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13th International Symposium on Advanced Parallel Processing Technologies (APPT)

作者： Du, Weijian Wu, Linyang Chen, Xiaobing Zhuang, Yimin Zhi, Tian Chinese Acad Sci Inst Comp Technol SKL Comp Architecture Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Cambricon Tech Ltd Shanghai Peoples R China

ISBN: (纸本)9783030296117;9783030296100

In the last five years, the research of neural network accelerators has made remarkable achievements and provided powerful hardware support for many deep learning algorithms. In order to improve the performance of the neural network accelerator, algorithm optimization and data layout in the neural network development kit (NDK) are indispensable. The rich data types in neural network algorithms determine the diversity of data layout information. How to add complex data layout information to the NDK, to guide the work of all aspects of the software, to avoid user perception and to provide a user-friendly API, has become a series of issues worth studying. This paper implements a neural network development kit based on labeled data layout to solve the above problems, and abstracts a neural network programming model. The programming model establishes a neural network computing graph at "creating time", "compiling time" sets the data label and "runtime" uses the label to control the data transfer. Compared with the existing NDK, the software has an average performance improvement of 4.76x. In addition, this paper also defines dynamic tags and static tags of neural network data, and proposes a neural network data classification method.

关键词： Neural network programming model Labeled Data layout SDK

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SLOPE: Structural Locality-Aware programming model for Composing Array Data Analysis 34th

SLOPE: Structural Locality-Aware Programming Model for Compo...

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34th International Conference on High Performance Computing (ISC High Performance)

作者： Dong, Bin Wu, Kesheng Byna, Suren Tang, Houjun Lawrence Berkeley Natl Lab 1 Cyclotron Rd Berkeley CA 94720 USA

ISBN: (纸本)9783030206567;9783030206550

MapReduce brought on the Big Data revolution. However, its impact on scientific data analyses has been limited because of fundamental limitations in its data and programming models. Scientific data is typically stored as multidimensional arrays, while MapReduce is based on key-value (KV) pairs. Applying MapReduce to analyze array-based scientific data requires a conversion of arrays to KV pairs. This conversion incurs a large storage overhead and loses structural information embedded in the array. For example, analysis operations, such as convolution, are defined on the neighbors of an array element. Accessing these neighbors is straightforward using array indexes, but requires complex and expensive operations like self-join in the KV data model. In this work, we introduce a novel `structural locality'-aware programming model (SLOPE) to compose data analysis directly on multidimensional arrays. We also develop a parallel execution engine for SLOPE to transparently partition the data, to cache intermediate results, to support in-place modification, and to recover from failures. Our evaluations with real applications show that SLOPE is over ninety thousand times faster than Apache Spark and is 38% faster than TensorFlow.

关键词： Multidimensional array programming model Structural locality Composable data analysis User-defined function ArrayUDF Apache Spark TensorFlow MapReduce Array cache

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Flexible Ray Traversal with an Extended programming model 19

Flexible Ray Traversal with an Extended Programming Model

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12th ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia

作者： Lee, Won-Jong Liktor, Gabor Vaidyanathan, Karthik Intel Corp Mountain View CA 94040 USA

ISBN: (纸本)9781450369459

The availability of hardware-accelerated ray tracing in GPUs and standardized APIs has led to a rapid adoption of ray tracing in games. While these APIs allow programmable surface shading and intersections, most of the ray traversal is assumed to be fixed-function. As a result, the implementation of per-instance Level-of-Detail (LOD) techniques is very limited. In this paper, we propose an extended programming model for ray tracing which includes an additional programmable stage called the traversal shader that enables procedural selection of acceleration structures for instances. Using this programming model, we demonstrate multiple applications such as procedural multi-level instancing and stochastic LOD selection that can significantly reduce the bandwidth and memory footprint of ray tracing with no perceptible loss in image quality.

关键词： ray tracing programming model level-of-detail instancing

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A programming model for Internetworked Things

A Programming Model for Internetworked Things

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作者： Hao Jiang University of Western Ontario

