A key enabler for the ever-increasing adoption of FPGA accelerators is the availability of frameworks allowing for the seamless coupling to general-purpose host processors. Embedded FPGA+CPU systems still heavily rely on copy-based host-to-accelerator communication, which complicates application development. In this paper, we present a hardware/software framework for enabling transparent, shared virtual memory for FPGA accelerators in embedded SoCs. It can use a hard-macro IOMMU if available, or a configurable soft-core IOMMU that we provide. We explore different TLB configurations and provide a comparison with other designs for shared virtual memory to gain insight on performance-critical IOMMU components. Experimental results using pointer-rich benchmarks show that our framework not only simplifies FPGA-accelerated application development, it also achieves up to 13x speedup compared to traditional copy-based offloading.
Vogel, P., Marongiu, A., Benini, L. (2019). Exploring Shared Virtual Memory for FPGA Accelerators with a Configurable IOMMU. IEEE TRANSACTIONS ON COMPUTERS, 68(4), 510-525 [10.1109/TC.2018.2879080].
Exploring Shared Virtual Memory for FPGA Accelerators with a Configurable IOMMU
Marongiu, Andrea;Benini, Luca
2019
Abstract
A key enabler for the ever-increasing adoption of FPGA accelerators is the availability of frameworks allowing for the seamless coupling to general-purpose host processors. Embedded FPGA+CPU systems still heavily rely on copy-based host-to-accelerator communication, which complicates application development. In this paper, we present a hardware/software framework for enabling transparent, shared virtual memory for FPGA accelerators in embedded SoCs. It can use a hard-macro IOMMU if available, or a configurable soft-core IOMMU that we provide. We explore different TLB configurations and provide a comparison with other designs for shared virtual memory to gain insight on performance-critical IOMMU components. Experimental results using pointer-rich benchmarks show that our framework not only simplifies FPGA-accelerated application development, it also achieves up to 13x speedup compared to traditional copy-based offloading.File | Dimensione | Formato | |
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Exploring 2018.pdf
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