RUI: Chaos in Computer Memories

最近发表的结果表明，分形几何可以有效地用来模拟处理器产生的存储器访问模式所表现出的偏度和自相似程度。分形模型可用于预测存储器层次结构的许多级别上的程序的行为，并且这些级别的性能又可被预测，这一事实意味着存储器访问模式是高度结构化的。不幸的是，这种结构也是高度不规则的，已经提出的用于模拟程序行为的绝大多数模型必须依赖于访问一致性和/或访问独立性的过度简化和不切实际的假设。一些初步结果表明，在某些情况下，特别是当进程分配的缓存空间太少时，其内存访问模式会导致缓存中的混乱，从而产生较差的缓存性能。本研究调查了混沌产生的条件，缓存设计参数如何影响它，混沌行为如何影响缓存性能，并将这些结果应用于线程和缓存分区，这两种方法为混沌的出现提供了潜在的有利条件。

Recent published results show that fractal geometry can be effectively used to model the skewness and degree of self- similarity exhibited by the memory-access patterns generated by processors. The fact that the fractal model can be used to predict the behavior of programs at many levels of the memory hierarchy, and that the performance of those levels can be in turn predicted, implies that memory access patterns are highly structured. Unfortunately, this structure is also highly irregular, and the vast majority of models that have been proposed to simulate program behavior must rely on over-simplifying and unrealistic assumptions of uniformity of access and/or of independence of access. Some preliminary results show that under some conditions, in particular when a process is allocated too little cache storage, its memory access pattern results in chaos in the cache, yielding poor cache performance. This research investigates the conditions under which chaos occurs, how cache design parameters influence it, how chaotic behavior influences cache performance, and applies these results to threading and cache partitioning, two methodologies that present potentially favorable conditions for chaos to appear.