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Static Analysis of the Worst-Case Memory Performance for Irregular Codes with Indirections

机译:带有间接指令的不规则代码的最坏情况下内存性能的静态分析

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Real-time systems are subject to timing constraints, whose upper bound is given by the Worst-Case Execution Time (WCET). Cache memory behavior is difficult to predict analytically and estimating a safe and precise worst-case value is even more challenging. The worst-case memory performance (WCMP) component of the WCET can only be estimated with the precise knowledge of the stream of data addresses accessed by the code, which is determined by the access patterns and the base addresses of the data structures accessed. The regularity of strided access patterns simplifies their analysis, as they are characterized by relatively few parameters, which are often available at compile time. Unfortunately codes may exhibit irregular access patterns, which are much more difficult to statically analyze. As for the base addresses of the data structures, they are not always available at compile-time for many reasons: stack variables, dynamically allocated memory, modules compiled separately, etc. This article addresses these problems by presenting a model that predicts an upper bound of the data cache performance for codes both with regular and irregular access patterns, which is valid for any possible base addresses of the data structures. The model analyzes irregular access patterns due to the presence of indirections in the code and it can provide two kinds of predictions: a safe hard boundary that is suitable for hard real-time systems and a soft boundary whose safeness is not guaranteed but which is valid most of the times. In fact, in all our experiments the number of misses was below the soft boundary predicted by the model. This turns this soft boundary prediction into a valuable tool, particularly for non and soft real-time systems, which tolerate a percentage of the runs exceeding their deadlines.
机译:实时系统受时序约束,其上限由最坏情况执行时间(WCET)给出。高速缓存的行为很难通过分析来预测,而估计安全且精确的最坏情况值则更具挑战性。 WCET的最坏情况下的内存性能(WCMP)组件只能在对代码访问的数据地址流有确切了解的情况下才能估算出来,该知识由访问模式和访问的数据结构的基址确定。跨步访问模式的规则性简化了它们的分析,因为它们具有相对较少的参数,这些参数通常在编译时可用。不幸的是,代码可能会表现出不规则的访问模式,这将使静态分析更加困难。至于数据结构的基地址,由于许多原因,它们在编译时并不总是可用:堆栈变量,动态分配的内存,单独编译的模块等。本文通过提供一个预测上限的模型来解决这些问题。具有规则访问模式和不规则访问模式的代码的数据高速缓存性能的平均值,这对于数据结构的任何可能的基地址均有效。该模型分析了由于代码中存在间接导致的不规则访问模式,它可以提供两种预测:适用于硬实时系统的安全硬边界和不能保证安全但有效的软边界大部分的时间。实际上,在我们所有的实验中,未命中次数均低于模型所预测的软边界。这将这种软边界预测变成了一个有价值的工具,尤其是对于非实时和软实时系统而言,该系统可以忍受一定比例的运行超出其最终期限。

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