A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Filters
Automated Mapping of the MapReduce Pattern onto Parallel Computing Platforms
2010
Journal of Signal Processing Systems
Preserved Fulltext
Gate Array (FPGA) based parallel computing platforms. ...
Unlike previous work, in which designers explicitly specify how to exploit the pattern, we develop a compilation approach for mapping applications with the MapReduce pattern automatically onto Field-Programmable ...
Acknowledgements We thank FP6 hArtes project, the EPSRC, AlphaData and Xilinx for their support. We also thank the anonymous reviewers for their comments. ...
doi:10.1007/s11265-010-0563-9
fatcat:qq3skkqcyjeiloryxhctjhrrem
Automatic optimisation of MapReduce designs by geometric programming
2009
2009 International Conference on Field-Programmable Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Many important applications can be expressed using the MapReduce pattern, where a computation is decomposed into a Map phase on which each element of source data is independently operated, followed by ...
We develop an approach for compiling applications with the MapReduce pattern into parallel hardware. ...
We thank FP6 hArtes project, the EPSRC, Al-phaData and Xilinx for their support. ...
doi:10.1109/fpt.2009.5377629
fatcat:2z5vmltn7rgn3apeanwd3kf37e
Guest Editorial: Field-Programmable Technology
2011
Journal of Signal Processing Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
In "Automated Mapping of the MapReduce Pattern onto Parallel Computing Platforms," Qiang Lie, Tim Todman, Wayne Luk and George Constantinides explore using FPGAs effectively for large computational problems ...
Having identified that many applications use a "MapReduce" computational pattern, they develop a ...
In "Automated Mapping of the MapReduce Pattern onto Parallel Computing Platforms," Qiang Lie, Tim Todman, Wayne Luk and George Constantinides explore using FPGAs effectively for large computational problems ...
doi:10.1007/s11265-011-0653-3
fatcat:7vextmaqsfcuhjiwtais3nk35e
Optimizing Hardware Design by Composing Utility-Directed Transformations
2012
IEEE transactions on computers
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2013; you can also visit the original URL.
The file type is application/pdf.
We present a systematic approach composing multiple utility-directed transformations for optimizing and mapping a sequential design onto a customizable parallel computing platform such as a Field-Programmable ...
The utility-directed transformations in this work produce performance-optimized designs by exploiting data reuse, MapReduce, and pipelining for the target parallel computing platform. ...
We thus map the innermost loop of matrix multiplication onto a parallel computing structure, by loop strip mining. ...
doi:10.1109/tc.2011.205
fatcat:o5ekmgzqundk5jzpnhrfrhfnj4
Adapting MPI to MapReduce PaaS Clouds: An Experiment in Cross-Paradigm Execution
2012
2012 IEEE Fifth International Conference on Utility and Cloud Computing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
on MapReduce platforms. ...
ABSTRACT One desired attribute of utility computing is the ability for any provider's offering to meet any user's requirement, but the variety of programming paradigms and platform models make this non-trivial ...
Another intriguing research issue concerns the feasibility and scope for mapping the tightly coupled computation model of MPI onto the unrestricted BSP model. ...
doi:10.1109/ucc.2012.52
dblp:conf/ucc/SlawinskiS12
fatcat:mm2nyib7mbhxnlewguehnj3xo4
Combining optimizations in automated low power design
2010
2010 Design, Automation & Test in Europe Conference & Exhibition (DATE 2010)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Starting from sequential programs, we present an approach combining data reuse, multi-level MapReduce, and pipelining to automatically find the most power-efficient designs that meet speed and area constraints ...
missed by separating the optimizations. ...
Next, the analysis toolbox maps the regular loop iteration space in the code onto a polytope space and determines data dependencies and memory access patterns in the loops, for design space exploration ...
doi:10.1109/date.2010.5457104
dblp:conf/date/LiuTL10
fatcat:wsriwopv2fcejlz3lh4zz7qrde
An Abstract Annotation Model for Skeletons
[chapter]
2013
Lecture Notes in Computer Science
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
In this work a first step toward the automated optimization of high level skeleton-based parallel code is discussed. ...
The paper presents an abstract annotation model for skeleton programs aimed at formally describing suitable mapping of parallel activities on a high-level platform representation. ...
The work described in this paper is supported by the EU ParaPhrase project (http://www.paraphrase-ict.eu, 2011-2014). ...
doi:10.1007/978-3-642-35887-6_14
fatcat:j674vzcgibhz5p2ytwfxbrtehu
Monte Carlo simulation of photon migration in a cloud computing environment with MapReduce
2011
Journal of Biomedical Optics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The purpose of this work is to report on our implementation of a simple MapReduce method for performing fault-tolerant Monte Carlo computations in a massively-parallel cloud computing environment. ...
In this implementation, Map tasks compute photon histories in parallel while a Reduce task scores photon absorption. The distributed implementation was evaluated on a commercial compute cloud. ...
