The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform

Lara Dolecek - One of the best experts on this subject based on the ideXlab platform.

  • The weight consistency matrix framework for general non-binary LDPC Code Optimization: Applications in flash memories
    2016 IEEE International Symposium on Information Theory (ISIT), 2016
    Co-Authors: Ahmed Hareedy, Chinmayi Radhakrishna Lanka, Clayton Schoeny, Lara Dolecek
    Abstract:

    Transmission channels underlying modern memory systems, e.g., Flash memories, possess a significant amount of asymmetry. While existing LDPC Codes optimized for symmetric, AWGN-like channels are being actively considered for Flash applications, we demonstrate that, due to channel asymmetry, such approaches are fairly inadequate. We propose a new, general, combinatorial framework for the analysis and design of non-binary LDPC (NB-LDPC) Codes for asymmetric channels. We introduce a refined definition of absorbing sets, which we call general absorbing sets (GASs), and an important subclass of GASs, which we refer to as general absorbing sets of type two (GASTs). Additionally, we study the combinatorial properties of GASTs. We then present the weight consistency matrix (WCM), which succinctly captures key properties in a GAST. Based on these new concepts, we then develop a general Code Optimization framework, and demonstrate its effectiveness on the realistic highly-asymmetric normal-Laplace mixture (NLM) Flash channel. Our optimized Codes enjoy over one order (resp., half of an order) of magnitude performance gain in the uncorrectable BER (UBER) relative to the unoptimized Codes (resp. the Codes optimized for symmetric channels).

  • ISIT - The weight consistency matrix framework for general non-binary LDPC Code Optimization: Applications in flash memories
    2016 IEEE International Symposium on Information Theory (ISIT), 2016
    Co-Authors: Ahmed Hareedy, Chinmayi Radhakrishna Lanka, Clayton Schoeny, Lara Dolecek
    Abstract:

    Transmission channels underlying modern memory systems, e.g., Flash memories, possess a significant amount of asymmetry. While existing LDPC Codes optimized for symmetric, AWGN-like channels are being actively considered for Flash applications, we demonstrate that, due to channel asymmetry, such approaches are fairly inadequate. We propose a new, general, combinatorial framework for the analysis and design of non-binary LDPC (NB-LDPC) Codes for asymmetric channels. We introduce a refined definition of absorbing sets, which we call general absorbing sets (GASs), and an important subclass of GASs, which we refer to as general absorbing sets of type two (GASTs). Additionally, we study the combinatorial properties of GASTs. We then present the weight consistency matrix (WCM), which succinctly captures key properties in a GAST. Based on these new concepts, we then develop a general Code Optimization framework, and demonstrate its effectiveness on the realistic highly-asymmetric normal-Laplace mixture (NLM) Flash channel. Our optimized Codes enjoy over one order (resp., half of an order) of magnitude performance gain in the uncorrectable BER (UBER) relative to the unoptimized Codes (resp. the Codes optimized for symmetric channels).

  • A General Non-Binary LDPC Code Optimization Framework Suitable for Dense Flash Memory and Magnetic Storage
    IEEE Journal on Selected Areas in Communications, 2016
    Co-Authors: Ahmed Hareedy, Chinmayi Radhakrishna Lanka, Lara Dolecek
    Abstract:

    Transmission channels underlying modern dense storage systems, e.g., Flash memory and magnetic recording (MR) systems, significantly differ from canonical channels, like additive white Gaussian noise (AWGN) channels. While existing low-density parity-check (LDPC) Codes optimized for symmetric, AWGN-like channels are being actively considered for Flash applications, we demonstrate that, due to channel asymmetry, such approaches are inadequate. We introduce a refined definition of absorbing sets, which we call general absorbing sets of type two (GASTs), and study the combinatorial properties of GASTs. We then present the weight consistency matrix (WCM), which succinctly captures key properties in a GAST. Furthermore, we show how to customize the WCM definition such that it suits other special subclasses of GASTs. Based on these new concepts, we then develop a new, general combinatorial Code Optimization framework, which we call the WCM framework, and demonstrate its effectiveness on the realistic highly-asymmetric normal-Laplace mixture (NLM) Flash channel. Moreover, we show that our framework can be customized to optimize non-binary LDPC (NB-LDPC) Codes for other asymmetric channels, channels with memory (incorporated in MR systems), and canonical symmetric channels. For all the channels we have simulated NB-LDPC Codes over, the Codes optimized using the WCM framework enjoy at least 1 order, and up to nearly 2 orders of magnitude performance gain in the uncorrectable bit error rate (UBER) or the frame error rate (FER) relative to the unoptimized Codes. Our simulations also show that Codes optimized for symmetric channels are not the best choice for asymmetric channels.