学位级别：硕士

The Internet of Things (IoT) emerges as a system paradigm that encompasses a wide spectrum of technologies and protocols related to Internetworking, services computing, and device connectivity. The main objective is to achieve an environment whereby physical devices and everyday objects can communicate and interact with each other over the Internet. The Internet of Things is heralded as the next generation Internet, and introduces significant opportunities for novel applications in many different domains. What is missing right now is a programming model whereby developers as well as end-users can specify any addressable resource at a higher level of abstraction, and consequently utilize these abstractions to define compositions, or scripts, among resources that allow for the customizable exchange of data among the resources, the evaluation of conditions based on exchanged data, and the enactment of actions provided that specific events occur and specific conditions are met. In this thesis, we investigate the problem of designing a programming model for composing resource or "things", with applications in the IoT domain, and implement a proof of concept prototype in order to evaluate the feasibility of such a programming model. More specifically, this thesis attacks the problem of devising an IoT programming model from three directions. The first direction is the design of a Meta-Object Facility meta-model, that allows for URI addressable entities to be specified at a higher level of abstraction. Such a meta-model can be considered as domain specific language that allows for the denotation of \emph{types} of entities (resources) in different application domains. The second direction is the design of an actionable composition model for IoT devices and other URI addressable resources. In this respect, this thesis investigates the use of the Event-Condition-Action paradigm as a basis of a runtime environment whereby action models can be enacted once events occur and con

关键词： Internet of Things Internet of Everything Internetworked things programming model middleware Event-Condition-Action goal modeling

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Action-Oriented programming model: Collective Executions and Interactions in the Fog

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JOURNAL OF SYSTEMS AND SOFTWARE 2019年 157卷 110391-000页

作者： Makitalo, Niko Aaltonen, Timo Raatikainen, Mikko Ometov, Aleksandr Andreev, Sergey Koucheryavy, Yevgeni Mikkonen, Tommi Univ Helsinki Dept Comp Sci FI-00014 Helsinki Finland Tampere Univ Comp Lab FI-33014 Tampere Finland Natl Res Univ Higher Sch Econ 20 Myasnitskaya St Moscow 101000 Russia Tampere Univ Unit Elect Engn FI-33014 Tampere Finland

Today's dominant design for the Internet of Things (loT) is a Cloud-based system, where devices transfer their data to a back-end and in return receive instructions on how to act. This view is challenged when delays caused by communication with the back-end become an obstacle for loT applications with, for example, stringent timing constraints. In contrast, Fog Computing approaches, where devices communicate and orchestrate their operations collectively and closer to the origin of data, lack adequate tools for programming secure interactions between humans and their proximate devices at the network edge. This paper fills the gap by applying Action-Oriented programming (AcOP) model for this task. While originally the AcOP model was proposed for Cloud-based infrastructures, presently it is re-designed around the notion of coalescence and disintegration, which enable the devices to collectively and autonomously execute their operations in the Fog by serving humans in a peer-to-peer fashion. The Cloud's role has been minimized-it is being leveraged as a development and deployment platform.(C) 2019 The Authors. Published by Elsevier Inc.

关键词： Fog Computing Edge computing Socio-technical systems programming model Proximity-based computing

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CharmPy: A Python Parallel programming model

CharmPy: A Python Parallel Programming Model

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IEEE International Conference on Cluster Computing (CLUSTER)

作者： Galvez, Juan J. Senthil, Karthik Kale, Laxmikant V. Univ Illinois Dept Comp Sci Champaign IL 61820 USA

ISBN: (纸本)9781538683194

Parallel programming can be extremely challenging. programming models have been proposed to simplify this task, but wide acceptance of these remains elusive for many reasons, including the demand for greater accessibility and productivity. In this paper, we introduce a parallel programming model and framework called CharmPy, based on the Python language. CharmPy builds on Charm++, and runs on top of its C++ runtime. It presents several unique features in the form of a simplified model and API, increased flexibility, and the ability to write everything in Python. CharmPy is a high-level model based on the paradigm of distributed migratable objects. It retains the benefits of the Charm++ runtime, including dynamic load balancing, asynchronous execution model with automatic overlap of communication and computation, high performance, and scalability from laptops to supercomputers. By being Python-based, CharmPy also benefits from modern language features, access to popular scientific computing and data science software, and interoperability with existing technologies like C, Fortran and OpenMP. To illustrate the simplicity of the model, we will show how to implement a distributed parallel map function based on the Master-Worker pattern using CharmPy, with support for asynchronous concurrent jobs. We also present performance results running stencil code and molecular dynamics mini-apps fully written in Python, on Blue Waters and Cori supercomputers. For stencil3d, we show performance similar to an equivalent MPI-based program, and significantly improved performance for imbalanced computations. Using Numba to JIT-compile the critical parts of the code, we show performance for both mini-apps similar to the equivalent C++ code.

关键词： programming model parallel programming distributed computing multiprocessing Python HPC

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Research on programming model for "Master-slave Distributed Tasks" of Insect Intelligent Building

Research on Programming Model for "Master-slave Distributed ...

