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作者： Saha, Bratin Zhou, Xiaocheng Chen, Hu Gao, Ying Yan, Shoumeng Rajagopalan, Mohan Fang, Jesse Zhang, Peinan Ronen, Ronny Mendelson, Avi Intel Corporation

The client computing platform is moving towards a heterogeneous architecture consisting of a combination of cores focused on scalar performance, and a set of throughput-oriented cores. The throughput oriented cores (e.g. a GPU) may be connected over both coherent and non-coherent interconnects, and have different ISAs. This paper describes a programming model for such heterogeneous platforms. We discuss the language constructs, runtime implementation, and the memory model for such a programming environment. We implemented this programming environment in a x86 heterogeneous platform simulator. We ported a number of workloads to our programming environment, and present the performance of our programming environment on these workloads. Copyright © 2009 ACM.

关键词： Heterogeneous platforms programming model

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τ C: C with Process Network Extensions for Embedded Manycores

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Procedia Computer Science 2014年 29卷 1100-1112页

作者： Thierry Goubier Damien Couroussé Selma Azaiez CEA LIST DACLE/Lastre 91191 Gif-sur-Yvette CEDEX France CEA LIST DACLE/LIALP Grenoble France

Current and future embedded manycore systems bring complex and heterogeneous architectures with a large number of processing cores, making both parallel programming at this scale and understanding the architecture itself a daunting task. Process Networks and other dataflow based models of Computation (MoC) are a good base to present a universal model of the underlying manycore architectures to the programmer. If a language exposes a simple to grasp MoC in a consistent way across architectures, the programmer can concentrate the efforts on optimizing the expression of parallelism in the application instead of porting code to a given system. In this paper, we present a process network extension to C called τ C and its mapping to both a POSIX target and the P2012/STHORM platform, and show how the language offers an architecture independent solution of this problem.

关键词： manycore programming model process networks compiler toolchain

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Task scheduling of cloud computing based on Improved CHC algorithm

Task scheduling of cloud computing based on Improved CHC alg...

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International Conference on Audio, Language and Image Processing

作者： Liping Zhang Weiqin Tong Shengpeng Lu School of Computer Engineering and Science Shanghai University

ISBN: (纸本)9781479939046

In recent years, research on task scheduling in cloud computing has become a hot topic. Task scheduling is a NP hard problem. As there is a great number of users in cloud computing, the amount of task and data processing is also very huge. With regard to cloud computing programming model, we proposed an Improved CHC algorithm, which inherits the advantages of standard genetic algorithm (SGA) and CHC algorithm. The Improved CHC algorithm takes comprehensive consideration of the allocation of resources to tasks and the completion time of tasks and it also enhances the convergence speed of the algorithm. The experimental results show that Improved CHC algorithm has good efficiency and convergence, the average and completion time of the task scheduling is relatively shorter.

关键词： Cloud computing Task scheduling CHC algorithm programming model

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An Extended PRAM-NUMA model of Computation for TCF programming

An Extended PRAM-NUMA Model of Computation for TCF Programmi...

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26th IEEE International Parallel and Distributed Processing Symposium (IPDPS) / Workshop on High Performance Data Intensive Computing

作者： Forsell, Martti Leppanen, Ville VTT Tech Res Ctr Finland Platform Architectures Team Box 1100 FI-90571 Oulu Finland Turku Univ Dept Informat Technol FI-20014 Turku Finland

ISBN: (纸本)9780769546766

The Parallel Random Access Machine - Non Uniform Memory Access (PRAM-NUMA) model of computation can be used to implement efficient emulated shared memory (ESM) computers for general purpose parallel applications and yet support sequential and NUMA legacy code and avoid loss of performance in applications with low parallelism. While programming of these computers is provably easy, there is still room for improvement since they make implementing time-shared multitasking expensive, sometimes replicate much of the execution unnecessarily, and force a programmer to use looping and conditional control primitives in the case the application parallelism does not match the hardware parallelism. Thick Control Flow (TCF) is a parallel programming model that does not provide a fixed number of threads like PRAM-NUMA but a number of control flows that have certain thickness that can vary according to needs of the application catching the best parts of the dynamicism and generality of the original unbounded PRAM model and simplicity of the Single Instruction Stream Multiple Data Streams (SIMD) model. In this paper we study implementing the TCF model on a top of the PRAM-NUMA model and propose an extended PRAM-NUMA model that makes this straight-forward. Architectural implementation and programming of the extended model are discussed with short examples.