  • Non-Binary LDPC Code Optimization for Partial-Response Channels
    2015 IEEE Global Communications Conference (GLOBECOM), 2015
    Co-Authors: Ahmed Hareedy, Behzad Amiri, Shancheng Zhao, Richard Galbraith, Lara Dolecek
    Abstract:

    In this paper, we analyze and optimize non- binary low-density parity-check (NB-LDPC) Codes for magnetic recording applications. While the topic of the error floor performance of binary LDPC Codes over additive white Gaussian noise (AWGN) channels has recently received considerable attention, very little is known about the error floor performance of NB-LDPC Codes over other types of channels, despite the early results demonstrating superior characteristics of NB-LDPC Codes relative to their binary counterparts. We first show that, due to outer looping between detector and deCoder in the receiver, the error profile of NB-LDPC Codes over partial-response (PR) channels is qualitatively different from the error profile over AWGN channels - this observation motivates us to introduce new combinatorial definitions aimed at capturing decoding errors that dominate PR channel error floor region. We call these errors (or objects) balanced absorbing sets (BASs), which are viewed as a special subclass of previously introduced absorbing sets (ASs). Additionally, we prove that due to the more restrictive definition of BASs (relative to the more general class of ASs), an additional degree of freedom can be exploited in Code design for PR channels. We then demonstrate that the proposed Code Optimization aimed at removing dominant BASs offers improvements in the frame error rate (FER) in the error floor region by up to 2.5 orders of magnitude over the uninformed designs. Our Code Optimization technique carefully yet provably removes BASs from the Code while preserving its overall structure (node degree, quasi-cyclic property, regularity, etc.). The resulting Codes outperform existing binary and NB-LDPC solutions for PR channels by about 2.5 and 1.5 orders of magnitude, respectively.

  • GLOBECOM - Non-Binary LDPC Code Optimization for Partial-Response Channels
    2015 IEEE Global Communications Conference (GLOBECOM), 2014
    Co-Authors: Ahmed Hareedy, Behzad Amiri, Shancheng Zhao, Richard Leo Galbraith, Lara Dolecek
    Abstract:

    In this paper, we analyze and optimize non- binary low-density parity-check (NB-LDPC) Codes for magnetic recording applications. While the topic of the error floor performance of binary LDPC Codes over additive white Gaussian noise (AWGN) channels has recently received considerable attention, very little is known about the error floor performance of NB-LDPC Codes over other types of channels, despite the early results demonstrating superior characteristics of NB-LDPC Codes relative to their binary counterparts. We first show that, due to outer looping between detector and deCoder in the receiver, the error profile of NB-LDPC Codes over partial-response (PR) channels is qualitatively different from the error profile over AWGN channels - this observation motivates us to introduce new combinatorial definitions aimed at capturing decoding errors that dominate PR channel error floor region. We call these errors (or objects) balanced absorbing sets (BASs), which are viewed as a special subclass of previously introduced absorbing sets (ASs). Additionally, we prove that due to the more restrictive definition of BASs (relative to the more general class of ASs), an additional degree of freedom can be exploited in Code design for PR channels. We then demonstrate that the proposed Code Optimization aimed at removing dominant BASs offers improvements in the frame error rate (FER) in the error floor region by up to 2.5 orders of magnitude over the uninformed designs. Our Code Optimization technique carefully yet provably removes BASs from the Code while preserving its overall structure (node degree, quasi-cyclic property, regularity, etc.). The resulting Codes outperform existing binary and NB-LDPC solutions for PR channels by about 2.5 and 1.5 orders of magnitude, respectively.

