First version of a data flow procedure language

Dennis, Jack B.

doi:10.1007/3-540-06859-7_145

Cited by 444 publications

(213 citation statements)

References 7 publications

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“…Similar to a dataflow actor [9], a codelet is fired once all of its dependencies (or events) are met. An event primarily consists of the data (i.e.…”

Section: Codelets: Definition and Operational Semanticsmentioning

confidence: 99%

“…The semantics of traditional threads makes it extremely difficult to guarantee correct execution, and race conditions are the dreaded companion of any parallel programmer [17]. However, there are PXMs which emphasize properties such as the isolation of execution and the explicit declaration of producer-consumer relations like the dataflow program execution models [9]. This paper evaluates an implementation of the codelet model [24], a finegrain PXM inspired by dataflow.…”

Section: Introductionmentioning

confidence: 99%

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An Implementation of the Codelet Model

Suettlerlein

Zuckerman

Gao

2013

Euro-Par 2013 Parallel Processing

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Abstract. Chip architectures are shifting from few, faster, functionally heavy cores to abundant, slower, simpler cores to address pressing physical limitations such as energy consumption and heat expenditure. As architectural trends continue to fluctuate, we propose a novel program execution model, the Codelet model, which is designed for new systems tasked with efficiently managing varying resources. The Codelet model is a fine-grained dataflow inspired model extended to address the cumbersome resources available in new architectures. In the following, we define the Codelet execution model as well as provide an implementation named DARTS. Utilizing DARTS and two predominant kernels, matrix multiplication and the Graph 500's breadth first search, we explore the validity of fine-grain execution as a promising and viable execution model for future and current architectures. We show that our runtime is on par or performs better than AMD's highly-optimized parallel library for matrix multication, outperforming it on average by 1.40× with a speedup up to 4×. Our implementation of the parallel BFS outperforms Graph 500's reference implementation (with or without dynamic scheduling) on average by 1.50× with a speed up of up to 2.38×.

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“…Similar to a dataflow actor [9], a codelet is fired once all of its dependencies (or events) are met. An event primarily consists of the data (i.e.…”

Section: Codelets: Definition and Operational Semanticsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Implementation of the Codelet Model

Suettlerlein

Zuckerman

Gao

2013

Euro-Par 2013 Parallel Processing

View full text Add to dashboard Cite

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“…The first graphical user interface for specifying programs modeled as precedence graphs appeared in 1966 [28]. The modern notion of dataflow programming, as graph-structured parallel computations, was first clearly articulated in 1970 [29], although most subsequent work in the 1970s was based on a more restrictive model [30]. Hardware architectures based on the dataflow model also emerged [31].…”

Section: Dataflow Graphsmentioning

confidence: 99%

Cogset: a high performance MapReduce engine

Valvåg

Johansen

Kvalnes

2012

Concurrency and Computation

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MapReduce has become a widely employed programming model for large-scale data-intensive computations. Traditional MapReduce engines employ dynamic routing of data as a core mechanism for fault tolerance and load balancing. An alternative mechanism is static routing, which reduces the need to store temporary copies of intermediate data, but requires a tighter coupling between the components for storage and processing. The initial intuition motivating our work is that reading and writing less temporary data could improve performance, while the tight coupling of storage and processing could be leveraged to improve data locality.We therefore conjecture that a high-performance MapReduce engine can be based on static routing, while preserving the non-functional properties associated with traditional engines. To investigate this thesis, we design, implement, and experiment with Cogset, a distributed MapReduce engine that deviates considerably from the traditional design.We evaluate the performance of Cogset by comparing it to a widely used traditional MapReduce engine using a previously established benchmark. The results confirm our thesis that a high-performance MapReduce engine can be based on static routing, although analysis indicates that the reasons for Cogset's performance improvements are more subtle than expected. Through our work we develop a better understanding of static routing, its benefits and limitations, and its ramifications for a MapReduce engine.A secondary goal of our work is to explore how higher-level abstractions that are commonly built on top of MapReduce will interact with an execution engine based on static routing. Cogset is therefore designed with a generic, low-level core interface, upon which MapReduce is implemented as a relatively thin layer, as one of several supported programming interfaces.At its core, Cogset provides a few fundamental mechanisms for reliable and distributed storage of data, and parallel processing of statically partitioned data. While this dissertation mainly focuses on how these capabilities are leveraged to implement a distributed MapReduce engine, we also demonstrate how two other higher-level abstractions were built on top of Cogset. These may serve as alternative access points for data-intensive applications, and illustrate how some of the lessons learned from Cogset can be applicable in a broader context.

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“…The dataflow programming paradigm was initially envisioned in the late 1960s (Adams [7]) and early 1970s (Dennis [8]) out of an increased desire to design a method of programming based on the connections, or flow, between program elements as opposed to focusing on the data changes occurring as program execution progressed. Typically, this programming style is modeled similar to a graph diagram representation, as shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

SimITK: Visual Programming of the ITK Image-Processing Library within Simulink

et al. 2014

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The Insight Segmentation and Registration Toolkit (ITK) is a software library used for image analysis, visualization, and image-guided surgery applications. ITK is a collection of C++ classes that poses the challenge of a steep learning curve should the user not have appropriate C++ programming experience. To remove the programming complexities and facilitate rapid prototyping, an implementation of ITK within a higher-level visual programming environment is presented: SimITK. ITK functionalities are automatically wrapped into "blocks" within Simulink, the visual programming environment of MATLAB, where these blocks can be connected to form workflows: visual schematics that closely represent the structure of a C++ program. The heavily templated C++ nature of ITK does not facilitate direct interaction between Simulink and ITK; an intermediary is required to convert respective data types and allow intercommunication. As such, a SimITK "Virtual Block" has been developed that serves as a wrapper around an ITK class which is capable of resolving the ITK data types to native Simulink data types. Part of the challenge surrounding this implementation involves automatically capturing and storing the pertinent class information that need to be refined from an initial state prior to being reflected within the final block representation. The primary result from the SimITK wrapping procedure is multiple Simulink block libraries. From these libraries, blocks are selected and interconnected to demonstrate two examples: a 3D segmentation workflow and a 3D multimodal registration workflow. Compared to their pure-code equivalents, the workflows highlight ITK usability through an alternative visual interpretation of the code that abstracts away potentially confusing technicalities.

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First version of a data flow procedure language

Cited by 444 publications

References 7 publications

An Implementation of the Codelet Model

An Implementation of the Codelet Model

Cogset: a high performance MapReduce engine

SimITK: Visual Programming of the ITK Image-Processing Library within Simulink

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