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14th ACM International Conference on Computing Frontiers

作者： Stoutchinin, Arthur Benini, Luca ST Microelect Grenoble France Univ Bologna Dipartimento Ingn Energia Elettr & Inform Bologna Italy

ISBN: (纸本)9781450344876

In this paper, we present StreamDrive, a dynamic dataflow framework for programming clustered embedded multicore architectures. StreamDrive simplifies development of dynamic dataflow applications starting from sequential reference C code and allows seamless handling of heterogeneous and application-specific processing elements at the application level. We address issues of efficient implementation of the dynamic dataflow runtime system in the context of constrained embedded environments, which have not been sufficiently addressed by previous research. We conducted a detailed performance evaluation of the StreamDrive implementation on our Application Specific MultiProcessor (ASMP) cluster using the Oriented FAST and Rotated BRIEF (ORB) algorithm typical of image processing domain. Our implementation has less than 10% parallelization overhead, near linear speed-up when the number of processors increases from 1 to 8, and achieves the performance of 15 VGA frames per second with a small cluster configuration of 4 processing elements and 64KB of shared memory, and of 30 VGA frames per second with 8 processors and 128KB of shared memory.

关键词： image processing embedded multicore dataflow programming model

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Impact of Middleware Design on the Communication Performance 12th

Impact of Middleware Design on the Communication Performance

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12th International Conference on Green, Pervasive, and Cloud Computing (GPC)

作者： Garcia-Valls, Marisol Garrido, Daniel Diaz, Manuel Univ Carlos III Madrid Leganes Spain Univ Malaga Malaga Spain

ISBN: (纸本)9783319571867;9783319571850

The precise architectural approach of a communication middleware technology is of outmost importance in areas where a certain degree of control over the underlying platform is needed, e.g., for fine-grain management of temporal behavior or concurrency management. The design of the middleware libraries and, especially, the resulting execution environment that these provide affect the control level of the application code over the platform resources. In this paper, we describe and analyze the two main design approaches of communication middleware implementations, that offer two different execution environments to applications: direct execution and virtual machine intermediation. We exemplify this idea with a selected set of technologies that does not intend to be exhaustive, but simply representative of both possible middleware architectural design approaches. The goal is to show the impact of these architectures on the resulting communication performance, that we show as overhead, i.e., the percentage of time taken by both architectures with respect to a fixed remote operation with a fixed processing time.

关键词： Middleware Run time Design Communication Performance programming model Real-time

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Publish-Subscribe programming for a NoC-based Multiprocessor System-on-Chip 50

Publish-Subscribe Programming for a NoC-based Multiprocessor...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Hamerski, Jean Carlo Abich, Geancarlo Reis, Ricardo Ost, Luciano Amory, Alexandre Pontificia Univ Catolica Rio Grande do Sul FACIN Av Ipiranga 6681 BR-90619900 Porto Alegre RS Brazil Univ Fed Rio Grande do Sul Inst Informat PPGC PGMICRO Porto Alegre RS Brazil Univ Leicester Dept Engn Leicester Leics England

ISBN: (纸本)9781467368537

Shared memory and message passing are traditional parallel programming models used on multiprocessor system-on-chip environments. Underlying models are traditionally meant for static scenarios where all communicating entities and their intercommunication patterns are known a priori by the software engineer. The systems design following such programming models became complex due to dynamic behavior of applications at runtime. The goal of this work is to incorporate a publish-subscribe programming model to an MPSoC framework to decouple, in the time and space, the application development. The modified MPSoC framework is composed of a FreeRTOS kernel running on homogeneous processing elements distributed into a network-on-chip. The results present reduction around of 2% to 30% in DTW application execution time, and low overhead in memory footprint when comparing the original MPI primitives with the publish-subscribe programming model.

关键词： MPSOC programming model

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The Best of Both Worlds: Big Data programming with Both Productivity and Performance 17

The Best of Both Worlds: Big Data Programming with Both Prod...

