SHF: Small: Collaborative Research: Concurrent Programming with Composable Transactional Objects

SHF：小号：合作研究：随着多核体系结构的日益普及，构建可扩展的高效并发软件的问题越来越受到关注。 人们对编程模型越来越感兴趣，编程模型允许程序员划分线程代码的区域-所谓的事务-当从其他线程的角度来看时，这些线程代码应该以原子的方式发生，这个项目的前提是当前的单片软件事务存储器（STM）设计固有地效率太低，并且允许太少的并行性。 相反，我们提出了一个非常不同的方法：一个定制的并发数据结构库，可以组成，通过一个非常轻量级的运行时，形成事务。 每个数据结构都经过优化，以利用其类型的语义。 智能的优点是新的类型特定的同步和恢复算法的发展，沿着正式的工具，以理由对他们的正确性。 这些想法将体现在一个新的并发库和验证工具包，这将被用来构建基准和应用程序。 更广泛的影响包括将并发纳入教育，以及通过更高性能，更可靠和更便宜的软件造福社会的潜力。

SHF: Small: Collaborative Research: Concurrent Programming with Composable Transactional ObjectsWith multicore architectures becoming increasingly prevalent, the problem of constructing scalable and efficient concurrent software has attracted increasing attention. There has been growing interest in programming models that allow programmers to demarcate regions of thread code---so-called transactions---that should appear to occur atomically, when viewed from the perspective of other threads.The premise of this project is that current, monolithic software transactional memory (STM) designs are inherently too inefficient and permit too little parallelism. Instead we propose a very different approach: a library of customized concurrent data structures that can be composed, through a very light-weight run-time, to form transactions. Each data structure is optimized to exploit the semantics of its type. The intellectual merits are the development of new type-specific synchronization and recovery algorithms, along with formal tools to reason about their correctness. These ideas will be embodied in a novel concurrency library and verification toolkit, which will be used to construct benchmarks and applications. The boarder impacts involve incorporating concurrency into education and the potential to benefit society through higher performing, more reliable, and less expensive software.