SPX: Collaborative Research: Moving Towards Secure and Massive Parallel Computing

现代计算系统已经从单核、单处理器设备发展到更现代的多核并行处理器，这些处理器可以在网络系统中运行，并且可以在工业和政府推广的仓库规模的云中使用。这个新的并行、互联的大数据世界需要从算法到系统和计算机架构等多个层面的基础研究。该项目旨在通过构建和开发大规模并行计算的新通用框架，在现实生活场景中，通常涉及隐私和安全，在研究这一重要研究挑战中的大量算法和系统问题方面迈出初步步骤。调查人员吗?长期目标包括两个方向。作为这项工作的第一个推动力，研究人员的目标是在实际的MapReduce框架中为大规模并行计算设计基本和有效的算法，特别是通过减少该框架中的轮数。作为这项工作的第二个推动力，研究人员的目标是用更好的数据结构和抽象来增强当前的并行环境和架构，以开发基本算法的简化和快速实现，以便每个人都可以在实践中使用它们。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Modern computing systems have moved beyond single-core, single-processor devices to more modern multi-core parallel processors operating in networked systems and available in warehouse-scale clouds popularized by industries and the government. This new parallel, interconnected, big-data world requires fundamental research on multiple levels from algorithms to systems and computer architecture. This project seeks to take initial steps in the study of the expansive set of algorithms and systems issues in this important research challenge by building and developing new general frameworks for massive parallel computation, often involving privacy and security, in real-life scenarios. The investigators? long-term goals include two directions. As the first thrust of this effort, the investigators aim to design fundamental and efficient algorithms for massive parallel computations in the practical MapReduce framework, in particular by reducing the number of rounds in this framework. As the second thrust of this effort, the investigators aim to augment current parallel environments and architectures with better data structures and abstractions to develop simplified and fast implementations of fundamental algorithms such that everyone can use them in practice.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.