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A Configurable TLB Hierarchy for the RISC-V Architecture

机译:RISC-V体系结构的可配置TLB层次结构

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The Rocket Chip Generator uses a collection of parameterized processor components to produce RISC-V-based SoCs. It is a powerful tool that can produce a wide variety of processor designs ranging from tiny embedded processors to complex multi-core systems. In this paper we extend the features of the Memory Management Unit of the Rocket Chip Generator and specifically the TLB Hierarchy. TLBs are essential in terms of performance because they mitigate the overhead of frequent Page Table Walks, but may harm the critical path of the processor due to their size and/or associativity. In the original Rocket Chip implementation the L1 Data/Instruction TLB is fully-associative and the shared L2 TLB is direct-mapped. We lift these restrictions and design and implement configurable, set-associative L1 and L2 TLB templates that can create any organization from direct-mapped to fully-associative to achieve the desired ratio of performance and resource utilization, especially for larger TLBs. We present the area for different configurations and evaluate the overall performance of our design using the SPEC2006 benchmark suite on the Xilinx ZCU102 FPGA. Our design is intended both for ASIC implementation and for FPGA-friendly soft processors. As FPGAs continue to increase in size, it becomes increasingly attainable and desirable to use configurable high-performance soft processors that can run full-fledged operating systems, especially for applications with large memory footprints.
机译:火箭芯片生成器使用一组参数化的处理器组件来生产基于RISC-V的SoC。它是一个功能强大的工具,可以生成从微型嵌入式处理器到复杂的多核系统的各种处理器设计。在本文中,我们扩展了Rocket Chip Generator的内存管理单元的功能,尤其是TLB层次结构。 TLB在性能方面至关重要,因为它们可以减轻频繁的页表遍历的开销,但由于其大小和/或关联性,可能会损害处理器的关键路径。在原始的Rocket Chip实现中,L1数据/指令TLB是完全关联的,而共享的L2 TLB是直接映射的。我们消除了这些限制,设计并实现了可配置的,集合关联的L1和L2 TLB模板,这些模板可以创建从直接映射到完全关联的任何组织,以实现所需的性能和资源利用率,尤其是对于较大的TLB。我们介绍了不同配置的领域,并使用Xilinx ZCU102 FPGA上的SPEC2006基准套件评估了我们设计的整体性能。我们的设计既适用于ASIC实现,也适用于FPGA友好的软处理器。随着FPGA尺寸的不断增加,使用可运行成熟操作系统的可配置高性能软处理器,尤其是对于具有大内存占用空间的应用,变得越来越容易实现,并且越来越令人期望。

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