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Design and Comparison of parallel Dynamic Matérn Kernel-Based Regression Models and Machine Learning Approaches: Application to Bias Correction in Numerical Weather Prediction

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COMMUNICATIONS ON APPLIED MATHEMATICS AND COMPUTATION 2025年

作者： Migallon, Violeta Penades, Hector Penades, Jose Univ Alicante Dept Ciencia Comp & Inteligencia Artificial Alicante 03690 Spain

Mathematical modelling is fundamental to understanding real-world phenomena. Despite the inherent complexity in designing such models, numerical approaches and, more recently, machine learning techniques, have emerged as powerful tools in this area. This work proposes integrating the finite element method (FEM) into forecasting and introduces parallel techniques for regression problems, with a specific focus on the use of Mat & eacute;rn kernels on local mesh support. This approach generalises the modelling based on radial basis function kernels and offers more flexibility to control the smoothness of the modelled functions. An exhaustive study explores the impact of diverse norms and Mat & eacute;rn kernel variations on the performance of models, and aims to improve the computational efficiency of the model fitting and prediction processes. Furthermore, a heuristic framework is introduced to derive optimal complexity parameters for each Mat & eacute;rn-based FEM kernel. The proposed parallel approaches use dynamic strategies, which significantly reduce the computational time of the algorithms compared to other methods and parallel computing techniques presented in recent years. The proposed methodology is assessed in the context of bias corrections for temperature forecasts made by the Local Data Assimilation and Prediction System (LDAPS) model. A comprehensive comparative analysis which includes machine learning algorithms provides significant insights into the training process, norm selection, and kernel choice, and shows that Mat & eacute;rn-based methods emerge as a choice to be considered for regression problems.

关键词： Numerical modelling parallel programming Mat & eacute rn kernels Machine learning

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parallel Block-Delayed Sequences 22

Parallel Block-Delayed Sequences

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27th ACM SIGPLAN Symposium on Principles and Practice of parallel programming (PPoPP)

作者： Westrick, Sam Rainey, Mike Anderson, Daniel Blelloch, Guy E. Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9781450392044

programming languages using functions on collections of values, such as map, reduce, scan and filter, have been used for over fifty years. Such collections have proven to be particularly useful in the context of parallelism because such functions are naturally parallel. However, if implemented naively they lead to the generation of temporary intermediate collections that can significantly increase memory usage and runtime. To avoid this pitfall, many approaches use "fusion" to combine operations and avoid temporary results. However, most of these approaches involve significant changes to a compiler and are limited to a small set of functions, such as maps and reduces. In this paper we present a library-based approach that fuses widely used operations such as scans, filters, and flattens. In conjunction with existing techniques, this covers most of the common operations on collections. Our approach is based on a novel technique which parallelizes over blocks, with streams within each block. We demonstrate the approach by implementing libraries targeting multicore parallelism in two languages: parallel ML and C++, which have very different semantics and compilers. To help users understand when to use the approach, we define a cost semantics that indicates when fusion occurs and how it reduces memory allocations. We present experimental results for a dozen benchmarks that demonstrate significant reductions in both time and space. In most cases the approach generates code that is near optimal for the machines it is running on.

关键词： parallel programming fusion collections functional programming

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Facilitating the learning process in parallel computing by using instant messaging

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JOURNAL OF SUPERCOMPUTING 2021年第4期77卷 3899-3913页

作者： Guerrero-Higueras, Angel Manuel Sanchez-Gonzalez, Lidia Conde-Gonzalez, Miguel Angel Castejon-Limas, Manuel Univ Leon Dept Mech Comp Sci & Aerosp Engn Campus Vegazana S-N Leon 24071 Spain

parallel programming skills may require a long time to acquire. "Think in parallel" is a skill that requires time, effort, and experience. In this work, we propose to facilitate the students' learning process in parallel programming by using instant messaging. Our aim was to find out whether students' interaction through instant messaging tools is beneficial for the learning process. In order to do so, we asked several students of an HPC course of the Master's degree in Computer Science of the University of Leon to develop a specific parallel application, each of them using a different application program interface: OpenMP, MPI, CUDA, or OpenCL. Even though the used APIs are different, there are common points in the design process. We encouraged students to interact with each other by using Gitter, an instant messaging tool for GitHub users. Our analysis of the communications and results demonstrate that the direct interaction of students through the Gitter tool has a positive impact on the learning process.