Ahmed Hareedy - One of the best experts on this subject based on the ideXlab platform.

  • The weight consistency matrix framework for general non-binary LDPC Code Optimization: Applications in flash memories
    2016 IEEE International Symposium on Information Theory (ISIT), 2016
    Co-Authors: Ahmed Hareedy, Chinmayi Radhakrishna Lanka, Clayton Schoeny, Lara Dolecek
    Abstract:

    Transmission channels underlying modern memory systems, e.g., Flash memories, possess a significant amount of asymmetry. While existing LDPC Codes optimized for symmetric, AWGN-like channels are being actively considered for Flash applications, we demonstrate that, due to channel asymmetry, such approaches are fairly inadequate. We propose a new, general, combinatorial framework for the analysis and design of non-binary LDPC (NB-LDPC) Codes for asymmetric channels. We introduce a refined definition of absorbing sets, which we call general absorbing sets (GASs), and an important subclass of GASs, which we refer to as general absorbing sets of type two (GASTs). Additionally, we study the combinatorial properties of GASTs. We then present the weight consistency matrix (WCM), which succinctly captures key properties in a GAST. Based on these new concepts, we then develop a general Code Optimization framework, and demonstrate its effectiveness on the realistic highly-asymmetric normal-Laplace mixture (NLM) Flash channel. Our optimized Codes enjoy over one order (resp., half of an order) of magnitude performance gain in the uncorrectable BER (UBER) relative to the unoptimized Codes (resp. the Codes optimized for symmetric channels).

  • ISIT - The weight consistency matrix framework for general non-binary LDPC Code Optimization: Applications in flash memories
    2016 IEEE International Symposium on Information Theory (ISIT), 2016
    Co-Authors: Ahmed Hareedy, Chinmayi Radhakrishna Lanka, Clayton Schoeny, Lara Dolecek
    Abstract:

    Transmission channels underlying modern memory systems, e.g., Flash memories, possess a significant amount of asymmetry. While existing LDPC Codes optimized for symmetric, AWGN-like channels are being actively considered for Flash applications, we demonstrate that, due to channel asymmetry, such approaches are fairly inadequate. We propose a new, general, combinatorial framework for the analysis and design of non-binary LDPC (NB-LDPC) Codes for asymmetric channels. We introduce a refined definition of absorbing sets, which we call general absorbing sets (GASs), and an important subclass of GASs, which we refer to as general absorbing sets of type two (GASTs). Additionally, we study the combinatorial properties of GASTs. We then present the weight consistency matrix (WCM), which succinctly captures key properties in a GAST. Based on these new concepts, we then develop a general Code Optimization framework, and demonstrate its effectiveness on the realistic highly-asymmetric normal-Laplace mixture (NLM) Flash channel. Our optimized Codes enjoy over one order (resp., half of an order) of magnitude performance gain in the uncorrectable BER (UBER) relative to the unoptimized Codes (resp. the Codes optimized for symmetric channels).

  • A General Non-Binary LDPC Code Optimization Framework Suitable for Dense Flash Memory and Magnetic Storage
    IEEE Journal on Selected Areas in Communications, 2016
    Co-Authors: Ahmed Hareedy, Chinmayi Radhakrishna Lanka, Lara Dolecek
    Abstract:

    Transmission channels underlying modern dense storage systems, e.g., Flash memory and magnetic recording (MR) systems, significantly differ from canonical channels, like additive white Gaussian noise (AWGN) channels. While existing low-density parity-check (LDPC) Codes optimized for symmetric, AWGN-like channels are being actively considered for Flash applications, we demonstrate that, due to channel asymmetry, such approaches are inadequate. We introduce a refined definition of absorbing sets, which we call general absorbing sets of type two (GASTs), and study the combinatorial properties of GASTs. We then present the weight consistency matrix (WCM), which succinctly captures key properties in a GAST. Furthermore, we show how to customize the WCM definition such that it suits other special subclasses of GASTs. Based on these new concepts, we then develop a new, general combinatorial Code Optimization framework, which we call the WCM framework, and demonstrate its effectiveness on the realistic highly-asymmetric normal-Laplace mixture (NLM) Flash channel. Moreover, we show that our framework can be customized to optimize non-binary LDPC (NB-LDPC) Codes for other asymmetric channels, channels with memory (incorporated in MR systems), and canonical symmetric channels. For all the channels we have simulated NB-LDPC Codes over, the Codes optimized using the WCM framework enjoy at least 1 order, and up to nearly 2 orders of magnitude performance gain in the uncorrectable bit error rate (UBER) or the frame error rate (FER) relative to the unoptimized Codes. Our simulations also show that Codes optimized for symmetric channels are not the best choice for asymmetric channels.

