这项研究将结合联合收割机的理论算法工作与经验评估的真实的机器和应用程序，并将导致在一个图书馆的并发数据结构和收集的设计方法和规范方法。商业软件开发人员迫切需要可扩展的数据结构，同时仍然易于理解和修改。使这个项目开发的结构广泛可用，将极大地有助于使未来的应用程序，无论是在手机上还是在云中的服务器上运行，充分利用多核技术提供的并行性。

Most multicore data structures being designed and used in parallel software today are concurrent versions of the sequential data structures of years past. They continue to work reasonably well because the level of parallelism offered by mainstream multicore machines is still low. As machines grow in size, however, the limitations of these traditional structures will become clear: they have inherent sequential bottlenecks, require tight synchronization, and are not easily distributed. This project will develop new classes of parallel data structures that combine relaxed specifications with highly decentralized randomized implementations, overcoming the drawbacks of existing structures and providing a better fit with tomorrow's massively parallel many-core machine designs. This research will combine theoretical algorithmic work with empirical evaluation on real machines and applications, and will result in a library of concurrent data structures and a collection of design approaches and specification methodologies. Commercial software developers are in desperate need of data structures that scale while still remaining easy to understand and modify. Making this project's developed structures widely available will greatly help in making tomorrow's applications, whether they run on a cell phone or on a server in the cloud, make full use of the parallelism offered by multicore technology.