关键词： High-performance computing Instant messaging parallel programming

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Highly Efficient and Scalable Framework for High-Speed Super-Resolution Microscopy

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IEEE ACCESS 2021年 9卷 97053-97067页

作者： Do, Quan Acuna, Sebastian Kristiansen, Jon Ivar Agarwal, Krishna Ha, Phuong Hoai UiT Arctic Univ Norway Dept Comp Sci N-9037 Tromso Norway UiT Arctic Univ Norway Dept Phys & Technol N-9037 Tromso Norway

The multiple signal classification algorithm (MUSICAL) is a statistical super-resolution technique for wide-field fluorescence microscopy. Although MUSICAL has several advantages, such as its high resolution, its low computational performance has limited its exploitation. This paper aims to analyze the performance and scalability of MUSICAL for improving its low computational performance. We first optimize MUSICAL for performance analysis by using the latest high-performance computing libraries and parallel programming techniques. Thereafter, we provide insights into MUSICAL's performance bottlenecks. Based on the insights, we develop a new parallel MUSICAL in C++ using Intel Threading Building Blocks and the Intel Math Kernel Library. Our experimental results show that our new parallel MUSICAL achieves a speed-up of up to 30.36x on a commodity machine with 32 cores with an efficiency of 94.88%. The experimental results also show that our new parallel MUSICAL outperforms the previous versions of MUSICAL in Matlab, Java, and Python by 30.43x, 2.63x, and 1.69x, respectively, on commodity machines.

关键词： Music Microscopy Superresolution Matlab C plus plus languages Windows Python Computational nanoscopy parallel programming optimization super-resolution imaging image enhancement

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Inductive definitions in logic versus programs of real-time cellular automata

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THEORETICAL COMPUTER SCIENCE 2024年 987卷

作者： Grandjean, Etienne Grente, Theo Terrier, Veronique Normandie Univ UNICAEN ENSICAEN CNRSGREYC F-14000 Caen France

Descriptive complexity provides intrinsic, i.e. machine-independent , characterizations of the main complexity classes. On the other hand, logic can be useful for designing programs in a natural declarative way. This is especially important for parallel computation models such as cellular automata, since designing parallel programs is considered a difficult task. This paper establishes three logical characterizations of the three classical complexity classes modeling minimal time, called real-time , of one-dimensional cellular automata according to their canonical variations: unidirectional or bidirectional communication, input word given in a parallel or sequential way. Our three logics are natural restrictions of existential second-order Horn logic with built-in successor and predecessor functions. These logics correspond exactly to the three ways of deciding a language on a square grid circuit of side �� according to one of the three natural locations of an input word of length ��: along a side of the grid, on the diagonal that contains the output cell - placed on the vertex (n,n) of the square grid-, or on the diagonal opposite to the output cell. The key ingredient to our results is a normalization method that transforms a formula from one of our three logics into an equivalent normalized formula that closely mimics a grid circuit. Then, we extend our logics by allowing a limited use of negation on hypotheses like in Stratified Datalog. By revisiting in detail a number of representative classical problems -recognition of the set of primes by Fisher's algorithm, Dyck language recognition, Firing Squad Synchronization problem, etc. -we show that this extension makes easier programming and we prove that it does not change the real-time complexity of our logics. Finally, based on our experience in expressing these representative problems in logic, we argue that our logics are high-level programming languages: they make it possible to express in a natural, c

关键词： Computational complexity Descriptive complexity Cellular automaton Real-time computation Horn formula Existential second-order logic Inductive logic parallel programming

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A Compiler Extension for parallel Matrix programming 43

