Public cloud providers seek to meet stringent performance requirements and low hardware
cost. A key driver of performance and cost is main memory. Memory pooling promises to …

Fog/edge computing, function as a service, and programmable infrastructures, like software-
defined networking or network function virtualisation, are becoming ubiquitously used in …

Memory is the most contended and least elastic resource in datacenter servers today.
Applications can use only local memory—which may be scarce—even though memory …

The monolithic server model where a server is the unit of deployment, operation, and failure
is meeting its limits in the face of several recent hardware and application trends. To improve …

Disaggregated memory can address resource provisioning inefficiencies in current
datacenters. Multiple software runtimes for disaggregated memory have been proposed in …

As memory requirements grow, and advances in memory technology slow, the availability of
sufficient main memory is increasingly the bottleneck in large compute clusters. One solution …

The unrelenting growth of the memory needs of emerging datacenter applications, along
with ever increasing cost and volatility of DRAM prices, has led to DRAM being a major …

Resource-disaggregated architectures have risen in popularity for large datacenters.
However, prior disaggregation systems are designed for native applications; in addition, all …

Memory disaggregation promises transparent elasticity, high resource utilization and
hardware heterogeneity in data centers by physically separating memory and compute into …

Memory disaggregation over RDMA can improve the performance of memory-constrained
applications by replacing disk swapping with remote memory accesses. However, state-of …