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首页> 外文会议>International Symposium on Computer Architecture and High Performance Computing Workshops >Towards a Dataflow Runtime Environment for Edge, Fog and In-Situ Computing
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Towards a Dataflow Runtime Environment for Edge, Fog and In-Situ Computing

机译：朝向边缘，雾和原位计算的数据流运行时环境

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In the dataflow computation model, instructions or tasks are fired according to their data dependencies, instead of following program order, thus allowing natural parallelism exploitation. Dataflow has been used, in different flavors and abstraction levels (from processors to runtime libraries), as an interesting alternative for harnessing the potential of modern computing systems. Sucuri is a dataflow library for Python that allows users to specify their application as a dependency graph and execute it transparently at clusters of multicores, while taking care of scheduling issues. Recent trends in Fog and In-situ computing assumes that storage and network devices will be equipped with processing elements that usually have lower power consumption and performance. An important decision on such system is whether to move data to traditional processors (paying the communication costs), or performing computation where data is sitting, using a potentially slower processor. Hence, runtime environments that deal with that trade-off are extremely necessary. This work takes a first step towards a solution that considers Edge/Fog/In-situ in a dataflow runtime. We use Sucuri to manage the execution in a small system with a regular PC and a Parallella board. Experiments with text processing applications running with different input sizes, network latency and packet loss rates allow a discussion of scenarios where this approach would be fruitful.
机译：在数据流计算模型中，根据其数据依赖性触发指令或任务，而不是按照以下编程顺序触发，从而允许自然并行开发。在不同的口味和抽象级别（从处理器到运行时库的处理器）中使用了数据流，作为利用现代计算系统的潜力的有趣替代方案。 Sucuri是Python的数据流库，允许用户将其应用程序指定为依赖关系图，并在照顾调度问题时透明地执行它。最近雾和原位计算的趋势假设存储和网络设备将配备有较低功耗和性能的处理元件。关于此类系统的一个重要决定是是否将数据移动到传统处理器（支付通信成本），或使用潜在较慢的处理器执行数据坐姿的计算。因此，处理该权衡的运行时环境非常必要。这项工作迈出了一个迈向在数据流运行时考虑边缘/雾/原位的解决方案。我们使用Sucuri来管理使用常规PC和Parallella板的小型系统中的执行。采用不同输入大小的文本处理应用程序的实验，网络延迟和数据包丢失率允许讨论这种方法将富有成效的情况。

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