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首页> 外文会议>IEEE International Symposium on Rapid System Prototyping >Simulation driven insertion of data prefetching instructions for early software-on-SoC optimization
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Simulation driven insertion of data prefetching instructions for early software-on-SoC optimization

机译：仿真驱动的数据预取指令的插入，以实现SoC上的早期软件优化

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摘要

A System-On-Chip (SoC) is a combination of hardware and software which interact to perform a set of functions, usually for some specific application domain. However, with the increasing complexity of both hardware and software, estimating and optimizing the performance of software on SoC during the design process is becoming a difficult objective. The aim of this paper is to show that observability provided by cycle accurate (CA) simulations using virtual platforms available early in the design flow is helping to obtain estimations and to design a software strategy which optimizes software-on-SoC performance, based on some particular metrics. We apply this approach to a case study which tackles the memory wall problem and contributes to its resolution by using software data prefetching technique. We exploit profiling capabilities provided by simulation models, by analyzing the collected data to identify high memory accesses latencies and finally inserting data prefetching instructions in a suitable and non-intuitive way for increasing system execution performance. Bubble sort is used as experimental methodology and the Inverse Discrete Cosine Transform (JPEG IDCT) routine typical from an industrial decoder is used as initial case study. Based on platform simulation observability, we reach an improvement of more than 25% on the overall execution time.
机译：片上系统（SoC）是硬件和软件的组合，它们相互作用以执行一组功能，通常用于某些特定的应用程序域。但是，随着硬件和软件的复杂性越来越高，在设计过程中估计和优化SoC上软件的性能已成为一个困难的目标。本文的目的是证明使用某些设计流程早期可用的虚拟平台进行的周期精确（CA）仿真所提供的可观察性，有助于基于某些特性来获得估计值，并设计出一种优化SoC上软件性能的软件策略。特定指标。我们将此方法应用于解决内存墙问题并通过使用软件数据预取技术为其解决做出贡献的案例研究。我们通过分析收集的数据以识别高内存访问延迟，并最终以合适且非直观的方式插入数据预取指令来提高系统执行性能，从而利用仿真模型提供的性能分析功能。气泡排序用作实验方法，工业解码器中典型的逆余弦逆变换（JPEG IDCT）例程用作初始案例研究。基于平台仿真的可观察性，我们将整体执行时间提高了25％以上。

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