A Fast Array of Wimpy Nodes
FAWN: A Fast Array of Wimpy Nodes
Introducing the FAWN
FAWN is a fast, scalable, and energy-efficient cluster
architecture for data-intensive computing. A FAWN
cluster links together a large number of "wimpy" nodes
built using energy-efficient processors and small amounts
of flash memory into an ensemble cluster that can
perform the same amount of work as a traditional cluster
but at a fraction of the power.
We have designed and implemented a clustered key-value storage system, FAWN-KV, that runs atop these node. Nodes in FAWN-KV use a specialized log-like back-end hash-based datastore (FAWN-DS) to ensure that the system can absorb the large write workload imposed by frequent node arrivals and departures. FAWN-KV uses a two-level cache hierarchy to ensure that imbalanced workloads cannot create hot-spots on one or a few wimpy nodes that impair the system's ability to service queries at its guaranteed rate.
Our evaluation of a small-scale FAWN cluster and several candidate FAWN node systems suggest that FAWN can be a practical approach to building large-scale storage for seek-intensive workloads. Our further analysis indicates that a FAWN cluster is cost-competitive with other approaches (e.g., DRAM, multitudes of magnetic disks, solid-state disk) to providing high query rates, while consuming significantly less power.
Source code for Basic FAWN-KV is available below.
Source code for SILT is available below.
Using Vector Interfaces to Deliver Millions of IOPS
from a Networked Key-value Storage Server
Vijay Vasudevan Michael Kaminsky, David Andersen,
In Proc. ACM Symposium on Cloud Computing (SOCC 2012), San Jose, CA. October 2012.
FAWNSort: Energy-efficient Sorting of 10GB, 100GB, and 1TB (2012)
Padmanabhan Pillai, Michael Kaminsky, Michael A. Kozuch, David Andersen,
Winner of 2012 10GB, 100GB, and 1TB, Joulesort Daytona and Indy categories.
SILT: A Memory-Efficient, High-Performance Key-Value Store
Hyeontaek Lim, Bin Fan, David Andersen, Michael Kaminsky,
In Proc. 23nd ACM Symposium on Operating Systems Principles (SOSP 2011), Cascais, Portugal. October 2011.
Small Cache, Big Effect: Provable Load Balancing for Randomly Partitioned Cluster Services
Bin Fan, Hyeontaek Lim, David Andersen, Michael Kaminsky,
In Proc. ACM Symposium on Cloud Computing (SOCC 2011), Cascais, Portugal. October 2011.
FAWNSort: Energy-efficient Sorting of 10GB (2011)
Padmanabhan Pillai, Michael Kaminsky, Michael A. Kozuch, Vijay Vasudevan, Lawrence Tan, David Andersen
Winner of 2011 10GB Joulesort Daytona and Indy categories.
FAWNSort: Energy-efficient Sorting of 10GB (2010)
Vijay Vasudevan Lawrence Tan, David Andersen, Michael Kaminsky, Michael A. Kozuch, Padmanabhan Pillai,
Winner of 2010 10GB Joulesort Daytona and Indy categories.
Energy-efficient Cluster Computing with FAWN: Workloads and Implications
Vijay Vasudevan David Andersen, Michael Kaminsky, Lawrence Tan, Jason Franklin, Iulian Moraru
In Proc. Proceedings of e-Energy 2010.
FAWN: A Fast Array of Wimpy Nodes
David Andersen, Jason Franklin, Michael Kaminsky, Amar Phanishayee, Lawrence Tan, Vijay Vasudevan
In Proc. 22nd ACM Symposium on Operating Systems Principles (SOSP 2009), Big Sky, MT. October 2009. Awarded Best Paper
FAWNdamentally Power-efficient Clusters
Vijay Vasudevan, Jason Franklin, David Andersen, Amar Phanishayee, Lawrence Tan, Michael Kaminsky, and Iulian Moraru
In Proc. 12th Workshop on Hot Topics in Operating Systems (HotOS XII), Monte Verita, May 2009.
July 1, 2011
FAWN article in CACM this month (July 2011), available here.
November 2, 2010
FAWN-KV source code released, available here.
March 20, 2009
FAWNdamentals paper accepted to HotOS XII
Jul 30th, 2008
Photos of 3G posted.