A Compiler Extension for Parallel Matrix Programming

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43rd Annual International Conference on parallel Processing (ICPP)

作者： Williams, Kevin Le, Matthew Kaminski, Ted Van Wyk, Eric Univ Minnesota Dept Comp Sci & Engn Minneapolis MN 55455 USA

ISBN: (纸本)9781479956180

This paper describes a compiler extension to our prototype extensible C translator that adds new features for parallel execution of matrix operations and shows their application to problems in spatio-temporal data mining. The extension provides new language features for constructing new matrices, mapping functions over elements of a matrix, and accumulating operations that, for example, can sum values in a matrix. It also provides the appropriate semantic analysis to check for errors before translating the constructs down to parallel C code. The extension also provides features that let the programmer indicate how the extension translates these matrix constructs down to C code. Programmers seeking higher levels of performance can specify how the underlying for-loops are structured so that code using, for example, loop-tiling techniques or vector processors, is generated. In general, compiler extensions supported by our approach allow new domain-specific syntax and semantic analyses to be easily added to the host language. Specifications of the host C language and the extensions are composed to create a custom translator that maps extended C programs down to plain (parallel) C code, checking for domain-specific errors and applying high-level domain-specific optimizations in the process.

关键词： C language data mining formal specification matrix algebra optimisation parallel programming program compilers compiler extension high-level domain-specific optimization language feature loop-tiling technique matrix operation parallel C code parallel matrix programming prototype extensible C translator semantic analysis spatio-temporal data mining syntax analysis vector processor Generators Indexing Instruction sets Oceans Semantics Syntactics extensible languages matrix programming

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Accelerated execution via eager-release of dependencies in task-based workflows

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INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS 2021年第4期35卷 325-343页

作者： Elshazly, Hatem Lordan, Francesc Ejarque, Jorge Badia, Rosa M. Barcelona Supercomp Ctr C Jordi Girona 31 Barcelona 08034 Spain Barcelona Supercomp Ctr Workflows & Distributed Comp Grp Barcelona Spain

Task-based programming models offer a flexible way to express the unstructured parallelism patterns of nowadays complex applications. This expressive capability is required to achieve maximum possible performance for applications that are executed in distributed execution platforms. In current task-based workflows, tasks are launched for execution when their data dependencies are satisfied. However, even though the data dependencies of a certain task might have been already produced, the execution of this task will be delayed until its predecessor tasks completely finish their execution. As a consequence of this approach of releasing dependencies, the amount of parallelism inherent in applications is limited and performance improvement opportunities are wasted. To mitigate this limitation, we propose an eager approach for releasing data dependencies. Following this approach, the execution of tasks will not be delayed until their predecessor tasks completely finish their execution, instead, tasks will be launched for execution as soon as their data requirements are available. Hence, more parallelism is exposed and applications can achieve higher levels of performance by overlapping the execution of tasks. Towards achieving this goal, in this paper we propose applying two changes to task-based workflow systems. First, modifying the dependency relationships of tasks to be specified not only in terms of predecessor and successor tasks but also in terms of the data that caused these dependencies. Second, triggering the release of dependencies as soon as a predecessor task generates the output data instead of having to wait until the end of the predecessor execution to release all of its dependencies. We realize this proposal using PyCOMPSs: a task-based programming model for parallelizing Python applications. Our experiments show that using an eager approach for releasing dependencies achieves more than 50% performance improvement in the total execution time as compared

关键词： Task-based workflows partial dependencies lazy dependency release eager dependency release high-performance computing parallel programming distributed execution

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Machine Learning for CUDA+MPI Design Rules 36

Machine Learning for CUDA+MPI Design Rules

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36th IEEE International parallel and Distributed Processing Symposium Workshops, IPDPSW 2022

作者： Pearson, Carl Javeed, Aurya Devine, Karen Sandia National Laboratories AlbuquerqueNM United States

