scholarly journals Parallel gridded simulation framework for DSSAT-CSM (version 4.7.5.21) using MPI and NetCDF

2021 ◽  
Vol 14 (10) ◽  
pp. 6541-6569
Author(s):  
Phillip D. Alderman
Keyword(s):  
Execution Time ◽  
Large Scale ◽  
Message Passing Interface ◽  
Soil Parameters ◽  
Crop Modeling ◽  
Input Output ◽  
Simulation Framework ◽  
Standard Version ◽  
Text Input ◽  
Systems Model

Abstract. The Decision Support System for Agrotechnology Transfer Cropping Systems Model (DSSAT-CSM) is a widely used crop modeling system that has been integrated into large-scale modeling frameworks. Existing frameworks generate spatially explicit simulated outputs at grid points through an inefficient process of translation from binary spatially referenced inputs to point-specific text input files, followed by translation and aggregation back from point-specific text output files to binary spatially referenced outputs. The main objective of this paper was to document the design and implementation of a parallel gridded simulation framework for DSSAT-CSM. A secondary objective was to provide preliminary analysis of execution time and scaling of the new parallel gridded framework. The parallel gridded framework includes improved code for model-internal data transfer, gridded input–output with the Network Common Data Form (NetCDF) library, and parallelization of simulations using the Message Passing Interface (MPI). Validation simulations with the DSSAT-CSM-CROPSIM-CERES-Wheat model revealed subtle discrepancies in simulated yield due to the rounding of soil parameters in the input routines of the standard DSSAT-CSM. Utilizing NetCDF for direct input–output produced a 3.7- to 4-fold reduction in execution time compared to R- and text-based input–output. Parallelization improved execution time for both versions with between 12.2- (standard version) and 13.4-fold (parallel gridded version) speed-up when comparing 1 to 16 compute cores. Estimates of parallelization of computation ranged between 99.2 % (standard version) and 97.3 % (parallel gridded version), indicating potential for scaling to higher numbers of compute cores.

scholarly journals Parallel gridded simulation framework for DSSAT-CSM (version 4.7.5.21) using MPI and NetCDF

2021 ◽  
Author(s):  
Phillip Alderman
Keyword(s):  
Execution Time ◽  
Large Scale ◽  
Message Passing Interface ◽  
Soil Parameters ◽  
Crop Modeling ◽  
Input Output ◽  
Simulation Framework ◽  
Standard Version ◽  
Text Input ◽  
Systems Model

Abstract. The Decision Support System for Agrotechnology Transfer Cropping Systems Model (DSSAT-CSM) is a widely used crop modeling system that has been integrated into large-scale modeling frameworks. Existing frameworks generate spatially-explicit simulated outputs at grid points through an inefficient process of translation from binary, spatially-referenced inputs to point-specific text input files followed by translation and aggregation back from point-specific, text output files to binary, spatially-referenced outputs. The main objective of this paper was to document the design and implementation of a parallel gridded simulation framework for DSSAT-CSM. A secondary objective was to provide preliminary analysis of execution time and scaling of the new parallel gridded framework. The parallel gridded framework includes improved code for model-internal data transfer, gridded input/output with the Network Common Data Form (NetCDF) library, and parallelization of simulations using the Message Passing Interface (MPI). Validation simulations with the DSSAT-CSM-CROPSIM-CERES-Wheat model revealed subtle discrepancies in simulated yield due to the rounding of soil parameters in the input routines of the standard DSSAT-CSM. Utilizing NetCDF for direct input/output produced a 3.7- to 4-fold reduction in execution time compared to text-based input/output. Parallelization improved execution time for both versions with between 12.2- (standard version) and 13.4-fold (parallel gridded version) speedup when comparing 1 to 16 compute cores. Estimates of parallelization of computation ranged between 99.2 (standard version) and 97.3 percent (parallel gridded version) indicating potential for scaling to higher numbers of compute cores.

scholarly journals A lightweight approach to performance portability with targetDP

2016 ◽  
Vol 32 (2) ◽  
pp. 288-301
Author(s):  
Alan Gray ◽  
Kevin Stratford
Keyword(s):  
Particle Physics ◽  
Message Passing ◽  
Graphics Processing Units ◽  
High Performance ◽  
Large Scale ◽  
Message Passing Interface ◽  
Graphics Processing Unit ◽  
Processing Unit ◽  
Performance Portability ◽  
Graphics Processing

Leading high performance computing systems achieve their status through use of highly parallel devices such as NVIDIA graphics processing units or Intel Xeon Phi many-core CPUs. The concept of performance portability across such architectures, as well as traditional CPUs, is vital for the application programmer. In this paper we describe targetDP, a lightweight abstraction layer which allows grid-based applications to target data parallel hardware in a platform agnostic manner. We demonstrate the effectiveness of our pragmatic approach by presenting performance results for a complex fluid application (with which the model was co-designed), plus separate lattice quantum chromodynamics particle physics code. For each application, a single source code base is seen to achieve portable performance, as assessed within the context of the Roofline model. TargetDP can be combined with Message Passing Interface (MPI) to allow use on systems containing multiple nodes: we demonstrate this through provision of scaling results on traditional and graphics processing unit-accelerated large scale supercomputers.

LESS: LargE-Scale remote sensing data and image simulation framework over heterogeneous 3D scenes

2019 ◽  
Vol 221 ◽  
pp. 695-706 ◽  
Author(s):  
Jianbo Qi ◽  
Donghui Xie ◽  
Tiangang Yin ◽  
Guangjian Yan ◽  
Jean-Philippe Gastellu-Etchegorry ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Remote Sensing Data ◽  
Image Simulation ◽  
Simulation Framework ◽  
Sensing Data

scholarly journals tHapMix: simulating tumour samples through haplotype mixtures

2016 ◽  
Author(s):  
Sergii Ivakhno ◽  
Camilla Colombo ◽  
Stephen Tanner ◽  
Philip Tedder ◽  
Stefano Berri ◽  
...  
Keyword(s):  
Copy Number ◽  
Large Scale ◽  
Variant Calling ◽  
Copy Number Variant ◽  
Supplementary Information ◽  
Genome Diversity ◽  
Simulation Framework ◽  
Somatic Genome ◽  
Copy Number Changes ◽  
Sequencing Platforms

AbstractMotivationLarge-scale rearrangements and copy number changes combined with different modes of cloevolution create extensive somatic genome diversity, making it difficult to develop versatile and scalable oriant calling tools and create well-calibrated benchmarks.ResultsWe developed a new simulation framework tHapMix that enables the creation of tumour samples with different ploidy, purity and polyclonality features. It easily scales to simulation of hundreds of somatic genomes, while re-use of real read data preserves noise and biases present in sequencing platforms. We further demonstrate tHapMix utility by creating a simulated set of 140 somatic genomes and showing how it can be used in training and testing of somatic copy number variant calling tools.Availability and implementationtHapMix is distributed under an open source license and can be downloaded from https://github.com/Illumina/[email protected] informationSupplementary data are available at Bioinformatics online.

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