Ling Liu's SC13 paper "Large Graph Processing Without the Overhead" featured by HPCwire.
Another list highlighting Open Source Software Releases.
Second GraphLab workshop should be even bigger than the first! GraphLab is a new programming framework for graph-style data analytics.
Application-to-Core Mapping Policies
to Reduce Memory Interference in Multi-Core Systems
International Conference on Parallel Architectures and Compilation Techniques (PACT'12), September 2012.
Reetuparna Das, Rachata Ausavarungnirun†, Onur Mutlu†, Akhilesh Kumar‡,
University of Michigan
†Carnegie Mellon University
How applications running on a many-core system are mapped to cores largely determines the interference between these applications in critical shared resources. This paper proposes application-to-core mapping policies to improve system performance by reducing inter-application interference in the on-chip network and memory controllers. The major new ideas of our policies are to: 1) map network-latency-sensitive applications to separate parts of the network from network-bandwidth-intensive applications such that the former can make fast progress without heavy interference from the latter, 2) map those applications that benefit more from being closer to the memory controllers close to these resources. Our evaluations show that both ideas significantly improve system throughput, fairness and interconnect power efficiency.
KEYWORDS: Multicore, scheduling, interconnect, memory
FULL PAPER: pdf