Portable application guidance for complex memory systems

The recent emergence of new memory technologies and multi-tier memory architectures has disrupted the traditional view of memory as a single block of volatile storage with uniform performance. Several options for managing data on heterogeneous memory platforms now exist, but current approaches either rely on inflexible, and often inefficient, hardware-based caching, or they require expert knowledge and source code modification to utilize the different performance and capabilities within each memory tier. This paper introduces a new software-based framework to collect and apply memory management guidance for applications on heterogeneous memory platforms. The framework, together with new tools, combines a generic runtime API with automated program profiling and analysis to achieve data management that is both efficient and portable across multiple memory architectures. To validate this combined software approach, we deployed it on two real-world heterogeneous memory platforms: 1) an Intel^® Cascade Lake platform with conventional DDR4 alongside nonvolatile Optane^TM DC memory with large capacity, and 2) an Intel^® Knights Landing platform high-bandwidth, but limited capacity, MCDRAM backed by DDR4 SDRAM. We tested our approach on these platforms using three scientific mini-applications (LULESH, AMG, and SNAP) as well as one scalable scientific application (QMCPACK) from the CORAL benchmark suite. The experiments show that portable application guidance has potential to improve performance significantly, especially on the Cascade Lake platform – which achieved peak speedups of 22x and 7.8x over the default unguided software- and hardware-based management policies. Additionally, this work evaluates the impact of various factors on the effectiveness of memory usage guidance, including: the amount of capacity that is available in the high performance tier, the input that is used during program profiling, and whether the profiling was conducted on the same architecture or transferred from a machine with a different architecture.