Pushing Big Data into Accelerators: Can the JVM Saturate Our Hardware?
Pushing Big Data into Accelerators: Can the JVM Saturate Our Hardware?
复制标题
将大数据推入加速器：JVM 会使我们的硬件饱和吗？
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Z. Al
中科院分区：
文献类型：
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作者：
J. Peltenburg;Ahmad Hesam;Z. Al
大数据领域的进步已经导致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越来越大。然而，许多流行的大数据框架都是在Java虚拟机（JVM）上构建和运行的，这并没有明确地提供对GPGPU或FPGA等加速计算的支持。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托管内存中的对象传输到加速器。在本文中，可能的解决方案进行了严格的分析，以应对这一挑战。此外，提出了一种工具，它生成所需的代码为四种替代解决方案，并测量可达到的数据传输速度，给定一个特定的对象图。这可以让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会使加速器的计算资源饱和。该基准测试工具在POWER8系统上运行，测试结果表明，根据对象大小和集合大小的不同，基于Java本地接口的方法可以达到0.9到12 GB/s，ByteBuffers可以达到0.7到3.3 GB/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。从我们的测量结果中，我们得出结论，HotSpot VM还没有通过设计实现标准化接口，可以使今天或将来看到的加速器的公共带宽饱和，尽管本文中提出的方法之一可以克服这一限制。
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, a rigorous 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.