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Chinese Automation Congress (CAC)

作者： Xue, Guangtong Yang, Qiliang Xing, Jianchun Zhao, Shuo Army Engn Univ PLA Coll Def Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781728113128

Insect Intelligent Building is a flat and distributed new Building Intelligent System, whose tasks need be solved in parallel. How to develop parallel programs quickly and efficiently for it has become an important research content. However, the general parallel programming method lacks the domain characteristics of Insect Intelligent Building, and pay too much attention to the complex interaction between nodes. This leads to more difficulty in programming This paper focuses on the "master-slave distributed tasks" that is a kind of typical task in Insect Intelligent Building, and proposes a programming model. This programming model defines some new programming elements such as "Domain", "Master CPN", and "Slave CPN'', and hides underlying details of data propagation and aggregation between nodes. It effectively reduces the programming difficulty of "master-slave distributed tasks". In the case study, the programming model is applied to a tap water control system and the results show that it has high robustness and portability and be easy to use.

关键词： Insect Intelligent Building programming model master-slave distributed tasks MSpro

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MaMR: High-performance MapReduce programming model for material cloud applications

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COMPUTER PHYSICS COMMUNICATIONS 2017年 211卷 79-87页

作者： Jing, Weipeng Tong, Danyu Wang, Yangang Wang, Jingyuan Liu, Yaqiu Zhao, Peng Northeast Forestry Univ Coll Informat & Comp Engn Harbin Peoples R China Chinese Acad Sci Comp Network Informat Ctr Beijing Peoples R China Beihang Univ Sch Comp Sci & Engn Beijing Peoples R China

With the increasing data size in materials science, existing programming models no longer satisfy the application requirements. MapReduce is a programming model that enables the easy development of scalable parallel applications to process big data on cloud computing systems. However, this model does not directly support the processing of multiple related data, and the processing performance does not reflect the advantages of cloud computing. To enhance the capability of workflow applications in material data processing, we defined a programming model for material cloud applications that supports multiple different Map and Reduce functions running concurrently based on hybrid share-memory BSP called MaMR. An optimized data sharing strategy to supply the shared data to the different Map and Reduce stages was also designed. We added a new merge phase to MapReduce that can efficiently merge data from the map and reduce modules. Experiments showed that the model and framework present effective performance improvements compared to previous work. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Materials programming model MapReduce BSP Merge phase

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Research on programming model for "Master-slave Distributed Tasks" of Insect Intelligent Building

Research on Programming Model for "Master-slave Distributed ...

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Chinese Automation Congress

作者： Guangtong Xue Qiliang Yang Jianchun Xing Shuo Zhao College of Defense Engineering Army Engineering University of PLA Nanjing China

Insect Intelligent Building is a flat and distributed new Building Intelligent System, whose tasks need be solved in parallel. How to develop parallel programs quickly and efficiently for it has become an important research content. However, the general parallel programming method lacks the domain characteristics of Insect Intelligent Building, and pay too much attention to the complex interaction between nodes. This leads to more difficulty in programming. This paper focuses on the "master-slave distributed tasks" that is a kind of typical task in Insect Intelligent Building, and proposes a programming model. This programming model defines some new programming elements such as "Domain", "Master CPN", and "Slave CPN", and hides underlying details of data propagation and aggregation between nodes. It effectively reduces the programming difficulty of "master-slave distributed tasks". In the case study, the programming model is applied to a tap water control system and the results show that it has high robustness and portability and be easy to use.

关键词： Insect intelligent building programming model Master-slave distributed tasks MSpro

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A TOSCA-based programming model for Interacting Components of Automatically Deployed Cloud and IoT Applications 19

A TOSCA-based Programming Model for Interacting Components o...

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19th International Conference on Enterprise Information Systems (ICEIS)

作者： Zimmermann, Michael Breitenbuecher, Uwe Leymann, Frank Univ Stuttgart Inst Architecture Applicat Syst Stuttgart Germany

ISBN: (纸本)9789897582486

Cloud applications typically consist of multiple components interacting with each other. Service-orientation, standards such as WSDL, and the workflow technology provide common means to enable the interaction between these components. Nevertheless, during the automated application deployment, endpoints of interacting components, e.g., URLs of deployed services, still need to be exchanged: the components must be wired. However, this exchange mainly depends on the used (i) middleware technologies, (ii) programming languages, and (iii) deployment technologies, which limits the application's portability and increases the complexity of implementing components. In this paper. we present a programming model for easing the implementation of interacting components of automatically deployed applications. The presented programming model is based on the TOSCA standard and enables invoking components by their identifiers and interface descriptions contained in the application's TOSCA model. The approach can be applied to Cloud and IoT applications, i.e., also software hosted on physical devices may use the approach to call other application components. To validate the practical feasibility of the approach. we present a system architecture and prototype based on OpenTOSCA.

关键词： programming model Orchestration Interaction Communication Automated Deployment TOSCA

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