Dryad is a general-purpose distributed execution engine for coarse-grain data-parallel applications. A Dryad applica-tion combines computational “vertices ” with communica-tion “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 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 multi-ple computers, or on multiple CPU cores within a computer. The application can discover the size and placement of data at r...
Many problems currently require more processor throughput than can be achieved with current single-p...
A fine-grain parallel program is one in which processes are typically small, ranging from a few to a...
Abstract—Cloud-based systems and the datacenter computing environment present a series of challenges...
Abstract—We introduce DryadOpt, a library that enables massively parallel and distributed execution ...
This document evaluates the evolution of the dis-tributed execution engine Dryad to the.NET lan-guag...
Cluster-based data-parallel frameworks such as MapReduce, Hadoop, and Dryad are increasingly popular...
After a short overview of the most known ideas about the distributed computing as clustering and gri...
Applying high level parallel runtimes to data/compute intensive applications is becoming increasingl...
Abstract — Applying high level parallel runtimes to data/compute intensive applications is becoming ...
Increasingly, online computer applications rely on large-scale data analyses to offer personalised a...
Journal ArticleThe complexity and diversity of parallel programming languages and computer architect...
Cloud application development is currently for professionals only. To make the cloud more accessible...
Increased programmability for concurrent applications in distributed systems requires automatic supp...
Dynamic Parallel Schedules (DPS) is a high-level framework for developing parallel applications on d...
A framework for data-flow distributed processing is established through the definition of a data-flo...
Many problems currently require more processor throughput than can be achieved with current single-p...
A fine-grain parallel program is one in which processes are typically small, ranging from a few to a...
Abstract—Cloud-based systems and the datacenter computing environment present a series of challenges...
Abstract—We introduce DryadOpt, a library that enables massively parallel and distributed execution ...
This document evaluates the evolution of the dis-tributed execution engine Dryad to the.NET lan-guag...
Cluster-based data-parallel frameworks such as MapReduce, Hadoop, and Dryad are increasingly popular...
After a short overview of the most known ideas about the distributed computing as clustering and gri...
Applying high level parallel runtimes to data/compute intensive applications is becoming increasingl...
Abstract — Applying high level parallel runtimes to data/compute intensive applications is becoming ...
Increasingly, online computer applications rely on large-scale data analyses to offer personalised a...
Journal ArticleThe complexity and diversity of parallel programming languages and computer architect...
Cloud application development is currently for professionals only. To make the cloud more accessible...
Increased programmability for concurrent applications in distributed systems requires automatic supp...
Dynamic Parallel Schedules (DPS) is a high-level framework for developing parallel applications on d...
A framework for data-flow distributed processing is established through the definition of a data-flo...
Many problems currently require more processor throughput than can be achieved with current single-p...
A fine-grain parallel program is one in which processes are typically small, ranging from a few to a...
Abstract—Cloud-based systems and the datacenter computing environment present a series of challenges...