  • Non-Binary LDPC Code Optimization for Partial-Response Channels
    2015 IEEE Global Communications Conference (GLOBECOM), 2015
    Co-Authors: Ahmed Hareedy, Behzad Amiri, Shancheng Zhao, Richard Galbraith, Lara Dolecek
    Abstract:

    In this paper, we analyze and optimize non- binary low-density parity-check (NB-LDPC) Codes for magnetic recording applications. While the topic of the error floor performance of binary LDPC Codes over additive white Gaussian noise (AWGN) channels has recently received considerable attention, very little is known about the error floor performance of NB-LDPC Codes over other types of channels, despite the early results demonstrating superior characteristics of NB-LDPC Codes relative to their binary counterparts. We first show that, due to outer looping between detector and deCoder in the receiver, the error profile of NB-LDPC Codes over partial-response (PR) channels is qualitatively different from the error profile over AWGN channels - this observation motivates us to introduce new combinatorial definitions aimed at capturing decoding errors that dominate PR channel error floor region. We call these errors (or objects) balanced absorbing sets (BASs), which are viewed as a special subclass of previously introduced absorbing sets (ASs). Additionally, we prove that due to the more restrictive definition of BASs (relative to the more general class of ASs), an additional degree of freedom can be exploited in Code design for PR channels. We then demonstrate that the proposed Code Optimization aimed at removing dominant BASs offers improvements in the frame error rate (FER) in the error floor region by up to 2.5 orders of magnitude over the uninformed designs. Our Code Optimization technique carefully yet provably removes BASs from the Code while preserving its overall structure (node degree, quasi-cyclic property, regularity, etc.). The resulting Codes outperform existing binary and NB-LDPC solutions for PR channels by about 2.5 and 1.5 orders of magnitude, respectively.

  • GLOBECOM - Non-Binary LDPC Code Optimization for Partial-Response Channels
    2015 IEEE Global Communications Conference (GLOBECOM), 2014
    Co-Authors: Ahmed Hareedy, Behzad Amiri, Shancheng Zhao, Richard Leo Galbraith, Lara Dolecek
    Abstract:

    In this paper, we analyze and optimize non- binary low-density parity-check (NB-LDPC) Codes for magnetic recording applications. While the topic of the error floor performance of binary LDPC Codes over additive white Gaussian noise (AWGN) channels has recently received considerable attention, very little is known about the error floor performance of NB-LDPC Codes over other types of channels, despite the early results demonstrating superior characteristics of NB-LDPC Codes relative to their binary counterparts. We first show that, due to outer looping between detector and deCoder in the receiver, the error profile of NB-LDPC Codes over partial-response (PR) channels is qualitatively different from the error profile over AWGN channels - this observation motivates us to introduce new combinatorial definitions aimed at capturing decoding errors that dominate PR channel error floor region. We call these errors (or objects) balanced absorbing sets (BASs), which are viewed as a special subclass of previously introduced absorbing sets (ASs). Additionally, we prove that due to the more restrictive definition of BASs (relative to the more general class of ASs), an additional degree of freedom can be exploited in Code design for PR channels. We then demonstrate that the proposed Code Optimization aimed at removing dominant BASs offers improvements in the frame error rate (FER) in the error floor region by up to 2.5 orders of magnitude over the uninformed designs. Our Code Optimization technique carefully yet provably removes BASs from the Code while preserving its overall structure (node degree, quasi-cyclic property, regularity, etc.). The resulting Codes outperform existing binary and NB-LDPC solutions for PR channels by about 2.5 and 1.5 orders of magnitude, respectively.

