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检索条件"主题词=Parallel programming"

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A parallel Implementation for Cellular Potts Model with Software Transactional Memory 13th

A Parallel Implementation for Cellular Potts Model with Soft...

引用

13th International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB)

作者： Tomeu, A. J. Gamez, A. Salguero, A. G. Univ Cadiz Puerto Real 11519 CA Spain IES Mar Mediterraneo Aguadulce 04720 AL Spain

ISBN: (纸本)9783030238735;9783030238728

Cellular Potts Model is a mathematical model used to simulate biological systems in a wide scale range, from cells to organs. The model uses a Monte-Carlo approach to determinate for each cell, new state and actions like mitosis, movements or emission of pseudopods. Literature shows multiple implementations of CPM model, even incorporating parallel processing. These works use a data division approach that requires to take locks on data structures, or to spread information between tasks, slowing down simulations. This work proposes a fast implementation for CPM using software transactional memory to synchronize parallel tasks and to apply it to breast cancer in situ (DCIS). Execution times and speedups are calculated. Results show appreciable speedups.

关键词： Cellular automaton Cellular Potts Model (Breast cancer in situ) DCIS Gland Locks Multicore parallel programming Shared memory Software transactional memory speedup

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Minimizing Self-adaptation Overhead in parallel Stream Processing for Multi-cores 25th

Minimizing Self-adaptation Overhead in Parallel Stream Proce...

引用

25th International Conference on parallel and Distributed Computing (Euro-Par)

作者： Vogel, Adriano Griebler, Dalvan Danelutto, Marco Fernandes, Luiz Gustavo Pontificia Univ Catolica Rio Grande do Sul Sch Technol Porto Alegre RS Brazil Univ Pisa Dept Comp Sci Pisa Italy Tres de Maio Fac SETREM Lab Adv Res Cloud Comp LARCC Tres De Maio Brazil

ISBN: (纸本)9783030483401;9783030483395

Stream processing paradigm is present in several applications that apply computations over continuous data flowing in the form of streams (e.g., video feeds, image, and data analytics). Employing self-adaptivity to stream processing applications can provide higher-level programming abstractions and autonomic resource management. However, there are cases where the performance is suboptimal. In this paper, the goal is to optimize parallelism adaptations in terms of stability and accuracy, which can improve the performance of parallel stream processing applications. Therefore, we present a new optimized self-adaptive strategy that is experimentally evaluated. The proposed solution provided high-level programming abstractions, reduced the adaptation overhead, and achieved a competitive performance with the best static executions.

关键词： parallel programming Stream parallelism Self-adaptive parallelism Autonomic computing

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Random Forests in Chapel 34

Random Forests in Chapel

引用

34th IEEE International parallel and Distributed Processing Symposium (IPDPS)

作者： Albrecht, Benjamin Hewlett Packard Enterprise Houston TX 77070 USA

ISBN: (纸本)9781728174457

This talk will present the ongoing work of developing a Chapel implementation of Random Forest, a popular ensembling learning method utilized both for predictive modeling and feature selection. Language features in Chapel make it possible to easily express shared-memory and distributed-memory implementations of this algorithm. Furthermore, Chapel's built-in python interoperability functionality made it easier to implement a python front-end, making it accessible to a language popular among data scientists.

关键词： parallel programming machine learning

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Enhancing Java Streams API with PowerList Computation 34

Enhancing Java Streams API with PowerList Computation

引用

34th IEEE International parallel and Distributed Processing Symposium (IPDPS)

作者： Niculescu, Virginia Bufnea, Darius Sterca, Adrian Babes Bolyai Univ Fac Math & Comp Sci Cluj Napoca Romania

ISBN: (纸本)9781728174457

Since they were introduced, Java streams were very fast embraced by the industry, being currently used at a large scale. The parallelism enabled by them is very easy to achieve, but it is constrained either by the used parallelism model (in some cases), or by the set of operations that could be specified using streams. We investigate in this paper the possibility to enhance the computation types that could be defined using the Java streams API by introducing into this infrastructure the PowerList theory based computation. Powerlists are recursive data structures that together with their associated algebraic theory offer both abstractions in order to ease the development of parallel applications, and also a methodology to design parallel algorithms. The Java streaming infrastructure could be adapted to support them in a great measure. We present here such an adaptation, and we analyse and discuss the advantages and constraints. This analysis is exemplified by application examples.

