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About 7,093 papers for “Dataflow”

Dataflow Graph Optimization for Dataflow Architectures a Dataflow Otimizing Compiler

Sholin Kyo, Shinichiro Okazaki, Masanori Mizoguchi · 1993

In general, datafiow graph for which it is difficult to optimize quality are those used for branches (conditionals) and loops. Although a number of dataflow graph transformation schemes have taken these into accounts, the quality of graphs been produced was not compared with that of hand-written optimized graphs.

Cited by 2

Dataflow Architectures.

Culler,David E · Defense Technical Information Center (DTIC) · 1986

Dataflow graphs are described as a machine language for parallel machines. Static and dynamic dataflow architectures are presented as two implementations of the abstract dataflow model. Static dataflow allows at most one token per arc in dataflow graphs and thus only approximates the abstract model where unbounded token storage per arch is assumed. Dynamic architectures tag each token and keep them in a common pool of storage, thus permitting a better approximation of the abstract model. The relative merits of the two approaches are discussed. Functional data structures and I-structures are presented as two views of data structures which are both compatible with the dataflow model. These views are contrasted and compared in regard to efficiency and exploitation of potential parallelism in programs. A discussion of major dataflow projects and a prognosis for data flow architectures are also presented. Keywords: Mulitprocessors, Parallel computation, Parallel computers. (Author)

Cited by 6

Synchronous dataflow

Shuvra S. Battacharyya, Praveen K. Murthy, Edward A. Lee · Kluwer international series in engineering and computer science · 1996

Cited by 0

Dataflow analysis

Suzanne M · 2011

ABSTRACT Qualitative measures were developed within a Principal-Teacher Intelaction (PTI) study by the Research and Development Center for Teacher Education, Uni.versitx of Texas at Austin, concerning the role of the principal and process of change as it oceurs in school settings. Mettiodoiogies for data collection and analysis included quantitative measures of individual and group responses to change and qualitative dimensions concerning a sense of,the context, interactions, and social meanings underlying the. quantitative responses. These qualitative measures interpret and organize data to represent existing reality within a site and contribute to theory across sites. Qualitative methods can include coding.of change action interventions, listing of effects, levels of use of an innovation, and configuration and concerns data. Qualitative information can be focused'by'using intervention mapping of planned action, antecedent mapping of how change'evolved, critical-incident maps,and time lines,cand "reality checks " by-cross-site discussions involving "site expert " researchers and district

Cited by 0

Dataflow Analysis

Andrew W. Appel, Jens Palsberg · Cambridge University Press eBooks · 2002

An optimizing compiler transforms programs to improve their efficiency without changing their output. There are many transformations that improve efficiency:

Cited by 0

Differential dataflow

Frank McSherry, Derek G. Murray, Rebecca Isaacs et al. · 2013

Existing computational models for processing continuously changing input data are unable to efficiently support iterative queries except in limited special cases. This makes it difficult to perform complex tasks, such as social-graph analysis on changing data at interactive timescales, which would greatly benefit those analyzing the behavior of services like Twitter. In this paper we introduce a new model called differential computation, which extends traditional incremental computation to allow arbitrarily nested iteration, and explain—with reference to a publicly available prototype system called Naiad—how differential computation can be efficiently implemented in the context of a declarative dataparallel dataflow language. The resulting system makes it easy to program previously intractable algorithms such as incrementally updated strongly connected components, and integrate them with data transformation operations to obtain practically relevant insights from real data streams. 1.

Cited by 93

BCV dataflow.

Yuri S. Fantin (277410), Alexey D. Neverov (277411), Alexander V. Favorov (277412) et al. · Figshare · 2015

<p>Rectangles depict software applications; rolls depict files; black arrows are the pipeline input and output streams with the corresponding input and output file extensions shown in italic bold. The file extensions are as follows: The input ABIF (*.ab1) file contains the chromatogram itself and the ABI base-calling. TraceTuner files (PHRED compatible): *.scf contains the chromatogram; *.phd.1 is the chromatogram sequence, and *.poly is the secondary peak calling results. PolyScan files: *.fpoly contains minor peak calls around the primary sequence, and *.bqs contains the peak likelihoods. BCV pipeline output files: *.viterbi.fasta contains the chromatogram sequence; *.cluster.fasta is the DNA type reconstruction and *.indels.txt is the indel report. The configuring and calling of TraceTuner, BCV::PolyScan and BCV::proc applications is enveloped in the bcv_run.pl script. For indel detection functionality the call of the bcv_indels.pl script is followed of the bcv_run.pl. The bcv_run.pl prepares an alignment of raw predicted DNA variants (from the *.strains.fasta file) with similar sequences from the vocabulary that are listed in the *.decomplog.gfas file. Both files are generated by the BCV::proc application. The input file for the indel detection script bcv_indels.pl has the grouped FASTA format and corresponding.gfas file name extension.</p>

Cited by 0Open access

Beyond Dataflow

Ungerer, Theo, Šilc, Jurij, Robič, Borut · Hrčak Portal of scientific journals of Croatia (University Computing Centre) · 2000

