ABOUT THE PDL
Welcome
The Parallel Data Lab at Carnegie Mellon University is academia's premiere storage systems research center. An interdisciplinary group, its 40-50 members come mainly from the Computer Science and ECE Departments. We also have a lot of friends in industry who generously provide us with advice, and some of the funding and equipment necessary to carry out our research.
Brief Research Overview
Our research addresses a broad spectrum of storage-related challenges, including storage security, emerging technologies, disk characterization and modeling, efficient storage access, storage networking, and network-attached storage clusters.
CURRENT PROJECTS:
- ARGON (Storage QoS) - performance insulation for shared storage servers
- Astro-DISC - new algorithms, data structures, and software tools for the analysis of massive astronomical and cosmological datasets.
- Database I/O - optimizing database performance
- Data Center Observatory (DCO) - A working data center and a research vehicle for the study of data center automation and efficiency
- Data-Intensive Supercomputing (DISC) - research to extend the type of computing systems used for Internet search to a larger range of applications
- dbug - exploring an alternative method to stress testing called systematic testing, which controls the order in which certain concurrent events occur
- DiskReduce - a framework for integrating RAID into replicated storage systems to lower storage capacity overhead
- DiskSim - an efficient, accurate, highly-configurable disk system simulator.
- eScience - PDL projects that are data-intensive and thus heavily invested in the use of computers for advancement
- FAWN - fast arrays of wimpy nodes
- Fingerpointing - problem diagnosis in distributed systems
- Home Storage - data management for the home
- Incast - addressing catastrophic TCP throughput collapse in storage server networks
- Enabling Non-Volatile Memory Techonologies - examining the use of NVM technologies as part of main memory, accessed directly using load/store instructions in order to overcome the challenges associated with building a DRAM-only main memory
- Otus - improving resource attribution through a monitoring system implementation
- PDL vCloud - replacing a multitude of single-purpose clusters, managed and underutilized by individual groups, with an IaaS private cloud for class projects, simulations, data analyses, and cluster and data-intensive computing activities
- Petascale Data Storage Institute (PDSI) - addressing the challenges of petascale computing for scientific discovery on information storage capacity, performance, concurrency, reliability, availability, and manageability
- pNFS - considers the problem of limited bandwidth to NFS servers
- Problem Analysis - analyzing performance and reliability problems in deployed large-scale systems
- pWalrus - a storage service layer that integrates parallel file systems effectively into cloud storage
- Survivable Storage (PASIS) - decentralized storage systems whose availability and security policies can survive component failures and successful malicious attacks
- Self-Securing Devices - systems with security functionality equally distributed among physically distinct system components
- Self-Securing Storage - storage devices that prevent successful intruders from undetectably tampering with or permanently deleting stored data
- Self-* Storage - a new storage architecture that integrates automated management functions and simplifies the human administrative task. Self*-systems are self configuring, self-organizing, self-managing, etc.
- YCSB++ - an advanced benchmark suite for categorizing cloud table stores
Contacts
, PDL Director
(412) 268-1297
, PDL Executive Director
(412) 268-5485
(412) 268-5890
, PDL Administrative Manager
(412) 268-6716
Mailing Address:
Computer Science Department
School of Computer Science
Carnegie Mellon University
5000 Forbes Avenue - CIC 2209
Pittsburgh, PA 15213-3891
Find Us
Most PDL offices are now located in the CIC Building on campus.
PDL's Visitor Information page.
The School of Computer Science's extensive
list of directions on how
to get to CMU from just about anywhere.
More directions to find CMU and the Dept. of ECE.