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Managed Runtimes for Energy Efficient Multicore Architecture

节能多核架构的托管运行时

基本信息

批准号：
1849183
负责人：
金额：
--
依托单位：
University of Manchester
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2016
资助国家：
英国
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=studentship-1849183
关键词：
Managed Runtimes Energy Efficient Multicore

项目摘要

Developing, controlling and optimizing distributed applications on modern heterogeneousarchitectures in the context of energy efficiency is a complex task involving trade-offs between rawperformance (operations per second), power consumption (joules per second) and, for manyapplications, the accuracy of the computation (suitably defined), all of which may vary in terms ofsupply and demand - from either the algorithm and/or the hardware - over the lifetime of anapplication.Looking at the Apache projects dedicated to Big Data processing(https://projects.apache.org/projects.html?category), there are 36 different software frameworks.Although there are some projects that are more popular than others, a quick analysis reveals two keytrends. First, most of the software frameworks have inside a data-driven or event-driven model ofcomputation. Secondly, most of the software frameworks run on Java Virtual Machines.The University of Manchester has unique knowledge on data-driven computations, JIT compilers,runtime systems and virtualization. For example, we have been porting the Maxine Virtual Machine (aresearch JVM, https://en.wikipedia.org/wiki/Maxine_Virtual_Machine) to the ARMv7. In addition wehave included and improved the support and performance of the GRAAL JIT compiler in Maxine VM(https://arxiv.org/abs/1509.04085). The current status of Maxine VM on ARMv7 is capable of runningof complex applications, e.g. SLAMBench, on platforms such as the Xilinx Zynq (dual-core ARMCortex A9 with 1GB of memory).For more information on GRAAL and how it is being integrated into the OpenJDK visithttps://github.com/graalvm/graalvm and http://hg.openjdk.java.net/graal/graal-jvmci-9/The University of Manchester has also started working on the port of Maxine VM to ARMv8. Thestudent Hartley started this process as part of his MSc thesis. There is a significant engineering effortthat needs to be dedicated so as to be able to optimize server side Big Data frameworks for ARMv8-based datacenters.The main research question is how and where we can optimize data-driven computations for Big Dataprocessing on ARMv8 servers? The approach taken by this PhD project is to investigate the runtimesystem. That is, look for improvements at the JIT compiler, memory management, JVM as well as theinteraction with the OS and or directly with a hypervisor.This PhD is systems-oriented and we will follow a methodology of investigation driven by buildingprototypes which demonstrate our novel ideas. In order to make progress, the PhD student needs tocommand the literature in, and become familiar with: Managed Runtime Systems optimizations forperformance and energy plus ; compiler and runtime technologies (specifically for ARM-basedsystems); ARM architecture (many-cores, particularly ARMv8 systems.

在能源效率的背景下，在现代异构架构上开发、控制和优化分布式应用程序是一项复杂的任务，涉及在原始性能（每秒操作数）、功耗（每秒焦耳）以及许多应用程序的计算精度（适当定义）之间进行权衡，所有这些都可能在应用程序的整个生命周期内因供需而变化——来自算法和/或硬件。看看专门用于大数据处理的Apache项目（https://projects.apache.org/projects.html?category），有36个不同的软件框架。尽管有一些项目比其他项目更受欢迎，但快速分析可以揭示两个主要趋势。首先，大多数软件框架内部都有数据驱动或事件驱动的计算模型。其次，大多数软件框架都运行在Java虚拟机上。曼彻斯特大学在数据驱动计算、JIT编译器、运行时系统和虚拟化方面拥有独特的知识。例如，我们一直在将Maxine虚拟机（研究JVM， https://en.wikipedia.org/wiki/Maxine_Virtual_Machine）移植到ARMv7上。此外，我们还在Maxine VM（https://arxiv.org/abs/1509.04085）中包含并改进了GRAAL JIT编译器的支持和性能。Maxine VM在ARMv7上的当前状态能够在Xilinx Zynq（双核ARMCortex A9, 1GB内存）等平台上运行复杂的应用程序，例如SLAMBench。关于GRAAL的更多信息，以及它是如何被集成到OpenJDK的，请访问：//github.com/graalvm/graalvm和http://hg.openjdk.java.net/graal/graal-jvmci-9/The曼彻斯特大学也开始了将Maxine VM移植到ARMv8的工作。学生哈特利开始这个过程，作为他的硕士论文的一部分。为了能够优化基于armv8的数据中心的服务器端大数据框架，需要投入大量的工程工作。主要的研究问题是我们如何以及在哪里为ARMv8服务器上的大数据处理优化数据驱动计算？这个博士项目采用的方法是研究运行时系统。也就是说，寻找JIT编译器、内存管理、JVM以及与操作系统或直接与管理程序的交互方面的改进。这个博士学位是以系统为导向的，我们将遵循一种由建筑原型驱动的调查方法，这些原型展示了我们的新想法。为了取得进步，博士生需要掌握和熟悉以下方面的文献：管理运行时系统优化的性能和能量；编译器和运行时技术（特别是基于arm的系统）；ARM架构（多核，特别是ARMv8系统）。