外围设备的通用内存管理

Weixi Zhu, Alan L. Cox, Scott Rixner
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引用次数: 0

摘要

本文提出了一种用于外围设备的通用内存管理方法GMEM。GMEM为cpu和设备的集中内存管理提供操作系统支持。GMEM提供了一个高级接口来解耦mmu特定的函数。因此,设备驱动程序可以将自己附加到进程的地址空间,并让操作系统负责它们的内存管理。这消除了设备驱动程序“重新发明轮子”的需要,并允许它们从GMEM集成的通用内存优化中受益。此外,gmems在内部协调每个虚拟地址空间中的所有附加设备。这极大地提高了用户级的可编程性,因为程序员可以在他们的程序中使用单个地址空间,即使在跨cpu和多个设备操作时也是如此。一个关于设备驱动程序的案例研究证明了这些好处。基于gmm的IOMMU驱动程序消除了大约700行代码,并且使用比最先进的cpu少32%的cpu获得了54%的高网络接收吞吐量。此外,基于gmm的仿真GPU驱动程序的代码少于70行,不包括其MMU功能。
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GMEM: Generalized Memory Management for Peripheral Devices
This paper presents GMEM, generalized memory management, for peripheral devices. GMEM provides OS support for centralized memory management of both CPU and devices. GMEM provides a high-level interface that decouples MMU-specific functions. Device drivers can thus attach themselves to a process's address space and let the OS take charge of their memory management. This eliminates the need for device drivers to "reinvent the wheel" and allows them to benefit from general memory optimizations integrated by GMEM. Furthermore, GMEM internally coordinates all attached devices within each virtual address space. This drastically improves user-level programmability, since programmers can use a single address space within their program, even when operating across the CPU and multiple devices. A case study on device drivers demonstrates these benefits. A GMEM-based IOMMU driver eliminates around seven hundred lines of code and obtains 54% higher network receive throughput utilizing 32% less CPU compared to the state-of-the-art. In addition, the GMEM-based driver of a simulated GPU takes less than 70 lines of code, excluding its MMU functions.
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