关键词： parallel programming streams recursive structures Java performance models

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Exploring Chapel Productivity Using Some Graph Algorithms 34

Exploring Chapel Productivity Using Some Graph Algorithms

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34th IEEE International parallel and Distributed Processing Symposium (IPDPS)

作者： Barrett, Richard F. Cook, Jeanine Olivier, Stephen L. Aaziz, Omar Jenkins, Christipher D. Vaughan, Courtenay T. Sandia Natl Labs Cyber Intelligence Res POB 5800 Albuquerque NM 87185 USA Sandia Natl Labs Ctr Comp Res POB 5800 Albuquerque NM 87185 USA Sandia Natl Labs Cyber Secur & Mission Comp Ctr POB 5800 Albuquerque NM 87185 USA Sandia Natl Labs Syst Secur Res POB 5800 Albuquerque NM 87185 USA

ISBN: (纸本)9781728174457

A broad set of data science and engineering questions may be organized as graphs, providing a powerful means for describing relational data. Although experts now routinely compute graph algorithms on huge, unstructured graphs using high performance computing (HPC) or cloud resources, this practice hasn't yet broken into the mainstream. Such computations require great expertise, yet users often need rapid prototyping and development to quickly customize existing code. Toward that end, we are exploring the use of the Chapel programming language as a means of making some important graph analytics more accessible, examining the breadth of characteristics that would make for a productive programming environment, one that is expressive, performant, portable, and robust. In this talk we describe our early explorations of this space, based on miniTri [4], a miniapp from the Mantevo suite [1], and the mean hitting time algorithm [2], one of the analytics being explored within Grafiki1 [3], both of which are designed for use on distributed memory parallel processing environments. These implementations have been posed in terms of key linear algebra operations and algorithms, specifically sparse matrix-matrix multiplication, operating on integer datatypes, and the Conjugate Gradient method, based on a graph Laplacian matrix.

关键词： High performance computing parallel programming graph analytics

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Towards an Auto-Tuned and Task-Based SpMV (LASs Library) 16th

Towards an Auto-Tuned and Task-Based SpMV (LASs Library)

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16th International Workshop on OpenMP (IWOMP)

作者： Catalan, Sandra Usui, Tetsuzo Toledo, Leonel Martorell, Xavier Labarta, Jesus Valero-Lara, Pedro Univ Complutense Madrid Madrid Spain Fujitsu Ltd Next Generat Tech Comp Unit Kawasaki Kanagawa Japan Barcelona Supercomp Ctr Barcelona Spain Univ Politecn Cataluna Barcelona Spain

ISBN: (纸本)9783030581442;9783030581435

We present a novel approach to parallelize the SpMV kernel included in LASs (Linear Algebra routines on OmpSs) library, after a deep review and analysis of several well-known approaches. LASs is based on OmpSs, a task-based runtime that extends OpenMP directives, providing more flexibility to apply new strategies. Based on tasking and nesting, with the aim of improving the workload imbalance inherent to the SpMV operation, we present a strategy especially useful for highly imbalanced input matrices. In this approach, the number of created tasks is dynamically decided in order to maximize the use of the resources of the platform. Throughout this paper, SpMV behavior depending on the selected strategy (state of the art and proposed strategies) is deeply analyzed, setting in this way the base for a future auto-tunable code that is able to select the most suitable approach depending on the input matrix. The experiments of this work were carried out for a set of 12 matrices from the Suite Sparse Matrix Collection, all of them with different characteristics regarding their sparsity. The experiments of this work were performed on a node of Marenostrum 4 supercomputer (with two sockets Intel Xeon, 24 cores each) and on a node of Dibona cluster (using one ARM ThunderX2 socket with 32 cores). Our tests show that, for Intel Xeon, the best parallelization strategy reduces the execution time of the reference MKL multi-threaded version up to 67%. On ARM ThunderX2, the reduction is up to 56% with respect to the OmpSs parallel reference.

关键词： SpMV parallel programming Tasking Auto-tuning Taskloop Nesting LASs OmpSs

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GVPRoF: A Value Profiler for GPU-Based Clusters

GVPRoF: A Value Profiler for GPU-Based Clusters

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International Conference on High Performance Computing, Networking, Storage and Analysis (SC)

作者： Zhou, Keren Hao, Yueming Mellor-Crummey, John Meng, Xiaozhu Liu, Xu Rice Univ Dept Comp Sci Houston TX 77005 USA North Carolina State Univ Dept Comp Sci Raleigh NC USA

ISBN: (纸本)9781728199986

GPGPUs arc widely used in high-performance computing systems to accelerate scientific and machine learning workloads. Developing efficient GPU kernels is critically important to obtain "bare-metal" performance on GPU-based dusters. In this paper, we describe the design and implementation of GVPROF, the first value profiler that pinpoints value-related inefficiencies in applications running on NVIDIA GPU-based clusters. The novelly of GVPROF resides in its ability to detect temporal and spatial value redundancies, which provides useful information to guide code optimization. GVPROF can monitor production multi-node multi-GPU executions in clusters. Our experiments with well-known GPU benchmarks and HPC applications show that GVPROF incurs acceptable overhead and scales to large executions. Using GVPROF, we optimized several IIPC and machine learning workloads on one NVIDIA V100 GPU. In one case study of LAMMPS, optimizations based on information from GVProf led to whole-program speedups ranging from I.37x on a single CPU to 1.08x on 64 GPUs.