Jorge Revuelta Herrero - One of the best experts on this subject based on the ideXlab platform.

  • Acceleration of the Geostatistical Software Library (GSLIB) by Code Optimization and hybrid parallel programming
    Computers & Geosciences, 2015
    Co-Authors: Oscar Peredo, Julian M. Ortiz, Jorge Revuelta Herrero
    Abstract:

    The Geostatistical Software Library (GSLIB) has been used in the geostatistical community for more than thirty years. It was designed as a bundle of sequential Fortran Codes, and today it is still in use by many practitioners and researchers. Despite its widespread use, few attempts have been reported in order to bring this package to the multi-core era. Using all CPU resources, GSLIB algorithms can handle large datasets and grids, where tasks are compute- and memory-intensive applications. In this work, a methodology is presented to accelerate GSLIB applications using Code Optimization and hybrid parallel processing, specifically for compute-intensive applications. Minimal Code modifications are added decreasing as much as possible the elapsed time of execution of the studied routines. If multi-core processing is available, the user can activate OpenMP directives to speed up the execution using all resources of the CPU. If multi-node processing is available, the execution is enhanced using MPI messages between the compute nodes.Four case studies are presented: experimental variogram calculation, kriging estimation, sequential gaussian and indicator simulation. For each application, three scenarios (small, large and extra large) are tested using a desktop environment with 4 CPU-cores and a multi-node server with 128 CPU-nodes. Elapsed times, speedup and efficiency results are shown. HighlightsThis work is part of an effort to accelerate geostatistical simulation Codes.We apply acceleration techniques to a package of legacy geostatistical Codes (GSLIB).Acceleration techniques are Code Optimization and hybrid OpenMP/MPI parallelization.Accelerations were applied to variogram, kriging and sequential simulation.Elapsed time and speedup results are shown.

  • Acceleration of the Geostatistical Software Library (GSLIB) by Code Optimization and hybrid parallel programming
    Computers and Geosciences, 2015
    Co-Authors: Oscar Peredo, Julian M. Ortiz, Jorge Revuelta Herrero
    Abstract:

    The Geostatistical Software Library (GSLIB) has been used in the geostatistical community for more than thirty years. It was designed as a bundle of sequential Fortran Codes, and today it is still in use by many practitioners and researchers. Despite its widespread use, few attempts have been reported in order to bring this package to the multi-core era. Using all CPU resources, GSLIB algorithms can handle large datasets and grids, where tasks are compute- and memory-intensive applications. In this work, a methodology is presented to accelerate GSLIB applications using Code Optimization and hybrid parallel processing, specifically for compute-intensive applications. Minimal Code modifications are added decreasing as much as possible the elapsed time of execution of the studied routines. If multi-core processing is available, the user can activate OpenMP directives to speed up the execution using all resources of the CPU. If multi-node processing is available, the execution is enhanced using MPI messages between the compute nodes.Four case studies are presented: experimental variogram calculation, kriging estimation, sequential gaussian and indicator simulation. For each application, three scenarios (small, large and extra large) are tested using a desktop environment with 4 CPU-cores and a multi-node server with 128 CPU-nodes. Elapsed times, speedup and efficiency results are shown.

Chinmayi Radhakrishna Lanka - One of the best experts on this subject based on the ideXlab platform.

  • Weight Consistency Matrix Framework for Non-Binary LDPC Code Optimization
    2020
    Co-Authors: Chinmayi Radhakrishna Lanka
    Abstract:

    Transmission channels underlying modern memory systems, e.g., Flash memories, possess a signicant amount of asymmetry. While existing LDPC Codes optimized forsymmetric, AWGN-like channels are being actively considered for Flash applications, wedemonstrate that, due to channel asymmetry, such approaches are fairly inadequate. Wepropose a new, general, combinatorial framework for the analysis and design of non-binary LDPC (NB-LDPC) Codes for asymmetric channels.We introduce a refined definition of absorbing sets, which we call general absorbing sets (GASs), and an important subclass of GASs, which we refer to as general absorbing sets of type two (GASTs). Additionally, we study the combinatorial properties of GASTs. We then present the weight consistency matrix (WCM), which succinctly captures key properties in a GAST. Based on these new concepts, we then develop a general Code Optimization framework, and demonstrate its effectiveness on the realistic Flash channels. Our optimized designs enjoy over one order of magnitude performance gain in the uncorrectable BER (UBER) relative to the unoptimized Codes.

