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MATHEMATICAL programming models IN EDUCATIONAL PLANNING

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REVIEW OF EDUCATIONAL RESEARCH 1971年第5期41卷 419-446页

作者： MCNAMARA, JF UNIV OREGON CTR ADVANCED STUDY EDUC ADMEUGENEOR

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Comparing Julia to Performance Portable Parallel programming models for HPC 12

Comparing Julia to Performance Portable Parallel Programming...

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12th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems held as part of the 33rd ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis

作者： Lin, Wei-Chen McIntosh-Smith, Simon Univ Bristol Dept Comp Sci Bristol Avon England

ISBN: (纸本)9781665411189

Julia is a general-purpose, managed, strongly and dynamically-typed programming language with emphasis on high performance scientific computing. Traditionally, HPC software development uses languages such as C, C++ and Fortran, which compile to unmanaged code. This offers the programmer near bare-metal performance at the expense of safety properties that a managed runtime would otherwise provide. Julia, on the other hand, combines novel programming language design approaches to achieve high levels of productivity without sacrificing performance while using a fully managed runtime. This study provides an evaluation of Julia's suitability for HPC applications from a performance point of view across a diverse range of CPU and GPU platforms. We select representative memory-bandwidth bound and compute bound mini-apps, port them to Julia, and conduct benchmarks across a wide range of current HPC CPUs and GPUs from vendors such as Intel (R), AMD (R), NVIDIA (R), Marvell (R), and Fujitsu (R). We then compare and characterise the results against existing parallel programming frameworks such as OpenMP (R), Kokkos, OpenCL (TM), and first-party frameworks such as CUDA (R), HIP (TM), and oneAPI (TM) SYCL (TM). Finally, we show that Julia's performance either matches the competition or is only a short way behind.

关键词： Julia OpenMP OpenCL Kokkos CUDA HIP Performance Portability programming models GPUs

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Assessing the performance portability of modern parallel programming models using TeaLeaf

Assessing the performance portability of modern parallel pro...

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Euro-Par Conference / 7th International Workshop on programming models and Applications for Multicores and Manycores (PMAM) held in conjunction with the 21st SIGPLAN Symposium on Principles and Practice of Parallel programming (PPoPP)

作者： Martineau, Matthew McIntosh-Smith, Simon Gaudin, Wayne Univ Bristol HPC Grp Bristol Avon England UK Atom Weap Estab AWE Aldermaston England

In this work, we evaluate several emerging parallel programming models: Kokkos, RAJA, OpenACC, and OpenMP 4.0, against the mature CUDA and OpenCL APIs. Each model has been used to port Tealeaf, a miniature proxy application, or mini app, that solves the heat conduction equation and belongs to the Mantevo Project. We find that the best performance is achieved with architecture-specific implementations but that, in many cases, the performance portable models are able to solve the same problems to within a 5% to 30% performance penalty. While the models expose varying levels of complexity to the developer, they all achieve reasonable performance with this application. As such, if this small performance penalty is permissible for a problem domain, we believe that productivity and development complexity can be considered the major differentiators when choosing a modern parallel programming model to develop applications like Tealeaf.

关键词： Kokkos OpenMP 4 0 performance portability programming models RAJA

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Exploring Memory Error Vulnerability for Parallel programming models 11th

Exploring Memory Error Vulnerability for Parallel Programmin...