关键词： High performance computing Performance analysis parallel programming Supercomputers

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Empirical Modeling of Spatially Diverging Performance 7

Empirical Modeling of Spatially Diverging Performance

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IEEE/ACM International Workshop on HPC User Support Tools (HUST) / Workshop on programming and Performance Visualization Tools (ProTools)

作者： Calotoiu, Alexandru Geisenhofer, Markus Kummer, Florian Ritter, Marcus Weber, Jens Hoefler, Torsten Oberlack, Martin Wolf, Felix Swiss Fed Inst Technol Dept Comp Sci Zurich Switzerland Tech Univ Darmstadt Dept Mech Engn Darmstadt Germany

ISBN: (纸本)9780738110707

A common simplification made when modeling the performance of a parallel program is the assumption that the performance behavior of all processes or threads is largely uniform. Empirical performance-modeling tools such as Extra-P exploit this common pattern to make their modeling process more noise resilient, mitigating the effect of outliers by summarizing performance measurements of individual functions across all processes. While the underlying assumption does not equally hold for all applications, knowing the qualitative differences in how the performance of individual processes changes as execution parameters are varied can reveal important performance bottlenecks such as malicious patterns of load imbalance. A challenge for empirical modeling tools, however, arises from the fact that the behavioral class of a process may depend on the process configuration, letting process ranks migrate between classes as the number of processes grows. In this paper, we introduce a novel approach to the problem of modeling of spatially diverging performance based on a certain type of process clustering. We apply our technique to identify a previously unknown performance bottleneck in the BoSSS fluid-dynamics code. Removing it made the code regions in question running up to 20 times and the application as a whole run up to 4.5 times faster.

关键词： parallel programming performance modeling fluid dynamics

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Introduction to programming with C++ for Engineers 1

引用

丛书名： Wiley - IEEE

2020年

作者： Boguslaw Cyganek

ISBN: (数字)9781119431152

ISBN: (纸本)9781119431107

A complete textbook and reference for engineers to learn the fundamentals of computer programming with modern C++ Introduction to programming with C++ for Engineers is an original presentation teaching the fundamentals of computer programming and modern C++ to engineers and engineering students. Professor Cyganek, a highly regarded expert in his field, walks users through basics of data structures and algorithms with the help of a core subset of C++ and the Standard Library, progressing to the object-oriented domain and advanced C++ features, computer arithmetic, memory management and essentials of parallel programming, showing with real world examples how to complete tasks. He also guides users through the software development process, good programming practices, not shunning from explaining low-level features and the programming tools. Being a textbook, with the summarizing tables and diagrams the book becomes a highly useful reference for C++ programmers at all levels. Introduction to programming with C++ for Engineers teaches how to program by: Guiding users from simple techniques with modern C++ and the Standard Library, to more advanced object-oriented design methods and language features Providing meaningful examples that facilitate understanding of the programming techniques and the C++ language constructions Fostering good programming practices which create better professional programmers Minimizing text descriptions, opting instead for comprehensive figures, tables, diagrams, and other explanatory material Granting access to a complementary website that contains example code and useful links to resources that further improve the reader’s coding ability Including test and exam question for the reader’s review at the end of each chapter Engineering students, students of other sciences who rely on computer programming, and professionals in various fields will find this book invaluable when learning to program with C++.

关键词： Introduction to programming in C++ for Engineers C++ for engineers intro programming programming for beginners introduction to C++ introduction to C C++ for beginners c for beginners C++ instruction manual C++ guide C for engineers object-oriented programming design patterns parallel programming computer arithmetic

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Managing Failures in Task-Based parallel Workflows in Distributed Computing Environments 26th

Managing Failures in Task-Based Parallel Workflows in Distri...

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26th International Conference on parallel and Distributed Computing (Euro-Par)

作者： Ejarque, Jorge Bertran, Marta Cid-Fuentes, Javier Alvarez Conejero, Javier Badia, Rosa M. Barcelona Supercomp Ctr Barcelona Spain

ISBN: (纸本)9783030576752;9783030576745

Current scientific workflows are large and complex. They normally perform thousands of simulations whose results combined with searching and data analytics algorithms, in order to infer new knowledge, generate a very large amount of data. To this end, workflows comprise many tasks and some of them may fail. Most of the work done about failure management in workflow managers and runtimes focuses on recovering from failures caused by resources (retrying or resubmitting the failed computation in other resources, etc.) However, some of these failures can be caused by the application itself (corrupted data, algorithms which are not converging for certain conditions, etc.), and these fault tolerance mechanisms are not sufficient to perform a successful workflow execution. In these cases, developers have to add some code in their applications to prevent and manage the possible failures. In this paper, we propose a simple interface and a set of transparent runtime mechanisms to simplify how scientists deal with application-based failures in task-based parallel workflows. We have validated our proposal with use-cases from e-science and machine learning to show the benefits of the proposed interface and mechanisms in terms of programming productivity and performance.

关键词： Failure management Scientific workflows parallel programming Distributed computing

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