Processing-In-Memory (PIM) architectures based on recent technology advances (eg,
Hybrid Memory Cube) demonstrate great potential for graph processing. However, existing …

Graph analysis is a powerful method in data analysis. Although several frameworks have
been proposed for processing large graph instances in distributed environments, their …

Numerous recent research eorts have explored the use of Graphics Processing Units
(GPUs) as accelerators for software-based routing and packet handling applications …

Datacenters of today have maintained the same architecture for decades. The building block
of the datacenter remains the server, which tightly couples the necessary compute …

It is increasingly important for parallel applications to run together on the same machine.
However, current performance is often poor: programs do not adapt well to dynamically …

A coherent global address space in a distributed system enables shared memory
programming in a much larger scale than a single multicore or a single SMP. Without …

Graph processing is experiencing a surge of renewed interest as applications in social
networks and their analysis have grown in importance. Additionally, graph algorithms have …

Multi-Agent Systems (MAS) are a separate scientific field. The agent-oriented approach is
widely applied in systems for distributed solutions of complex tasks in the simulation …

We propose a new data structure, Parallel Adjacency Lists (PAL), for efficiently managing
graphs with billions of edges on disk. The PAL structure is based on the graph storage …

We introduce Callisto-RTS, a parallel runtime system designed for multi-socket shared-
memory machines. It supports very fine-grained scheduling of parallel loops—down to …