Heterogeneity is ubiquitous, not only in terms of processing units but also memories and networks. As heterogeneity increases, memory subsystems play an even more important role to attain performance, from their technology to the system architecture to the software management and programming model. While CPU-only compute nodes are becoming rare instances, heterogeneous memory architectures have recently emerged and revolutionized the traditional memory hierarchy. Today’s and upcoming architectures may well comprise multiple memory technologies next to DRAM, accelerators with dedicated memories, or even specific expansion cards hosting memory alone, such as: 3D-stacked memory, high-bandwidth multi-channel RAM, unified/shared memory on accelerators, Compute Express Link (CXL)-based architectures, persistent memory, or MRDIMMs.

As in previous years, the Workshop on Heterogeneous Memory Systems, now rebranded as Heterogeneity and Memory Systems (HMEM), will bring together different research efforts and expertise to the end of integrating different approaches and democratizing the use of resource heterogeneity from a memory perspective, to benefit applications not only in terms of performance, but also energy efficiency and cost trade-offs. The main goal of the workshop is to push the research frontiers forward by exchanging knowledge and debating ideas through featured talks, technical paper presentations, and interactive discussions. Overall, topics of interest include, but are not limited to:

Resource heterogeneity (e.g., accelerators) and memory implications, including memory designs, data layouts, etc.
Data allocation and placement techniques in heterogeneous memory systems
Caching for heterogeneous memory systems
Programming models and tools for complex/heterogeneous memory hierarchies
Software-defined far memories
Disaggregated memory and in-memory computing
Data movement in heterogeneous memory systems
Memory consistency and persistency models
Data structures for heterogeneous memory infrastructures
Abstractions and support for failure-atomicity in persistent memory
Emerging memory architectures and system configurations
AI on heterogeneous memory systems and use of AI for heterogeneous memory systems
Use cases, early experiences and performance evaluations