关键词： parallel computing models of computation programming model PRAM NUMA Thick control flow

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OpenMPC: extended OpenMP for efficient programming and tuning on GPUs

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INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING 2013年第1期8卷 4-20页

作者： Lee, Seyong Eigenmann, Rudolf Oak Ridge Natl Lab Comp Sci & Math Div Oak Ridge TN 37831 USA Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

General-purpose graphics processing units (GPGPUs) provide inexpensive, high performance platforms for compute-intensive applications. However, their programming complexity poses a significant challenge to developers. Even though the compute unified device architecture (CUDA) programming model offers better abstraction, developing efficient GPGPU code is still complex and error-prone. This paper proposes a directive-based, high-level programming model, called OpenMPC, which addresses both programmability and tunability issues on GPGPUs. We have developed a fully automatic compilation and user-assisted tuning system supporting OpenMPC. In addition to a range of compiler transformations and optimisations, the system includes tuning capabilities for generating, pruning, and navigating the search space of compilation variants. Evaluation using 14 applications shows that our system achieves 75% of the performance of the hand-coded CUDA programmes (92% if excluding one exceptional case).

关键词： OpenMP graphics processing unit GPU compute unified device architecture CUDA OpenMPC programming model directives automatic translation compiler transformation performance tuning code generation optimisations

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The TERAFLUX Project: Exploiting the DataFlow Paradigm in Next Generation Teradevices

The TERAFLUX Project: Exploiting the DataFlow Paradigm in Ne...

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16th Euromicro Conference on Digital System Design (DSD)

作者： Solinas, Marco Badia, Rosa M. Bodin, Francois Cohen, Albert Evripidou, Paraskevas Faraboschi, Paolo Fechner, Bernhard Gao, Guang R. Garbade, Arne Girbal, Sylvain Goodman, Daniel Khan, Behran Koliai, Souad Li, Feng Lujan, Mikel Morin, Laurent Mendelson, Avi Navarro, Nacho Pop, Antoniu Trancoso, Pedro Ungerer, Theo Valero, Mateo Weis, Sebastian Watson, Ian Zuckermann, Stephane Giorgi, Roberto Univ Siena Dip Ingn Informaz & Sci Matemat I-53100 Siena Italy Barcelona Supercomp Ctr Barcelona Spain CAPS Enterprise Paris France INRIA Paris France Univ Cyprus CY-1678 Nicosia Cyprus Intelligent Infrastructure Lab Hewlett Packard Barcelona Spain Univ Augsburg Augsburg Germany Univ Delaware Delaware OH USA THALES Paris France Univ Manchester Manchester Lancs England Techn Jerusalem Israel

ISBN: (纸本)9780769550749

Thanks to the improvements in semiconductor technologies, extreme-scale systems such as teradevices (i.e., composed by 1000 billion of transistors) will enable systems with 1000+ general purpose cores per chip, probably by 2020. Three major challenges have been identified: programmability, manageable architecture design, and reliability. TERAFLUX is a Future and Emerging Technology (FET) large-scale project funded by the European Union, which addresses such challenges at once by leveraging the dataflow principles. This paper describes the project and provides an overview of the research carried out by the TERAFLUX consortium.

关键词： TERAFLUX dataflow programming model compilation reliability architecture simulation many-cores exascale computing multi-cores

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Integrated Optimization for Supply Chain with Facility Disruption

Integrated Optimization for Supply Chain with Facility Disru...

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10th IEEE International Conference on Mechatronics and Automation (ICMA)

作者： Wang, Yong Ming Yin, Hong Li Kunming Univ Sci & Technol Fac Management & Econ Kunming 650093 Peoples R China Yunnan Normal Univ Sch Comp Sci & Informat Kunming 650093 Peoples R China

ISBN: (纸本)9781467355605

Supply chain optimization models typically assume that facilities never fail. However, in the real world cases facilities are always subject to disruptions of various sorts due to natural disasters, strikes, machine breakdowns, power outages, and other factors. This paper investigates an integrated supply chain optimization problem that optimizes facility locations, customer allocations, and inventory management decisions when facilities are subject to disruption risks. When a facility fails, its customers may be reassigned to other operational facilities in order to avoid the high penalty costs associated with losing service. The problem is formulated as a mixed integer nonlinear programming to minimize the sum of the expected total costs. The model simultaneously determines the location of distribution centres and the allocation of disruption affected customer to distribution centres. In order to solve the proposed model, an effective solution approach based on genetic algorithm is presented. Finally, computational results for several instances of the problem are given to validate the effectiveness of the proposed model and algorithm.

