Hybrid storage systems (HSS) use multiple different storage devices to provide high and
scalable storage capacity at high performance. Data placement across different devices is …

Resource disaggregation offers a cost effective solution to resource scaling, utilization, and
failure-handling in data centers by physically separating hardware devices in a server …

Memory management across discrete CPU and GPU physical memory is traditionally
achieved through explicit GPU allocations and data copy or unified virtual memory. The …

Dynamic neural network (DyNN) enables high computational efficiency and strong
representation capability. However, training DyNN can face a memory capacity problem …

We propose a new framework called CachedArrays and a set of APIs to address the data
tiering problem in large scale heterogeneous and disaggregated memory systems. The …

Multi-terabyte large memory systems are often characterized by more than two memory tiers
with different latency and bandwidth. Multi-tiered large memory systems call for rethinking of …

Abstract Hybrid Main Memory introduces emerging non-volatile memory technologies and
reduces the DRAM footprint to address the increasing capacity demands of modern …

Large multi-socket machines are mission-critical high-performance systems for workloads
requiring massive memory shared by hundreds of processors. Beyond eight sockets, such …

Emerging workloads benefit from massive memory capacities provided by hybrid memory
platforms. Recent system-level hybrid memory management solutions integrate machine …

Disaggregated memory is being proposed as a way to provide efficient memory scaling for
data intensive applications. High performance interconnect technologies, such as CXL …