Using Bandwidth Throttling to Quantify Application Sensitivity to Heterogeneous Memory

International audiencen the dawn of the exascale era, the memory management is getting increasingly harder but also of primary importance. The plurality of processing systems along with the emergence of heterogeneous memory systems require more care to be put into data placement. Yet, in order to test models, designs and heuristics for data placement, the programmer has to be able to access these expensive systems, or find a way to emulate them.In this paper we propose to use the Resource Control features of the Linux kernel and x86 processors to add heterogeneity to a homogeneous memory system in order to evaluate the impact of different bandwidths on application performance. We define a new metric to evaluate the sensibility to bandwidth throttling as a way to investigate the benefits of using high-bandwidth memory (HBM) for any given application, without the need to access a platform offering this kind of memory. We evaluated 6 different well-known benchmarks with different sensitivity to bandwidth on a AMD platform, and validated our results on two Intel platforms with heterogeneous memory, Xeon Phi and Xeon with NVDIMMs. Although representing an idealized version of HBM, our method gives reliable insight of potential gains when using HBM.Finally, we envision a design based on Resource Control using both bandwidth restriction and cache partitioning to simulate a more complex heterogeneous environment that allows for hand-picked data placement on emulated heterogeneous memory. We believe our approach can help develop new tools to test reliably new algorithms that improve data placement for heterogeneous memory systems