关键词： Supply chain Facility disruption programming model Genetic algorithm

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Vasculature segmentation using parallel multi-hypothesis template tracking on heterogeneous platforms

Vasculature segmentation using parallel multi-hypothesis tem...

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Conference on Image Processing - Algorithms and Systems XI

作者： Zhang, Dong Ping Howes, Lee Adv Micro Devices Inc Res Grp Sunnyvale CA 94088 USA

ISBN: (纸本)9780819494283

We present a parallel multi-hypothesis template tracking algorithm on heterogeneous platforms using a layered dispatch programming model. The contributions of this work are: an architecture-specific optimised solution for vasculature structure enhancement, an approach to segment the vascular lumen network from volumetric CTA images and a layered dispatch programming model to free the developers from hand-crafting mappings to particularly constrained execution domains on high throughput architecture. This abstraction is demonstrated through a vasculature segmentation application and can also be applied in other real-world applications. Current GPGPU programming models define a grouping concept which may lead to poorly scoped local/shared memory regions and an inconvenient approach to projecting complicated iterations spaces. To improve on this situation, we propose a simpler and more flexible programming model that leads to easier computation projections and hence a more convenient mapping of the same algorithm to a wide range of architectures. We first present an optimised image enhancement solution step-by-step, then solve a separable nonlinear least squares problem using a parallel Levenberg-Marquardt algorithm for template matching, and perform the energy efficiency analysis and performance comparison on a variety of platforms, including multi-core CPUs, discrete GPUs and APUs. We propose and discuss the efficiency of a layered-dispatch programming abstraction for mapping algorithms onto heterogeneous architectures.

关键词： Image Enhancement Cardiac Imaging GPU computing programming model

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Toward Large-scale Situation Awareness Applications on Camera Networks

Toward Large-scale Situation Awareness Applications on Camer...

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IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops)

作者： Hong, Kirak Georgia Inst Technol Coll Comp Atlanta GA 30332 USA

ISBN: (纸本)9781467350778;9781467350754

Ubiquitous deployment of cameras and recent advances in video analytics enable a new class of applications, situation awareness using camera networks. The application class includes surveillance, traffic monitoring, and assisted living that autonomously generate actionable knowledge from a large number of camera streams. Despite technological advances, developing a large-scale situation awareness application still remains a challenge due to the programming complexity, highly dynamic workloads, and latency-sensitive quality of service. To solve the problem, my research topic concerns developing a programming model and a runtime system to support large-scale situation awareness applications on camera networks. The programming model requires a minimal set of domain-specific handlers from the domain experts, allowing them to focus on the algorithmic aspect of situation awareness applications rather than the details of distributed programming. The runtime system provides automatic resource management using smart cameras and the cloud for handling dynamic workloads and ensuring latency-sensitive quality of services.

关键词： programming model runtime system situation awareness camera network cloud computing

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A New Method for Supply Chain Optimization with Facility Fail Risks

A New Method for Supply Chain Optimization with Facility Fai...

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9th International Conference on Computational Intelligence and Security (CIS)

作者： Yin, Hong Li Yunnan Normal Univ Sch Comp Sci & Informat Technol Kunming Peoples R China

ISBN: (纸本)9781479925483

Supply chain optimization models typically assume that facilities never fail. However, in the real world cases facilities are always subject to disruptions of various sorts due to natural disasters, strikes, machine breakdowns, power outages, and other factors. This paper investigates an integrated supply chain optimization problem that optimizes facility locations, customer allocations, and inventory management decisions when facilities are subject to disruption risks. When a facility fails, its customers may be reassigned to other operational facilities in order to avoid the high penalty costs associated with losing service. The problem is formulated as a mixed integer nonlinear programming to minimize the sum of the expected total costs. The model simultaneously determines the location of distribution centers and the allocation of disruption affected customer to distribution centers. In order to solve the proposed model, an effective solution approach based on genetic algorithm is presented. Finally, computational results for several instances of the problem are given to validate the effectiveness of the proposed model and algorithm.

关键词： Supply chain Facility disruption programming model Genetic algorithm

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