DRYAD DISTRIBUTED DATA-PARALLEL PROGRAMS FROM SEQUENTIAL BUILDING BLOCKS PDF

Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. It achieve similar goals as MapReduce, but with different design. Computations in Dryad expressed as a graph. On a very high level, Dryad focuses more on simplicity of the programming model and reliability, efficiency and scalability of the application.

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Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. Dryad runs the application by executing the vertices of this graph on a set of available computers, communicating as appropriate through files, TCP pipes, and shared-memory FIFOs. The vertices provided by the application developer are quite simple and are usually written as sequential programs with no thread creation or locking.

Concurrency arises from Dryad scheduling vertices to run simultaneously on multiple computers, or on multiple CPU cores within a computer. The application can discover the size and placement of data at run time, and modify the graph as the computation progresses to make efficient use of the available resources. Dryad is designed to scale from powerful multi-core single computers, through small clusters of computers, to data centers with thousands of computers.

The Dryad execution engine handles all the difficult problems of creating a large distributed, concurrent application: scheduling the use of computers and their CPUs, recovering from communication or computer failures, and transporting data between vertices.

On 31 Jul, By admin 0 Comments. Abstract: Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. Resource Type:. Academic Paper. Distributed Data-Parallel Programs. Sequential Building Blocks. Distributed Computing. Cluster Computing.

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Dryad: Distributed Data-Parallel Programs from Sequential Building Blocks

Summary: Dryad is a runtime for data-intensive parallel programs that models computations as graphs where vertices are sequential programs and edges represent data flows between programs. Developers use a high-level language to construct graphs representing their computations, decreasing the need to directly use low-level synchronization primitives. Problem: The rise in multi-core systems has increased the need for software to compute in parallel on separate processors where possible, but developing such software is often difficult when working directly with low-level parallelization primitives such as threads and methods to communicate between them. In response to the demand for easier programming models, systems such as MapReduce were developed to handle certain common paradigms. But systems such as MapReduce and parallel database servers are still very domain-specific and leave limited room for customization.

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Summary of "Dryad: Distributed Data-Parallel Programs from Sequential Building Blocks"

Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. Dryad runs the application by executing the vertices of this graph on a set of available computers, communicating as appropriate through files, TCP pipes, and shared-memory FIFOs. The vertices provided by the application developer are quite simple and are usually written as sequential programs with no thread creation or locking. Concurrency arises from Dryad scheduling vertices to run simultaneously on multiple computers, or on multiple CPU cores within a computer. The application can discover the size and placement of data at run time, and modify the graph as the computation progresses to make efficient use of the available resources.

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Dryad: Distributed Data-parallel Programs from Sequential Building Blocks

Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. Dryad runs the application by executing the vertices of this graph on a set of available computers, communicating as appropriate through files, TCP pipes, and shared-memory FIFOs. The vertices provided by the application developer are quite simple and are usually written as sequential programs with no thread creation or locking. Concurrency arises from Dryad scheduling vertices to run simultaneously on multiple computers, or on multiple CPU cores within a computer.

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Dryad: distributed data-parallel programs from sequential building blocks

Skip to search form Skip to main content You are currently offline. Some features of the site may not work correctly. DOI: Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. A Dryad application combines computational "vertices" with communication "channels" to form a dataflow graph. Dryad runs the application by executing the vertices of this graph on a set of available computers, communicating as appropriate through flies, TCP pipes, and shared-memory FIFOs. View on ACM.

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