ISBN: (纸本)9781665497473

We present a new strategy for automatically exploring the design space of key CUDA + MPI programs and providing design rules that discriminate slow from fast implementations. In such programs, the order of operations (e.g., G PU kernels, MPI communication) and assignment of operations to resources (e.g., G PU streams) makes the space of possible designs enormous. Systems experts have the task of redesigning and reoptimizing these programs to effectively utilize each new platform. This work provides a prototype tool to reduce that burden. In our approach, a directed acyclic graph of CUDA and MPI operations defines the design space for the program. Monte-Carlo tree search discovers regions of the design space that have large impact on the program's performance. A sequence-to-vector transformation defines features for each explored im-plementation, and each implementation is assigned a class label according to its relative performance. A decision tree is trained on the features and labels to produce design rules for each class;these rules can be used by systems experts to guide their implementations. We demonstrate our strategy using a key kernel from scientific computing - sparse-matrix vector multiplication - on a platform with multiple MPI ranks and GPU streams. © 2022 IEEE.

关键词： parallel programming

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On the Performance Portability of OpenACC, OpenMP, Kokkos and RAJA 2022

On the Performance Portability of OpenACC, OpenMP, Kokkos an...

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5th International Conference on High Performance Computing in Asia-Pacific Region, HPC Asia 2022

作者： Marowka, Ami Parallel Research Lab Petach-Tikva Israel

ISBN: (纸本)9781450384988

Performance Portability frameworks are becoming more central and essential in heterogeneous computing systems. However, the developer toolbox lacks the tools to assess the performance portability degree of these frameworks. This article presents a new definition and a metric for evaluating the performance portability of high-level parallel programming models. Using the new metric, the performance portability of OpenACC, OpenMP, Kokkos and RAJA were evaluated based on 324 case studies in various application domains, CPUs and GPUs architectures, and high-performance compilers. The results show that the four performance portability frameworks achieve impressive performance portability of over 80% with no significant differences between different architectures and compilers. © 2022 ACM.

关键词： parallel programming

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GeoMFree^3D: A package of meshfree local Radial Point Interpolation Method (RPIM) for geomechanics

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COMPUTERS & MATHEMATICS WITH APPLICATIONS 2021年第1期81卷 113-132页

作者： Xu, Nengxiong Mei, Gang Qin, Jiayu Li, Yazhe Xu, Liangliang China Univ Geosci Beijing Sch Engn & Technol Beijing 100083 Peoples R China

Mesh-based numerical methods such as the Finite Element Method (FEM) and Finite Difference Method (FDM) are widely used in various fields of science and engineering. However, the shortcomings of mesh-based methods are becoming increasingly obvious mainly due to the distorted or broken elements when analyzing the problems of large deformation or crack propagation. To overcome the above problems, meshfree methods such as the Meshless Local Petrov-Galerkin (MLPG) and Radial Point Interpolation Method (RPIM) were proposed, which can eliminate or partially eliminate the difficulties triggered by mesh-dependence. In geotechnics, the numerical modeling of deformations and failures of soil and rock masses is one of the most important approaches to understand and prevent geohazards, such as landslides and ground subsidence. In this paper, a local RPIM-based meshfree software package GeoMFree(3D) is specifically developed for analyzing the deformations and failures of soil and rock masses. To enhance the computing capability of GeoMFree(3D), (1) effective memory storage strategies are adopted to solve the memory requirement bottleneck;and (2) parallel computing strategies are utilized and heterogeneously implemented on multi-core CPU and many-core GPU to improve the computational efficiency. To demonstrate the performance of GeoMFree(3D), three simple verification examples and one application case are presented in this paper. The verification examples indicate that the computational accuracy and efficiency of the package GeoMFree(3D) is acceptable. Furthermore, the application case indicates that GeoMFree(3D) is capable of analyzing the displacements of complex rock slopes. GeoMFree(3D) is currently under intensive development, plans for future work on the development of GeoMFree(3D) are also introduced. (C) 2020 The Author(s). Published by Elsevier Ltd.

关键词： Meshfree methods Radial Point Interpolation Method (RPIM) Geomechanics Soil and rock masses Large deformation parallel programming

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