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Most modern computing systems are heterogeneous, either for organic reasons because components grew independently as it is the case in desktop grids, or by design to leverage the strength of specific hardware as it is the case in accelerated systems. In any case, all computing systems have some form of hardware or software heterogeneity that must been managed, leveraged and understood. HCW is a venue to discuss and innovate in all theoretical and practical aspects of heterogeneous computing: programmability, modeling, design,applications, efficient utilization, algorithms, etc.. Authors are encouraged to submit papers on topics including but not limited to:

Heterogeneous Systems and Architecture. Accelerated systems (GPUs,Xeon Phi, FPGAs,big.LITTLE, ...). Heterogeneous distributed systems (grid, desktop grid, cloud, hybrid clusters) including software heterogeneity. Deep-memory hierarchies (HDD,DRAM, cache, NUMA) and novel explicit memory systems (SSD, NVRAM, 3D stacked memory).

Programming Models and Tools. Code reusability. Performance-abstraction tradeoff. Interoperability of heterogeneous software environments. Middleware and runtime systems. Workflows. Dataflows.

Algorithms for Heterogeneous Parallel System. Parallel algorithms for solving problems on heterogeneous systems. Algorithms for managing heterogeneous resources including allocation and scheduling.

Performance. Modeling, optimizing, improving the time to solve a problem (throughput, latency, runtime), the electric consumption (power, energy) and failure management (fault tolerance, recovery,reliability).

Applications on Heterogeneous System. Case studies. Confluence of Big Data systems and heterogeneous systems. Data-intensive computing. Deep Learning. Scientific computing.

We also recall that heterogeneous systems must consist of several different architectures working together.

征稿信息

重要日期

2017-01-23
初稿截稿日期
2017-02-17
初稿录用日期
2017-03-22
终稿截稿日期

征稿范围

Areas or research interest include, but are not limited to:

  • Parallel algorithms for heterogeneous and hierarchical systems, including manycores and hardware accelerators (FPGAs, GPUs, etc.)

  • Parallel algorithms for efficient problem solving on heterogeneous platforms (hybrid clusters, Grids or Clouds)

  • Performance models and their use in the design of parallel and distributed algorithms for heterogeneous platforms

  • Programming paradigms and tools for heterogeneous systems

  • Paradigms, algorithms, and techniques for failure management in high performance heterogeneous com- puting systems and applications

  • Resource management in heterogeneous systems including allocation and scheduling

  • Heterogeneity in computer architectures

  • Performance evaluation and management of heterogeneous systems and applications

  • Ubiquitous computing with heterogeneous systems

  • Application case studies

  • Task coordination and workflow issues in heterogeneous systems

  • Confluence of big data and heterogeneity, including big data for heterogeneous data sets, and exploitation of heterogeneity in data-intensive computing for analytics

  • Interoperability of heterogeneous software systems

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重要日期
  • 05月29日

    2017

    会议日期

  • 01月23日 2017

    初稿截稿日期

  • 02月17日 2017

    初稿录用通知日期

  • 03月22日 2017

    终稿截稿日期

  • 05月29日 2017

    注册截止日期

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