Ravi Reddy Manumachu's Research

Welcome to my webpage on my research interests.

I am a research fellow in heterogeneous computing laboratory (HCL), School of Computer Science, University College Dublin, Dublin, Ireland.
My main research interests are high performance heterogeneous computing, distributed computing, sparse matrix computations, and cryptography.

My full list of publications are available here:
Google Scholar
ResearchGate

My latest publications:

Performance Optimization of Multithreaded 2D Fast Fourier Transform on Multicore Processors Using Load Imbalancing Parallel Computing Method
IEEE Access, IEEE, 2018
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Bi-Objective Optimization of Data-Parallel Applications on Homogeneous Multicore Clusters for Performance and Energy
IEEE Transactions on Computers, vol. 67, issue 2, IEEE, 2017
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Other notable publications:

A Novel Data-Partitioning Algorithm for Performance Optimization of Data-Parallel Applications on Heterogeneous HPC Platforms
IEEE Transactions on Parallel and Distributed Systems, IEEE, 2018
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Design of Self-adaptable Data Parallel Applications on Multicore Clusters Automatically Optimized for Performance and Energy
Concurrency and Computation: Practice and Experience, Wiley, 2018
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A Survey of Power and Energy Predictive Models in HPC Systems and Applications
ACM Computing Surveys, vol. 50, issue 3: ACM, 07/2017
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New Model-based Methods and Algorithms for Performance and Energy Optimization of Data Parallel Applications on Homogeneous Multicore Clusters
IEEE Transactions on Parallel and Distributed Systems, vol. 28, issue 4: IEEE, pp. 1119-1133, 04/2017
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Additivity: A Selection Criterion for Performance Events for Reliable Energy Predictive Modeling
Supercomputing Frontiers and Innovations, vol. 4, issue 4, 2017
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Out-of-core implementation for accelerator kernels on heterogeneous clouds
The Journal of Supercomputing, 09/2017
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Data distribution for dense factorization on computers with memory heterogeneity
Parallel Computing, vol. 33, issue 12, pp. 757-779, 12/2007
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Data Partitioning with a Functional Performance Model of Heterogeneous Processors
International Journal of High Performance Computing Applications, vol. 21, issue 1: Sage, pp. 76-90, 2007
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HeteroMPI: Towards a Message-Passing Library for Heterogeneous Networks of Computers
Journal of Parallel and Distributed Computing, vol. 66, issue 2: Elsevier, pp. 197-220, 2006
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On Performance Analysis of Heterogeneous Parallel Algorithms
Parallel Computing, vol. 30, issue 11, pp. 1195-1216, 2004
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Ph.D Thesis:

HMPI: A Message-Passing Library for Heterogeneous Networks of Computers
School of Computer Science, University College Dublin, Dublin, pp. 456, 06/2005
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Softwares:

hclfft: Software Implementations of Multithreaded 2D Fast Fourier Transform on Multicore Processors Using Load Imbalancing Parallel Computing Method, 2017
hclfft

PARALEPH: Parallel ALgorithms for Energy and Performance using functional performance models for Homogeneous Multicore Clusters, 2017
PARALEPH

ALEPH: ALgorithms for Energy and Performance using functional performance models for Homogeneous Multicore Clusters, 2016
ALEPH

HeteroScaLAPACK: A Linear Algebra Library for Heterogeneous Networks of Computers, 2010
HeteroScaLAPACK

HeteroMPI: An extension of MPI for high performance heterogeneous computing, 2004
HeteroMPI