Analyzing large graphs provides valuable insights for social networking and web companies
in content ranking and recommendations. While numerous graph processing systems have …

We present Grappa, a modern take on software distributed shared memory (DSM) for in-
memory data-intensive applications. Grappa enables users to program a cluster as if it were …

Graph processing is an increasingly important application domain and is typically
communication-bound. In this work, we analyze the performance characteristics of three …

Emerging datacenter applications operate on vast datasets that are kept in DRAM to
minimize latency. The large number of servers needed to accommodate this massive …

Grace is a graph-aware, in-memory, transactional graph management system, specifically
built for real-time queries and fast iterative computations. It is designed to run on large multi …

Large graph processing has attracted much renewed attention due to its increased
importance for a social network analysis. The efficient parallel graph processing faces a set …

(57) ABSTRACT A computing system that uses a Scale-Out NUMA (" SONUMA”)
architecture, programming model, and/or communication protocol provides for low-latency …

Grappa is a runtime system for commodity clusters of multicore computers that presents a
massively parallel, single address space abstraction to applications. Grappa's purpose is to …

The determination of the atomistic structure of surfaces and interfaces is a central problem in
materials physics and in nanoscience [175, 176]. Among surface sensitive probes, non …

In the big data era, graph computing is one of the challenging issues because there are
numerous large graph datasets emerging from real applications. A question is: do we need …