This paper examines whether lossy compression can be used effectively in physics simulations as a possible strategy to combat the expected data-movement bottleneck in future high performance computing architectures. We show that, for the codes and simulations we tested, compression levels of 3–5X can be applied without causing significant changes to important physical quantities. Rather than applying signal processing error metrics, we utilize physics-based metrics appropriate for each code to assess the impact of compression. We evaluate three different simulation codes: a Lagrangian shock-hydrodynamics code, an Eulerian higher-order hydrodynamics turbulence modeling code, and an Eulerian coupled laser-plasma interaction code. We compress relevant quantities after each time-step to approximate the effects of tightly coupled compression and study the compression rates to estimate memory and disk-bandwidth reduction. We find that the error characteristics of compression algorithms must be carefully considered in the context of the underlying physics being modeled.

中文翻译：

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使用身体动力指标评估模拟中数据压缩的影响

本文探讨了有损压缩是否可以有效地用于物理模拟中，作为应对未来高性能计算体系结构中预期的数据移动瓶颈的一种可行策略。我们表明，对于我们测试的代码和模拟，可以应用3-5倍的压缩级别，而不会对重要的物理量造成显着变化。我们没有应用信号处理错误度量标准，而是利用适用于每个代码的基于物理的度量标准来评估压缩的影响。我们评估了三种不同的模拟代码：拉格朗日冲击流体力学代码，欧拉高阶流体动力学湍流建模代码和欧拉耦合激光-等离子体相互作用代码。我们在每个时间步长后压缩相关量，以近似估计紧密耦合压缩的效果，并研究压缩率以估计内存和磁盘带宽的减少。我们发现压缩算法的错误特征必须在被建模的基础物理环境中仔细考虑。