  • The weight consistency matrix framework for general non-binary LDPC Code Optimization: Applications in flash memories
    2016 IEEE International Symposium on Information Theory (ISIT), 2016
    Co-Authors: Ahmed Hareedy, Chinmayi Radhakrishna Lanka, Clayton Schoeny, Lara Dolecek
    Abstract:

    Transmission channels underlying modern memory systems, e.g., Flash memories, possess a significant amount of asymmetry. While existing LDPC Codes optimized for symmetric, AWGN-like channels are being actively considered for Flash applications, we demonstrate that, due to channel asymmetry, such approaches are fairly inadequate. We propose a new, general, combinatorial framework for the analysis and design of non-binary LDPC (NB-LDPC) Codes for asymmetric channels. We introduce a refined definition of absorbing sets, which we call general absorbing sets (GASs), and an important subclass of GASs, which we refer to as general absorbing sets of type two (GASTs). Additionally, we study the combinatorial properties of GASTs. We then present the weight consistency matrix (WCM), which succinctly captures key properties in a GAST. Based on these new concepts, we then develop a general Code Optimization framework, and demonstrate its effectiveness on the realistic highly-asymmetric normal-Laplace mixture (NLM) Flash channel. Our optimized Codes enjoy over one order (resp., half of an order) of magnitude performance gain in the uncorrectable BER (UBER) relative to the unoptimized Codes (resp. the Codes optimized for symmetric channels).

  • ISIT - The weight consistency matrix framework for general non-binary LDPC Code Optimization: Applications in flash memories
    2016 IEEE International Symposium on Information Theory (ISIT), 2016
    Co-Authors: Ahmed Hareedy, Chinmayi Radhakrishna Lanka, Clayton Schoeny, Lara Dolecek
    Abstract:

    Transmission channels underlying modern memory systems, e.g., Flash memories, possess a significant amount of asymmetry. While existing LDPC Codes optimized for symmetric, AWGN-like channels are being actively considered for Flash applications, we demonstrate that, due to channel asymmetry, such approaches are fairly inadequate. We propose a new, general, combinatorial framework for the analysis and design of non-binary LDPC (NB-LDPC) Codes for asymmetric channels. We introduce a refined definition of absorbing sets, which we call general absorbing sets (GASs), and an important subclass of GASs, which we refer to as general absorbing sets of type two (GASTs). Additionally, we study the combinatorial properties of GASTs. We then present the weight consistency matrix (WCM), which succinctly captures key properties in a GAST. Based on these new concepts, we then develop a general Code Optimization framework, and demonstrate its effectiveness on the realistic highly-asymmetric normal-Laplace mixture (NLM) Flash channel. Our optimized Codes enjoy over one order (resp., half of an order) of magnitude performance gain in the uncorrectable BER (UBER) relative to the unoptimized Codes (resp. the Codes optimized for symmetric channels).

  • A General Non-Binary LDPC Code Optimization Framework Suitable for Dense Flash Memory and Magnetic Storage
    IEEE Journal on Selected Areas in Communications, 2016
    Co-Authors: Ahmed Hareedy, Chinmayi Radhakrishna Lanka, Lara Dolecek
    Abstract:

    Transmission channels underlying modern dense storage systems, e.g., Flash memory and magnetic recording (MR) systems, significantly differ from canonical channels, like additive white Gaussian noise (AWGN) channels. While existing low-density parity-check (LDPC) Codes optimized for symmetric, AWGN-like channels are being actively considered for Flash applications, we demonstrate that, due to channel asymmetry, such approaches are inadequate. We introduce a refined definition of absorbing sets, which we call general absorbing sets of type two (GASTs), and study the combinatorial properties of GASTs. We then present the weight consistency matrix (WCM), which succinctly captures key properties in a GAST. Furthermore, we show how to customize the WCM definition such that it suits other special subclasses of GASTs. Based on these new concepts, we then develop a new, general combinatorial Code Optimization framework, which we call the WCM framework, and demonstrate its effectiveness on the realistic highly-asymmetric normal-Laplace mixture (NLM) Flash channel. Moreover, we show that our framework can be customized to optimize non-binary LDPC (NB-LDPC) Codes for other asymmetric channels, channels with memory (incorporated in MR systems), and canonical symmetric channels. For all the channels we have simulated NB-LDPC Codes over, the Codes optimized using the WCM framework enjoy at least 1 order, and up to nearly 2 orders of magnitude performance gain in the uncorrectable bit error rate (UBER) or the frame error rate (FER) relative to the unoptimized Codes. Our simulations also show that Codes optimized for symmetric channels are not the best choice for asymmetric channels.

Oscar Peredo - One of the best experts on this subject based on the ideXlab platform.

  • Acceleration of the Geostatistical Software Library (GSLIB) by Code Optimization and hybrid parallel programming
    Computers & Geosciences, 2015
    Co-Authors: Oscar Peredo, Julian M. Ortiz, Jorge Revuelta Herrero
    Abstract:

    The Geostatistical Software Library (GSLIB) has been used in the geostatistical community for more than thirty years. It was designed as a bundle of sequential Fortran Codes, and today it is still in use by many practitioners and researchers. Despite its widespread use, few attempts have been reported in order to bring this package to the multi-core era. Using all CPU resources, GSLIB algorithms can handle large datasets and grids, where tasks are compute- and memory-intensive applications. In this work, a methodology is presented to accelerate GSLIB applications using Code Optimization and hybrid parallel processing, specifically for compute-intensive applications. Minimal Code modifications are added decreasing as much as possible the elapsed time of execution of the studied routines. If multi-core processing is available, the user can activate OpenMP directives to speed up the execution using all resources of the CPU. If multi-node processing is available, the execution is enhanced using MPI messages between the compute nodes.Four case studies are presented: experimental variogram calculation, kriging estimation, sequential gaussian and indicator simulation. For each application, three scenarios (small, large and extra large) are tested using a desktop environment with 4 CPU-cores and a multi-node server with 128 CPU-nodes. Elapsed times, speedup and efficiency results are shown. HighlightsThis work is part of an effort to accelerate geostatistical simulation Codes.We apply acceleration techniques to a package of legacy geostatistical Codes (GSLIB).Acceleration techniques are Code Optimization and hybrid OpenMP/MPI parallelization.Accelerations were applied to variogram, kriging and sequential simulation.Elapsed time and speedup results are shown.

  • Acceleration of the Geostatistical Software Library (GSLIB) by Code Optimization and hybrid parallel programming
    Computers and Geosciences, 2015
    Co-Authors: Oscar Peredo, Julian M. Ortiz, Jorge Revuelta Herrero
    Abstract:

    The Geostatistical Software Library (GSLIB) has been used in the geostatistical community for more than thirty years. It was designed as a bundle of sequential Fortran Codes, and today it is still in use by many practitioners and researchers. Despite its widespread use, few attempts have been reported in order to bring this package to the multi-core era. Using all CPU resources, GSLIB algorithms can handle large datasets and grids, where tasks are compute- and memory-intensive applications. In this work, a methodology is presented to accelerate GSLIB applications using Code Optimization and hybrid parallel processing, specifically for compute-intensive applications. Minimal Code modifications are added decreasing as much as possible the elapsed time of execution of the studied routines. If multi-core processing is available, the user can activate OpenMP directives to speed up the execution using all resources of the CPU. If multi-node processing is available, the execution is enhanced using MPI messages between the compute nodes.Four case studies are presented: experimental variogram calculation, kriging estimation, sequential gaussian and indicator simulation. For each application, three scenarios (small, large and extra large) are tested using a desktop environment with 4 CPU-cores and a multi-node server with 128 CPU-nodes. Elapsed times, speedup and efficiency results are shown.