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11th International Conference on Parallel Processing and Applied Mathematics (PPAM)

作者： Oz, Isil Gil, Marisa Utrera, Gladys Martorell, Xavier Marmara Univ Dept Comp Engn Goztepe Campus TR-34722 Istanbul Turkey Univ Politecn Cataluna Comp Architecture Dept Jordi Girona 3 ES-08034 Barcelona Spain

ISBN: (纸本)9783319321493;9783319321486

Transistor size reduction and more aggressive power modes in HPC platforms make chip components more error prone. In this context, HPC applications can have a diverse level of tolerance to memory errors that may change the execution in different ways. As the tolerance to memory errors depends on write frequency and access patterns, different programming models may exhibit a different behavior in the rate of failures and alleviate the performance loss caused by the overhead of fault-tolerance mechanisms. In this paper, we explore how tolerant to memory errors are two main parallel programming models, message-passing and shared memory: we perform a memory vulnerability analysis and also conduct error propagation experiments to observe the effect of memory errors through program flow. Our results show the need for soft error resiliency methods based on memory behavior of programs, and the evaluation of the tradeoffs between performance and reliability.

关键词： Memory errors Reliability SDC programming models

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Evaluating GPU programming models for the LUMI Supercomputer 1

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7th Asian Conference on Supercomputing Frontiers (SCFA)

作者： Markomanolis, George S. Alpay, Aksel Young, Jeffrey Klemm, Michael Malaya, Nicholas Esposito, Aniello Heikonen, Jussi Bastrakov, Sergei Debus, Alexander Kluge, Thomas Steiniger, Klaus Stephan, Jan Widera, Rene Bussmann, Michael CSC IT Ctr Sci Ltd Espoo Finland Heidelberg Univ Heidelberg Germany Adv Micro Devices Inc Santa Clara CA USA Hewlett Packard Enterprise Spring TX USA Georgia Inst Technol Atlanta GA 30332 USA Ctr Adv Syst Understanding Gorlitz Germany Helmholtz Zentrum Dresden Rossendorf Dresden Germany

ISBN: (数字)9783031104190

ISBN: (纸本)9783031104190;9783031104183

It is common in the HPC community that the achieved performance with just CPUs is limited for many computational cases. The EuroHPC pre-exascale and the coming exascale systems are mainly focused on accelerators, and some of the largest upcoming supercomputers such as LUMI and Frontier will be powered by AMD Instinct (TM) accelerators. However, these new systems create many challenges for developers who are not familiar with the new ecosystem or with the required programming models that can be used to program for heterogeneous architectures. In this paper, we present some of the more well-known programming models to program for current and future GPU systems. We then measure the performance of each approach using a benchmark and a mini-app, test with various compilers, and tune the codes where necessary. Finally, we compare the performance, where possible, between the NVIDIA Volta (V100), Ampere (A100) GPUs, and the AMD MI100 GPU.

关键词： GPU programming models HIP CUDA OpenMP hipSYCL Kokkos Alpaka

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Exploring Parallel programming models for Heterogeneous Computing Systems

Exploring Parallel Programming Models for Heterogeneous Comp...

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IEEE International Symposium on Workload Characterization IISWC

作者： Daga, Mayank Tschirhart, Zachary S. Freitag, Chip Adv Micro Devices Inc AMD Res Sunnyvale CA 94088 USA

ISBN: (纸本)9781509000883

Parallel systems that employ CPUs and GPUs as two heterogeneous computational units have become immensely popular due to their ability to maximize performance under restrictive thermal budgets. However, programming heterogeneous systems via traditional programming models like OpenCL or CUDA involves rewriting large portions of application-code. They also lead to code that is not performance portable across different architectures or even across different generations of the same architecture. In this paper, we evaluate the current state of two emerging parallel programming models: C++ AMP and OpenACC. These emerging programming paradigms require minimal code changes and rely on compilers to interact with the low-level hardware language, thereby producing performance portable code from an application standpoint. We analyze the performance and productivity of the emerging programming models and compare them with OpenCL using a diverse set of applications on two different architectures, a CPU coupled with a discrete GPU and an Accelerated programming Unit (APU). Our experiments demonstrate that while the emerging programming models improve programmer productivity, they do not yet expose enough flexibility to extract maximum performance as compared to traditional programming models.

