CAREER: Flexible Architectures for Data-Intensive Computing

这项研究的重点是数据密集型计算-在传统计算机系统的内存和I/O子系统中嵌入处理能力，并将代码发送到数据，而不是通过主微处理器移动数据。 新的架构，可以利用这种新发现的灵活性，在内存和I/O系统有可能显着提高性能和鲁棒性。它们还将消除当前并行和单处理器架构中的三个重要限制：可扩展多处理器中的硬连线缓存一致性协议，具有不良步幅访问或不良空间局部性的应用程序的缓存性能差，以及I/O密集型应用程序中的延迟和带宽瓶颈。 这项研究专门解决这些限制，包括开发新的一致性协议和公平机制的可编程存储器系统;和必要的协议扩展的发展，转换成一个积极的内存机的FLASH多处理器。这将通过利用硬件原型来运行现实世界的问题并深入了解灵活内存和I/O系统的潜力来实现。最后，完成了一种面向数据密集型计算的高性能新型统一架构Active Fabric的设计。

This research focuses on data-intensive computing---embedding processing capability in the memory and I/O subsystems of traditional computer systems and shipping the code to the data rather than moving the data through the main microprocessor. Novel architectures that can exploit this newfound flexibility in the memory and I/O system have the potential to significantly improve performance and robustness. They will also remove three important limitations in current parallel and uniprocessor architectures: hardwired cache coherence protocols in scalable multiprocessors, poor cache performance for applications with bad stride accesses or poor spatial locality, and latency and bandwidth bottlenecks in I/O-intensive applications. This research specifically addresses those limitations and includes the development of novel coherence protocols and fairness mechanisms for programmable memory systems; and the development of the necessary protocol extensions to convert the FLASH multiprocessor into an active memory machine. This will be done by exploiting the existence of a hardware prototype to run real-world problems and gain insight into the potential of flexible memory and I/O systems. Finally, the design of Active Fabric, a high performance novel unified architecture for data-intensive computing will be accomplished.