CSR-PSCE, SM: Exploring Helper Computing Parallelism in Multicore Architectures

CSR-PSCE、SM：探索多核架构中的辅助计算并行性

• 批准号: 0834664
• 负责人: James Tuck
• 金额: $ 37万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0834664&HistoricalAwards=false
• 关键词: CSR; PSCE; SM; Exploring; Helper

Current trends in computing architectures and programming support the rationales for the proposed project. One trend is the increasing complexity of software both in terms of the number of lines of source code, and number of layers (hypervisor, guest OS, libraries, virtual machines, applications, etc.). This increase in complexity could make software even more vulnerable to bugs and security attacks in the future. Another trend is the increasing support for thread-level parallelism in mainstream microprocessors through chip multi-processor (CMP) architectures. Four and eight processor cores per chip have either been realized or are in the future roadmap of major chipmakers. Currently, mostly applications with natural thread-level parallelism (server and scientific computing workloads) can benefit from them. Increasing reliability and security requirements support parallelism opportunities for common applications, and such parallelism may effectively be exploited through helper computing. This project will address these issues by engaging in the following: exploring helper-computing's potentials for speeding up software reliability and security meta-functions with scenario-guided studies; a systematic, cross-layered study of efficient Meta-function Design, Extraction, Optimization, and Dynamic Adaptation to achieve low overhead execution in the main application; exploration of a prototype system which includes compiler, libraries, run-time system, OS support, and possibly hardware support. The exploration for such support will be holistic, i.e. by considering implementation layers that produce the best trade-offs in the feasibility of the solution in current systems, generality, and performance requirements. This prototype system will be made available to the public.This team also proposes to create an advanced course that focuses on helper computing, and integrate its basic elements into existing hardware and software courses. Such courses would integrate programming language, compiler, OS, runtime system, and hardware in a synergistic way, helping to train future workforce with unique and integrated expertise in these areas.

计算体系结构和编程的当前趋势支持所建议项目的基本原理。一个趋势是软件的复杂性在源代码行数和层数（管理程序、客户操作系统、库、虚拟机、应用程序等）方面都在增加。这种复杂性的增加可能会使软件在未来更容易受到错误和安全攻击。另一个趋势是，通过芯片多处理器（CMP）架构，主流微处理器对线程级并行性的支持越来越多。每个芯片的4和8个处理器内核要么已经实现，要么在主要芯片制造商的未来路线图中。目前，大多数具有自然线程级并行性的应用程序（服务器和科学计算工作负载）都可以从中受益。不断增加的可靠性和安全性需求支持常见应用程序的并行性，并且可以通过辅助计算有效地利用这种并行性。本项目将通过以下方式解决这些问题：通过场景引导研究，探索辅助计算在加速软件可靠性和安全元功能方面的潜力；系统地、跨层地研究高效的元函数设计、提取、优化和动态自适应，以实现主应用程序的低开销执行；探索一个原型系统，包括编译器、库、运行时系统、操作系统支持，可能还有硬件支持。对这种支持的探索将是整体性的，也就是说，通过考虑在当前系统、通用性和性能需求中解决方案的可行性方面产生最佳折衷的实现层。这个原型系统将向公众开放。该团队还建议创建一个专注于辅助计算的高级课程，并将其基本元素集成到现有的硬件和软件课程中。这些课程将以协同的方式整合编程语言、编译器、操作系统、运行时系统和硬件，帮助培养具有这些领域独特和综合专业知识的未来劳动力。