The authors would like to acknowledge the Oregon Medical Laser Center for making the MC321 package available online. ...
doi:10.1117/1.3656964
pmid:22191916
pmcid:PMC3273307
fatcat:ftanxuevnnfzbeo342gf57mmcu
Riding the elephant
2011
Proceedings of the 2011 ACM international workshop on Many task computing on grids and supercomputers - MTAGS '11
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
In this paper, we evaluate the programmability of MapReduce and Hadoop for scientific workflow ensembles. ...
in fluid and solid dynamics -all run large numbers of parallel analyses, which we call scientific ensembles. ...
Hadoop Hadoop is an open-source distributed computing platform that implements the MapReduce model. ...
doi:10.1145/2132876.2132888
dblp:conf/sc/DedeGGR11
fatcat:u2xt63v24rgo3ks2jz7cksjr2i
Hadoop Image Processing Framework
2015
2015 IEEE International Congress on Big Data
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
The emergence of processing frameworks such as the Hadoop MapReduce[1] platform addresses the problem of providing a system for computationally intensive data processing and distributed storage. ...
The main aim of the framework is to allow developers of image processing applications to leverage the Hadoop MapReduce framework without having to master its technical details and introduce an additional ...
The ability to parallelize tasks allows for scalable, efficient execution of resource-intensive applications. The Hadoop MapReduce framework provides a platform for such tasks. ...
doi:10.1109/bigdatacongress.2015.80
dblp:conf/bigdata/VemulaC15
fatcat:hwww2m2vynamxpvznbuorn6gja
The application of Hadoop in Structural Bioinformatics
[article]
2018
bioRxiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
This paper reviews the use of the Hadoop platform in Structural Bioinformatics applications. ...
We find that these deployments for the most part use known executables called from MapReduce rather than rewriting the algorithms. ...
Acknowledgements The research in this article was made possible from support from the Department of Computer Science, Royal Holloway, University of London. ...
doi:10.1101/376467
fatcat:3qoeg4h77rfarn5a2gneg3xmhe
Designing Parallel Data Processing for Large-Scale Sensor Orchestration
2016
2016 Intl IEEE Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress (UIC/ATC/ScalCom/CBDCom/IoP/SmartWorld)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
We have developed a prototype 1 of our approach, using Apache Hadoop. We applied it to a case study and obtained significant speedups by parallelizing computations over twelve nodes. ...
Specifically, an application design exposes declarations that are used to generate a programming framework based on the MapReduce programming model. ...
Gupta et al. propose sMapReduce [31] , a programming pattern inspired by the MapReduce programming model for mapping application behavior onto a sensor network and enabling complex data aggregation. sMapReduce ...
doi:10.1109/uic-atc-scalcom-cbdcom-iop-smartworld.2016.0031
dblp:conf/uic/KabacC16
fatcat:qvz2oybacbfr3icqpogvh5pxw4
Melia: A MapReduce Framework on OpenCL-Based FPGAs
2016
IEEE Transactions on Parallel and Distributed Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
We further develop a series of FPGA-centric optimization techniques to improve the efficiency of Melia, and a cost-and resource-based approach to automate the parameter settings for those optimizations ...
However, the design and implementation of MapReduce on FPGAs can be challenging: firstly, FPGAs are usually programmed with hardware description languages, which hurts the programmability of the MapReduce ...
On the other hand, Melia improves the programmability so that the user only needs to implement two primitives (map and reduce), and MapReduce is able to exploit the parallelism in the underlying computing ...
doi:10.1109/tpds.2016.2537805
fatcat:wguvs7g7gfe4fdv2ft2a7sde2y
The application of Hadoop in structural bioinformatics
2018
Briefings in Bioinformatics
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The paper reviews the use of the Hadoop platform in structural bioinformatics applications. ...
We find that these deployments for the most part use known executables called from MapReduce rather than rewriting the algorithms. ...
Acknowledgements The research in this article was made possible from support from the Department of Computer Science, Royal Holloway, University of London. ...
doi:10.1093/bib/bby106
pmid:30462158
fatcat:jbjd3n6eungbfo4etdtlns4wji
An optimized MapReduce workflow scheduling algorithm for heterogeneous computing
2014
Journal of Supercomputing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
The MapReduce framework is considered to be an effective resolution for huge and parallel data processing. ...
The experimental results show that the optimized MapReduce workflow scheduling algorithm can improve the performance of task scheduling and the rationality of resources allocation in heterogeneous computing ...
Acknowledgment The authors are grateful to the three anonymous reviewers for their criticism and comments which have helped to improve the presentation and quality of the paper. ...
doi:10.1007/s11227-014-1335-2
fatcat:cyayhon2fzgkbdvpb4edrigoae
« Previous
Showing results 1 — 15 out of 737 results