Qilin: Enabling performance analysis and optimization of shared-virtual memory systems with FPGA accelerators

While the tight integration of components in heterogeneous systems has increased the popularity of the Shared-Virtual Memory (SVM) system programming model, the overhead of SVM can significantly impact end-to-end application performance. However, studying SVM implementations is difficult, as there is no open and flexible system to explore trade-offs between different SVM implementations and the SVM design space is not clearly defined. To this end, we present Qilin, the first open-source system which enables thorough study of SVM in heterogeneous computing environments for discrete accelerators. Qilin is a transparent and flexible system built on top of an open-source FPGA shell, which allows researchers to alter components of the underlying SVM implementation to understand how SVM design decisions impact performance. Using Qilin, we perform an extensive quantitative analysis on the overheads of three SVM architectures, and generate several insights which highlight the cost and benefits of each architecture. From these insights, we propose a flowchart of how to choose the best SVM implementation given the application characteristics and the SVM capabilities of the system. Qilin also provides application developers a flexible SVM shell for high-performance virtualized applications. Optimizations enabled by Qilin can reduce the latency of translations by 6.86x compared to an open-source FPGA shell.