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Pushing Big Data into Accelerators: Can the JVM Saturate Our Hardware?

机译：将大数据推向加速器：JVM可以使我们的硬件饱和吗？

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摘要

Advancements in the field of big data have led into an increasing interest in accelerator-based computing as a solution for computationally intensive problems. However, many prevalent big data frameworks are built and run on top of the Java Virtual Machine (JVM), which does not explicitly offer support for accelerated computing with e.g. GPGPU or FPGA. One major challenge in combining JVM-based big data frameworks with accelerators is transferring data from objects that reside in JVM managed memory to the accelerator. In this paper, arigorous analysis of possible solutions is presented to address this challenge. Furthermore, a tool is presented which generates the required code for four alternative solutions and measures the attainable data transfer speed, given a specific object graph. This can give researchers and designers a fast insight about whether the interface between JVM and accelerator can saturate the computational resources of their accelerator. The benchmarking tool was run on a POWER8 system, for which results show that depending on the size of the objects and collections size, an approach based on the Java Native Interface can achieve between 0.9 and 12 GB/s, ByteBuffers can achieve between 0.7 and 3.3 GB/s, the Unsafe library can achieve between 0.8 and 16 GB/s and finally an approach access the data directly can achieve between 3 and 67 GB/s. From our measurements, we conclude that the HotSpot VM does not yet have standardized interfaces by design that can saturate common bandwidths to accelerators seen today or in the future, although one of the approaches presented in this paper can overcome this limitation.
机译：大数据领域的进步已引起人们对基于加速器的计算作为计算密集型问题的解决方案的兴趣日益浓厚。但是，许多流行的大数据框架是在Java虚拟机（JVM）之上构建和运行的，而Java虚拟机（JVM）并未明确提供对使用例如Java的加速计算的支持。 GPGPU或FPGA。将基于JVM的大数据框架与加速器相结合的一个主要挑战是将数据从驻留在JVM管理的内存中的对象传输到加速器。在本文中，对可能的解决方案进行了严格的分析，以解决这一挑战。此外，给出了一种工具，该工具为四个替代解决方案生成所需的代码，并在给定特定对象图的情况下测量可获得的数据传输速度。这可以使研究人员和设计人员快速了解JVM和加速器之间的接口是否可以饱和其加速器的计算资源。基准测试工具在POWER8系统上运行，结果表明，根据对象的大小和集合的大小，基于Java Native Interface的方法可以达到0.9到12 GB / s，而ByteBuffers可以达到0.7到12 GB / s。 3.3 GHz / s，Unsafe库可以达到0.8到16 GB / s，最后直接访问数据的方法可以达到3到67 GB / s。从我们的测量中，我们得出结论，尽管本文中介绍的一种方法可以克服此限制，但HotSpot VM尚不具备可以使当今或将来看到的加速器的通用带宽饱和的设计接口。

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  • 来源
    《High performance computing》|2017年|220-236|共17页
  • 会议地点 Frankfurt(DE)
  • 作者

    Johan Peltenburg; Ahmad Hesam; Zaid Al-Ars;

  • 作者单位

    Computer Engineering Lab, Delft University of Technology, Delft, Netherlands;

    Computer Engineering Lab, Delft University of Technology, Delft, Netherlands;

    Computer Engineering Lab, Delft University of Technology, Delft, Netherlands;

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  • 原文格式 PDF
  • 正文语种 eng
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