XPS: EXPL: Write Locality Theory and Optimization for Hybrid Memory

极限规模计算的一个限制是内存的容量、速度、耐用性和最重要的能效。持久内存是一种颠覆性的技术，它极大地降低了内存成本和静态功耗，但也带来了写速度慢和写持久性有限的问题。一个有效的解决方案是缓存。然而，现有的缓存是为快速读取而设计的：它们不能最大限度地减少从缓存到内存的回写次数。这个项目的智力优势在于，在未来使用持久内存的系统中，有足够的理论和有效的技术来优化写缓存。在软件和硬件中，缓存越来越普遍。硬件缓存服务于商用机器和超级计算机上的大部分内存访问。软件缓存，例如维基百科和Facebook使用的Memcached，为在线用户的大部分数据请求提供服务。该项目更广泛的意义和重要性是缓存优化在科学和消费者计算中的广泛好处。本项目发展了写局部性的正式概念，以及描述局部性和优化缓存的理论和技术。它有三部分。第一个是写局部性建模，它包括一组度量，这些度量可以导出缓存中修改数据的数量，以及所有大小和共享程度的缓存中从缓存到内存的写回。第二种是演绎优化，它从数学上推导出不同任务和数据组织的缓存性能，并从组合数量的选择中选择最佳解决方案。最后是系统建模和应用优化，利用写局部性对软件和硬件缓存进行建模，并对程序进行优化。

A limit on extreme scale computing is the capacity, speed, durability and most importantly, energy efficiency of memory. Persistent memory is a disruptive technology that drastically reduces memory cost and static power but introduces the problems of slow writes and limited write endurance. An effective solution is caching. However, existing caches have been designed for fast reads: they do not minimize the number of write backs from cache to memory. The intellectual merits of this project are sufficient theories and efficient techniques for optimal write caching in future systems that use persistent memory. Caching, in both software and hardware, is increasingly prevalent. Hardware caches serve most of the memory accesses on commodity machines as well as super computers. Software caches, e.g. Memcached used by Wikipedia and Facebook, serve most of the data requests from online users. The project's broader significance and importance are the broad benefits of cache optimization in scientific and consumer computing.This project develops the formal concept of write locality and the theory and techniques to characterize locality and optimize the cache. It has three parts. The first is write locality modeling, which includes a set of metrics that can derive the amount of modified data in cache and the write backs from cache to memory in cache of all sizes and degrees of sharing. The second is deductive optimization, which mathematically derives the cache performance of different task and data organizations and selects the best solution among a combinatorial number of choices. The last is system modeling and application optimization, which use write locality to model software and hardware cache and to optimize a program.