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RESEARCH HIGHLIGHTS
Ling Liu's SC13 paper "Large Graph Processing Without the Overhead" featured by HPCwire.
ISTC-CC provides a listing of useful benchmarks for cloud computing.
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.
ISTC-CC Abstract
On the Duality of Data-intensive File System Design:
Reconciling HDFS and PVFS
SC11, November 12-18, 2011, Seattle, Washington USA. Supersedes Carnegie Mellon University Parallel Data Lab Technical Report CMU-PDL-11-108. April 2011.
Wittawat Tantisiriroj, Swapnil Patil, Garth Gibson, Seung Woo Son*,
Samuel J. Lang*, Robert B. Ross*
Carnegie Mellon University
*Argonne National Laboratory
Data-intensive applications fall into two computing styles: Internet services (cloud computing) or high-performance computing (HPC). In both categories, the underlying file system is a key component for scalable application performance. In this paper, we explore the similarities and differences between PVFS, a parallel file system used in HPC at large scale, and HDFS, the primary storage system used in cloud computing with Hadoop. We integrate PVFS into Hadoop and compare its performance to HDFS using a set of data-intensive computing benchmarks. We study how HDFS-specific optimizations can be matched using PVFS and how consistency, durability, and persistence tradeoffs made by these file systems affect application performance. We show how to embed multiple replicas into a PVFS file, including a mapping with a complete copy local to the writing client, to emulate HDFS's file layout policies. We also highlight implementation issues with HDFS's dependence on disk bandwidth and benefi ts from pipelined replication.
FULL PAPER: pdf
