Next Generation Software: SmartApps: Smart Applications for Heterogeneous Computing

下一代软件：SmartApps：异构计算的智能应用程序

• 批准号: 9975018
• 负责人: Lawrence Rauchwerger
• 金额: $ 30万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-10-01 至 2003-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9975018&HistoricalAwards=false
• 关键词: Next; Generation; Software; SmartApps; Smart

EIA-9975018Rauchwerger, LawrenceCISE Next Generation Software(NG)Texas Engineering Experimental StationSmartApps: Smart Applications for Heterogeneous ComputingThis proposal proposes to generate SMART APPLICATION code that uses information about its input data, operating system services and architecture capability, to adaptively reconfigure the application and the OS/hardware platform. To enable very aggressive optimizations, we propose to build a two-stage compiler which has a static and run-time component. The run-time component is extremely fast, works in parallel on the target machine and can read all relevant input data, and the operating system and architectural capabilities. Furthermore, to adapt the performance to variable program inputs during execution, we propose to use novel speculative run-time adaptive optimization techniques (for example, the PI's speculative parallelization and a feedback loop of performance evaluator, predictor and optimizer inputs. All this support will be enabled by a run-time library and the necessary compiler-embedded code in the executable. With this approach, the application can adapt itself and its environment to its needs by issuing appropriate commands. For instance, it is able to control data placement by the OS, control the I/O subsystem, modify coherence protocols and establish network connections. Moreover, smart applications are able to respond to the failures and large performance variations that distributed systems suffer.

EIA-9975018Rauchwerger，LawrenceCISE 下一代软件（NG）德克萨斯工程实验站SmartApps：异构计算的智能应用程序该提案建议生成智能应用程序代码，该代码使用有关其输入数据、操作系统服务和架构功能的信息，以自适应地重新配置应用程序和操作系统/硬件平台。 为了实现非常积极的优化，我们建议构建一个具有静态和运行时组件的两阶段编译器。 运行时组件速度极快，在目标机器上并行工作，可以读取所有相关的输入数据以及操作系统和架构功能。 此外，为了使性能适应执行期间可变的程序输入，我们建议使用新颖的推测运行时自适应优化技术（例如，PI 的推测并行化以及性能评估器、预测器和优化器输入的反馈循环。所有这些支持将通过运行时库和可执行文件中必要的编译器嵌入代码来启用，通过这种方法，应用程序可以通过发出适当的命令来适应其自身及其环境，例如，它能够通过以下方式控制数据放置。操作系统，此外，智能应用程序能够响应分布式系统所遭受的故障和巨大的性能变化。