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ACM International Conference on Management of Data

作者： Yang, Fan Huang, Yuzhen Zhao, Yunjian Li, Jinfeng Jiang, Guanxian Cheng, James Chinese Univ Hong Kong Dept Comp Sci & Engn Hong Kong Peoples R China

ISBN: (纸本)9781450341974

Coarse-grained operators such as map and reduce have been widely used for large-scale data processing. While they are easy to master, over-simplified APIs sometimes hinder programmers from fine-grained control on how computation is performed and hence designing more efficient algorithms. On the other hand, resorting to domain-specific languages (DSLs) is also not a practical solution, since programmers may need to learn how to use many systems that can be very different from each other, and the use of low-level tools may even result in bug-prone programming. In [7], we proposed Husky which provides a highly expressive API to solve the above dilemma It allows developers to program in a variety of patterns, such as MapReduce, GAS, vertex-centric programs, and even asynchronous machine learning. While the Husky C++ engine provides great performance, in this demo proposal we introduce PyHusky and ScHusky, which allow users (e.g., data scientists) without system knowledge and low-level programming skills to leverage the performance of Husky and build high-level applications with ease using Python and Scala.

关键词： Distributed system Data-parallel processing programming model

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Data Structure Engineering For Byte-Addressable Non-Volatile Memory 17

Data Structure Engineering For Byte-Addressable Non-Volatile...

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ACM International Conference on Management of Data

作者： Oukid, Ismail Lehner, Wolfgang SAP SE Dresden Germany Tech Univ Dresden Dresden Germany

ISBN: (纸本)9781450341974

Storage Class Memory (SCM) is emerging as a viable alternative to traditional DRAM, alleviating its scalability limits, both in terms of capacity and energy consumption, while being non-volatile. Hence, SCM has the potential to become a universal memory, blurring well-known storage hierarchies. However, along with opportunities, SCM brings many challenges. In this tutorial we will dissect SCM challenges and provide an in-depth view of existing programming models that circumvent them, as well as novel data structures that stem from these models. We will also elaborate on fail-safety testing challenges - an often overlooked, yet important topic. Finally, we will discuss SCM emulation techniques for end-toend testing of SCM-based software components. In contrast to surveys investigating the use of SCM in database systems, this tutorial is designed as a programming guide for researchers and professionals interested in leveraging SCM in database systems.

关键词： testing dram programming model data structures main memory emulation non-volatile memory memory management storage-class memory crash simulation

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Generic Driver Injection for Automated IoT Application Deployments 17

Generic Driver Injection for Automated IoT Application Deplo...

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19th International Conference on Information Integration and Web-Based Applications and Services (iiWAS)

作者： Saatkamp, Karoline Breitenbuecher, Uwe Leymann, Frank Wurster, Michael Univ Stuttgart Inst Architecture Applicat Syst Stuttgart Germany

ISBN: (纸本)9781450352994

In the domain of IoT a major objective is the interconnection of a variety of devices with higher level applications. Therefore, several IoT middleware systems have been developed. These IoT integration middleware systems are heterogeneous, e.g., in terms of the supported transport protocols. Thus, IoT environments often differ due to the utilized middleware. As a result, by deploying applications in different environments the communication clients on the application side have to be adjusted manually. This leads to a greater development effort for each deployment and hampers the application's portability. In this paper, we present a generic driver injection concept to enable the development of portable IoT applications and the automated deployment in different environments without manual adaptation efforts. For this, a programming model and a deployment modeling concept are introduced. We demonstrate the feasibility of our approach with a TOSCA-based prototype.

关键词： IoT Application Deployment Drivers programming model TOSCA

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ΣC: A programming model and Language for Embedded Manycores

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11th International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Goubier, Thierry Sirdey, Renaud Louise, Stephane David, Vincent CEA LIST Embedded Real Time Syst Lab F-91191 Gif Sur Yvette France

ISBN: (纸本)9783642246494

We present Sigma C, a programming model and language for high performance embedded manycores. The programming model is based on process networks with non determinism extensions and process behavior specifications. The language itself extends C, with parallelism, composition and process abstractions. It is intended to support architecture independent, high-level parallel programming on embedded manycores, and allows for both low execution overhead and strong execution guarantees. Sigma C is being developed as part of an industry-grade tool chain for a high performance embedded manycore architecture.

关键词： programming model programming language embedded manycores embedded high performance computing

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DaSH: A benchmark suite for hybrid dataflow and shared memory programming models

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PARALLEL COMPUTING 2015年 45卷 18-48页

作者： Gajinov, Vladimir Stipic, Srdjan Eric, Igor Unsal, Osman S. Ayguade, Eduard Cristal, Adrian Barcelona Supercomp Ctr Barcelona Spain Univ Politecn Cataluna E-08028 Barcelona Spain Univ Belgrade Belgrade 11001 Serbia Artificial Intelligence Res Inst Barcelona Spain Spanish Natl Res Council Madrid Spain

