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M&MMs: Navigating complex memory spaces with hwloc

Abstract:

The complexity of the memory system has increased dramatically in the last decade. As a result, high-performance computers include multi-level, heterogeneous, and non-uniform memories, each with significantly different properties. For example, a memory system nowadays may include three types of memory: low-latency memory (DDR), high-bandwidth memory (HBM), and high-capacity memory (NVM)śnot to mention multiple NUMA domains. Because of their significantly different characteristics and number, scientific application developers face a tremendous challenge: Leverage the memory system effectively to improve performance and productivity. In this work, we present M&MMs, an interface to help manage the memory system complexity. It is comprised of a set of memory attributes and an API to express and manage the diverse memory characteristics using high-level metrics that are easy to understand. Our goal is to establish a building block to enable next-generation runtime systems, computing libraries, and scientific applications to leverage the best performance attributes of each memory, e.g., leverage the bandwidth of the fastest memory with the capacity of the largest memory. We believe M&MMs is a natural extension of hwlocśthat focuses on the memory systemśsince hwloc exposes the locality of the hardware resources and it is the de facto standard for hardware topology discovery.