关键词： APU C plus plus AMP evaluation GPU OpenACC OpenCL performance productivity programming models

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A Comparison of programming models for Multiprocessors with Explicitly Managed Memory Hierarchies

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ACM SIGPLAN NOTICES 2009年第4期44卷 131-140页

作者： Schneider, Scott Yeom, Jae-Seung Rose, Benjamin Linford, John C. Sandu, Adrian Nikolopoulos, Dimitrios S. Virginia Tech Dept Comp Sci Blacksburg VA 24060 USA

On multiprocessors with explicitly managed memory hierarchies (EMM), software has the responsibility of moving data in and out of fast local memories. This task can be complex and error-prone even for expert programmers. Before we can allow compilers to handle the complexity for us, we must identify the abstractions that are general enough to allow us to write applications with reasonable effort, yet specific enough to exploit the vast on-chip memory bandwidth of EMM multi-processors. To this end, we compare two programming models against hand-tuned codes on the STI Cell, paying attention to programmability and performance. The first programming model, Sequoia, abstracts the memory hierarchy as private address spaces, each corresponding to a parallel task. The second, Cellgen, is a new framework which provides OpenMP-like semantics and the abstraction of a shared address spaces divided into private and shared data. We compare three applications programmed using these models against their hand-optimized counterparts in terms of abstractions, programming complexity, and performance.

关键词： Design Languages Cell BE Explicitly Managed Memory Hierarchies programming models

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Use Concurrent programming models to Motivate Teaching of programming Languages

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ACM SIGPLAN NOTICES 2008年第11期43卷 93-98页

作者： Leavens, Gary T. Univ Cent Florida Coll Elect Engn & Comp Sci Orlando FL 32816 USA

Undergraduate computer science students typically have only a limited understanding of their favorite languages and no inkling of other programming paradigms. Yet modern programmers typically work with several languages, and the availability of cheap concurrency is exposing fundamental problems in standard concurrent programming techniques ( mutable objects and threads). This situation presents a great opportunity: by exploring nonstandard techniques for gaining intellectual control over concurrent programs, one can motivate and teach important semantic concepts ( such as scoping) and important programming concepts ( such as functional abstraction). Such a curriculum stimulates student interest in exploring new programming paradigms.

关键词： Languages programming language curriculum concepts concurrency computational models programming models paradigms

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AMA: Asynchronous Management of Accelerators for Task-based programming models

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Procedia Computer Science 2015年 51卷 130-139页

作者： Judit Planas Rosa M. Badia Eduard Ayguade Jesus Labarta Barcelona Supercomputing Center (BSC-CNS) Barcelona Spain Universitat Politecnica de Catalunya (UPC) Barcelona Spain Artificial Intelligence Research Institute Spanish National Research Council (IIIA CSIC) Spain

Computational science has benefited in the last years from emerging accelerators that increase the performance of scientific simulations, but using these devices hinders the programming task. This paper presents AMA: a set of optimization techniques to efficiently manage multi-accelerator systems. AMA maximizes the overlap of computation and communication in a blocking-free way. Then, we can use such spare time to do other work while waiting for device operations. Implemented on top of a task-based framework, the experimental evaluation of AMA on a quad-GPU node shows that we reach the performance of a hand-tuned native CUDA code, with the advantage of fully hiding the device management. In addition, we obtain up to more than 2x performance speed-up with respect to the original framework implementation.

关键词： Accelerator management Asynchronous devices programming models Multi-GPU systems

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INTEGER programming models FOR SALES TERRITORY ALIGNMENT TO MAXIMIZE PROFIT

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JOURNAL OF MARKETING RESEARCH 1976年第4期13卷 426-430页

作者： ZOLTNERS, AA NORTHWESTERN UNIV EVANSTONIL 60201

A recent article described a mathematical programming model and heuristic solution procedure to realign sales territories. This report presents two linear integer programming models for sales territory alignment to ma... 详细信息

关键词： Sales territory Integer programming Integers programming models Heuristics Optimal solutions Mathematical notation Algorithms Marketing

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