Dryad (programming)
| Original author(s) | Microsoft Research |
|---|---|
| Developer(s) | Microsoft |
| Stable release | v0.2.1
/ October 7, 2014 |
Apache License 2.0 | |
| Website | www |
Dryad was a research project at
data parallel
applications.
The research prototypes of the Dryad and DryadLINQ data-parallel processing frameworks are available in source form at GitHub.[1]
Overview
Microsoft made several preview releases of this technology available as add-ons to
Windows HPC Server 2008 R2
.
An application written for Dryad is modeled as a
files. A stream is used at runtime to transport a finite number of structured
Items.
Dryad defines a
class that inherits from the
can also be written.
GraphNode base class. The graph is defined by adding edges; edges are added by using a composition operator (defined by Dryad) that connects two graphs (or two nodes of a graph) with an edge. Managed code wrappers for the Dryad APIThere exist several high-level language compilers which use Dryad as a runtime; examples include Scope (Structured Computations Optimized for Parallel Execution) and DryadLINQ.[2]
In October 2011, Microsoft discontinued active development on Dryad, shifting focus to the Apache Hadoop framework.[3][4][5]
References
- ^ GitHub - MicrosoftResearch/Dryad: This is a research prototype of the Dryad and DryadLINQ data-parallel processing frameworks running on Hadoop YARN.
- ^ "DryadLINQ: A System for General-Purpose Distributed Data-Parallel Computing Using a High-Level Language" (PDF). Microsoft Research. Retrieved 2009-01-21.
- ^ Patee, Don. "Announcing the Windows Azure HPC Scheduler and HPC Pack 2008 R2 Service Pack 3 releases!". Microsoft. Retrieved 2013-05-31.
- ^ Foley, Mary Joe. "Microsoft drops Dryad; puts its big-data bets on Hadoop". ZDNet. Retrieved 2013-05-31.
- ^ Henschen, Doug. "Microsoft Ditches Dryad, Focuses On Hadoop". Information Week. Retrieved 2013-05-31.
Further reading
- "Dryad: Distributed Data-Parallel Programs from Sequential Building Blocks" (PDF). Microsoft Research. Retrieved 2007-12-04.
- "SCOPE: Easy and Efficient Parallel Processing of Massive Data Sets" (PDF). Microsoft Research. Retrieved 2009-01-21.
External links
- Dryad: Programming the Data Center Archived 2007-09-12 at the Wayback Machine
- Dryad Home
- Video of Michael Isard explaining Dryad at Google
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| MSR Labs applied research |
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| General | |
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| Levels | |
| Multithreading | |
| Theory | |
| Elements | |
| Coordination | |
| Programming | |
| Hardware | |
| APIs | |
| Problems | |