Cited by 0Open access

Pipeline dataflow

CJ Mungall, S Misra, BP Berman et al. · Figshare · 2011

<b>Copyright information:</b>Taken from "An integrated computational pipeline and database to support whole-genome sequence annotation"Genome Biology 2002;3(12):research0081.1-81.11.Published online 23 Dec 2002PMCID:PMC151183.Copyright © 2002 Mungall et al., licensee BioMed Central Ltd Finished genomic sequence is deposited in Gadfly, and then fed to the pipeline database, which manages jobs, dispatching them to the compute farm via PBS. When a job finishes, the pipeline database stores the output. BOP filters this output and exports GAME XML to Gadfly. A cycle of annotation consists of curators loading GAME XML into Apollo, either directly from Gadfly or from a data directory. Modified annotations are then written to a directory and loaded into Gadfly.

Cited by 0Open access

Dataflow analysis

Yockey Harry M, Yockey H, Harry M. Yockey et al. · 2011

Use of Mitrovic&amp;apos;s method in the analysis of a control system with two gain-variable feedback nonlinearities.

Cited by 0

Dataflow Analysis

Andrew W. Appel · Cambridge University Press eBooks · 1997

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.

Cited by 0

Dataflow supercomputing

Michael Flynn, Oliver Pell, Oskar Mencer · 2012

Over the past decades parallel processor speedup has been an elusive quantity for a broad class of applications. Yet with the end of performance scaling for single processors the need for speedup has never been greater. The problem is not technology but programming models. One answer to this speedup problem is to create an idealized data flow machine that exactly corresponds to the application and stream data through the resulting machine. This approach can be emulated with FPGAs, providing more than an order of magnitude speedup even as executed as an emulation of the data flow machine.

Cited by 13

From dataflow

Thomas Carle, Dumitru Potop-butucaru, Yves Sorel et al. · 2013

Cited by 0

FLYSIG: Dataflow . . .

Wolfram Hardt, Bernd Kleinjohann · 1998

As the one-chip integration of HW-modules designed by different companies becomes more and more popular reliability of a HW-design and evaluation of the timing behavior during the prototype stage are absolutely necessary. One way to guarantee reliability is the use of robust design styles, e.g., delay-insensitivity. For early timing evaluation two aspects must be considered: a) The timing needs to be proportional to technology variations and b) the implemented architecture should be identical for prototype and target. The first can be met also by delay-insensitive implementation. The latter one is the key point. A unified architecture is needed for prototyping as well as implementation. Our new

Cited by 0

Dataflow Computers

Justin R Smith · 1993

Abstract Although these algorithms look considerably more complex than the corresponding algorithms for the Butterfly and the shuffle-exchange network, their execution-time is comparable. Consider a modification of the butterfly network, where we introduce a new edge in each column that connects the top and bottom vertex - we will call this the m-Butterfly network. It is similar, but not identical to, the form of the Butterfly that identifies the top and bottom rows. Show that the CCC network with a given value of r is isomorphic to an m-Butterfly network with 2r rows.

Cited by 0

Dataflow notebooks

Jay Patel · 2017

Jupyter Notebook is an interactive computational environment widely adopted by scientists from many domains. It allows users to combine code, explanatory text, and textual &amp; visual execution results in a single, editable document. The code is divided into blocks called cells that can be individually executed as well as edited. The code written in one cell may depend on code in other cells, and those dependencies are usually codified by global variables. However, these dependencies are not easily identified or discovered, and the order cells were executed in is not easily captured. This leads to a problem with reproducing the results of a previous analysis. Dataflows, on the other hand, explicitly encode dependencies between computational modules, leading to a well-defined order of execution. We introduce dataflow notebooks to blend the benefits of each paradigm. This solution introduces a persistent and unique identifier for each cell and encourages users to explicitly reference outputs of other cells via these identifiers. As will dataflows, we can ensure that results are never out-of-date by recursively updating dependencies as needed. The solution also enables new operations in the notebook, allowing users to see dependencies of a computation as well as selectively update downstream cells when upstream dependencies are modified. This framework improves reproducibility while maintaining the core features of notebooks..

Cited by 0

Dataflow analysis

Scandura Joseph M · 2011

Set-Function Language This report describes research conducted regarding the development of a precise scientific language called the &amp;quot;Set-Function &amp;quot; Language (SFL) which was formulated in terms of sets and functions. The SFL retains many of the basic aspects of cognitive formulations but also provides more rigor than most of the other scientific languages. The SFL characterizes notions like rules, decoding and encoding processes, &amp;quot;chaining&amp;quot;, reference mechanisms, and higher order rules in a precise manner. The report claims that the SFL is more adequate than the existing S-R and cognitive languages for formulating research on meaningful learning. Also, the author presents a partial solution to the problem of &amp;quot;what (rule) is learned. &amp;quot; (FL),ArocaAne Avg/

Cited by 0