ULCC: a user-level facility for optimizing shared cache performance on multicores
ULCC: a user-level facility for optimizing shared cache performance on multicores
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DOI：
10.1145/1941553.1941568
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发表时间：
2011-02
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通讯作者：
Xiaoning Ding;Kaibo Wang;Xiaodong Zhang
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作者：
Xiaoning Ding;Kaibo Wang;Xiaodong Zhang
科学应用程序在多核处理器上面临严重的性能挑战，其中之一是由多个运行的线程在末级共享缓存中的访问竞争造成的。争用增加了长等待时间存储器访问的数量，从而增加了应用程序的执行时间。优化共享缓存性能对于显著减少多核上多线程程序的执行时间至关重要。然而，在用户级别的多核上实施缓存优化技术之前，有两个独特的问题需要解决。首先，由于共享空间中的访问竞争，很难预测末级缓存中每个正在运行的线程的可用缓存空间，这使得针对单核的缓存感知算法在多核上无效。其次，在用户级，程序员无法随意地为共享缓存中运行的线程分配缓存空间，因此局部性强的数据集可能得不到足够的缓存空间，容易发生缓存污染。为了解决这两个关键问题，我们设计了ULCC(用户级缓存控制)，这是一个软件运行库，使程序员能够通过为不同线程的不同数据集分配适当的缓存空间来显式管理和优化末级缓存使用。我们基于页面着色技术在用户级实现了ULCC，用于末级缓存使用管理。通过对英特尔多核处理器的多个案例研究，我们表明，通过使用ULCC，科学应用程序可以通过充分利用缓存优化算法的优势并相应地对缓存空间进行分区来保护频繁重复使用的数据集和避免缓存污染，从而实现显著的性能改进。我们在不同应用程序上的实验表明，ULCC可以显著提高应用程序性能近40%。
Scientific applications face serious performance challenges on multicore processors, one of which is caused by access contention in last level shared caches from multiple running threads. The contention increases the number of long latency memory accesses, and consequently increases application execution times. Optimizing shared cache performance is critical to reduce significantly execution times of multi-threaded programs on multicores. However, there are two unique problems to be solved before implementing cache optimization techniques on multicores at the user level. First, available cache space for each running thread in a last level cache is difficult to predict due to access contention in the shared space, which makes cache conscious algorithms for single cores ineffective on multicores. Second, at the user level, programmers are not able to allocate cache space at will to running threads in the shared cache, thus data sets with strong locality may not be allocated with sufficient cache space, and cache pollution can easily happen. To address these two critical issues, we have designed ULCC (User Level Cache Control), a software runtime library that enables programmers to explicitly manage and optimize last level cache usage by allocating proper cache space for different data sets of different threads. We have implemented ULCC at the user level based on a page-coloring technique for last level cache usage management. By means of multiple case studies on an Intel multicore processor, we show that with ULCC, scientific applications can achieve significant performance improvements by fully exploiting the benefit of cache optimization algorithms and by partitioning the cache space accordingly to protect frequently reused data sets and to avoid cache pollution. Our experiments with various applications show that ULCC can significantly improve application performance by nearly 40%.