Submissions due: Feb 14, 2018
Author notification: Feb 21, 2018


Explosive growth in dataset sizes and demand for ubiquitous access to information by both human and machine actors is fueling the use of warehouse-scale datacenters. To accommodate massive datasets and achieve their performance and resilience objectives, such datacenters rely on distributed memory systems. Distributed memory comes with a number of challenges, including consistency, scalability, availability and performance predictability. These challenges are amplified by an increasingly diverse datacenter workload portfolio, with established scale-out workloads sharing infrastructure with HPC, machine learning, and traditional server applications migrating to the cloud.

The goal of the workshop is to explore both established and emerging challenges in warehouse-scale memory systems, along with potential angles for attacking these challenges.

Topics of interest include, but are not limited to:

The workshop will include a mix of accepted presentations and invited talks.


Submissions are solicited in the form of a 1-page abstract. Submissions must have a clear focus on distributed memory systems from rack to datacenter scale. We welcome provocative ideas and negative results.

There will be no published proceedings, so submissions do not preclude future publication.

Submission site:
Submissions due: Feb 14, 2018


Boris Grot, University of Edinburgh
Tim Harris
Vijay Nagarajan, University of Edinburgh
Mark Silberstein, Technion


Please contact Boris Grot at