The current trend in development of parallel programming models is to combine different well established models into a single programming, model in order to support efficient implementation of a wide range of real world applications. The dataflow model has particularly managed to recapture the interest of the research community due to its ability to express parallelism efficiently. Thus, a number of recently proposed hybrid parallel programming models combine dataflow and traditional shared memory models. Their findings have influenced the introduction of task dependency in the OpenMP 4.0 standard. This article presents DaSH - the first comprehensive benchmark suite for hybrid dataflow and shared memory programming models. DaSH features 11 benchmarks, each representing one of the Berkeley dwarfs that capture patterns of communication and computation common to a wide range of emerging applications. DaSH also includes sequential and shared-memory implementations based on OpenMP and Intel TBB to facilitate easy comparison between hybrid dataflow implementations and traditional shared memory implementations based on work-sharing and/or tasks. Finally, we use DaSH to evaluate three different hybrid dataflow models, identify their advantages and shortcomings, and motivate further research on their characteristics. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Benchmark suite Dataflow Shared memory Transactional memory programming model

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A high-performance finite-volume algorithm for solving partial differential equations governing compressible viscous flows on structured grids

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COMPUTERS & MATHEMATICS WITH APPLICATIONS 2016年第9期72卷 2098-2118页

作者： Guzik, S. M. Gao, X. Olschanowsky, C. Colorado State Univ Dept Mech Engn Ft Collins CO 80523 USA Colorado State Univ Dept Comp Sci Ft Collins CO 80523 USA

This work focuses on the development of a high-performance fourth-order finite-volume method to solve the nonlinear partial differential equations governing the compressible Navier-Stokes equations on a Cartesian grid with adaptive mesh refinement. The novelty of the present study is to introduce the loop chaining concept to this complex fourth-order fluid dynamics algorithm for significant improvement in code performance on parallel machines. Specific operations involved in the algorithm include the finite-volume formulation of fourth-order spatial discretization stencils and optimal inter-loop parallelization strategies. Numerical fluxes of the Navier-Stokes equations comprise the hyperbolic (inviscid) and elliptic (viscous) components. The hyperbolic flux is evaluated using high-resolution Godunov's method and the elliptic flux is based on fourth-order centered-difference methods everywhere in the computational domain. The use of centered-difference methods everywhere supports the idea of fusing modular codes to achieve high efficiency on modern computers. Temporal discretization is performed using the standard fourth order Runge-Kutta method. The fourth-order accuracy of solution in space and time is verified with a transient Couette flow problem. The algorithm is applied to solve the Sod's shock tube and the transient flat-plate boundary layer flow. The numerical predictions are validated by comparing to the analytical solutions. The performance of the baseline code is compared to that of the fused scheme which fuses modular codes via loop chaining concept and a significant improvement in execution time is observed. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： High-order partial differential equations algorithm High-performance computational fluid dynamics algorithm Fourth-order finite-volume method programming model Loop chaining Parallel adaptive mesh refinement

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HadoopCL2: Motivating the Design of a Distributed, Heterogeneous programming System With Machine-Learning Applications

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2016年第3期27卷 762-775页

作者： Grossman, Max Breternitz, Mauricio Sarkar, Vivek Rice Univ Dept Comp Sci 6100 Main St Houston TX USA AMD Res 7171 Southwest Pkwy Austin TX USA

Machine learning (ML) algorithms have garnered increased interest as they demonstrate improved ability to extract meaningful trends from large, diverse, and noisy data sets. While research is advancing the state-of-the-art in ML algorithms, it is difficult to drastically improve the real-world performance of these algorithms. Porting new and existing algorithms from single-node systems to multi-node clusters, or from architecturally homogeneous systems to heterogeneous systems, is a promising optimization technique. However, performing optimized ports is challenging for domain experts who may lack experience in distributed and heterogeneous software development. This work explores how challenges in ML application development on heterogeneous, distributed systems shaped the development of the HadoopCL2 (HCL2) programming system. ML applications guide this work because they exhibit features that make application development difficult: large & diverse datasets, complex algorithms, and the need for domain-specific knowledge. The goal of this work is a general, MapReduce programming system that outperforms existing programming systems. This work evaluates the performance and portability of HCL2 against five ML applications from the Mahout ML framework on two hardware platforms. HCL2 demonstrates speedups of greater than 20x relative to Mahout for three computationally heavy algorithms and maintains minor performance improvements for two I/O bound algorithms.

关键词： MapReduce heterogeneous distributed programming model GPU auto-scheduling

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