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首页> 外文会议>Asilomar Conference on Signals, Systems and Computers >Run fast when you can: Loop pipelining with uncertain and non-uniform memory dependencies
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Run fast when you can: Loop pipelining with uncertain and non-uniform memory dependencies

机译：可以在可能的情况下快速运行：循环流水线具有不确定和不一致的内存依赖性

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摘要

As a key optimisation method in high-level synthesis (HLS), high-performance loop pipelining is enabled by the static scheduling algorithm. When there are non-trivial memory dependencies in the loop, current HLS tools have to apply conservative pipeline schedule that also leads to nearly sequential execution. In this paper, we demonstrate using parametric polyhedral model to mathematically capture uncertain (i.e., parameterised by an undetermined variable) and/or non-uniform (i.e., varying between loop iterations) memory dependence patterns. According to this static analysis, if we always execute the loop with an aggressive (fast) pipeline schedule, we can generate the parameter conditions in which this execution is safe and the parametric break points when the execution encounters memory conflicts. Then, we apply these information into an automated source-to-source code transformation, which implements parametric loop pipelining and loop splitting. The transformed loop is synthesised by Vivado HLS and its execution speed can be adjusted at runtime to avoid memory conflicts. The experiments over a set of benchmark loops show that our optimisation can improve the runtime pipeline performance significantly with a reasonable overhead of hardware resources.
机译：作为高级综合（HLS）中的关键优化方法，通过静态调度算法可以实现高性能循环流水线化。当循环中存在非平凡的内存依赖关系时，当前的HLS工具必须应用保守的流水线调度，这也将导致几乎连续的执行。在本文中，我们演示了使用参数多面体模型以数学方式捕获不确定性（即由不确定变量参数化）和/或非均匀性（即在循环迭代之间变化）的内存依赖模式。根据此静态分析，如果我们始终以积极的（快速）流水线计划执行循环，则可以生成参数条件，在该条件条件下此执行是安全的，并且在执行遇到内存冲突时可以使用参数断点。然后，我们将这些信息应用到自动的源到源代码转换中，该转换实现了参数化循环流水线和循环拆分。转换后的循环由Vivado HLS合成，可以在运行时调整其执行速度，以避免内存冲突。在一组基准循环上进行的实验表明，我们的优化可以在合理的硬件资源开销下显着提高运行时管道性能。

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