ViTAL: Virtualizing FPGAs in the Cloud

Abstract

Field-Programmable Gate Arrays (FPGAs) have been integrated into the cloud infrastructure to enhance its computing performance by supporting on-demand acceleration. However, system support for FPGAs in the context of the cloud environment is still in its infancy with two major limitations, i.e., the inefficient runtime management due to the tight coupling between compilation and resource allocation, and the high programming complexity when exploiting scale-out acceleration. The root cause is that FPGA resources are not virtualized. In this paper, we propose a full-stack solution, namely ViTAL, to address the aforementioned limitations by virtualizing FPGA resources. Specifically, ViTAL provides a homogeneous abstraction to decouple the compilation and resource allocation. Applications are offline compiled onto the abstraction, while the resource allocation is dynamically determined at runtime. Enabled by a latency-insensitive communication interface, applications can be mapped flexibly onto either one FPGA or multiple FPGAs to maximize the resource utilization and the aggregated system throughput. Meanwhile, ViTAL creates an illusion of a single and large FPGA to users, thereby reducing the programming complexity and supporting scale-out acceleration. Moreover, ViTAL also provides virtualization support for peripheral components (e.g., on-board DRAM and Ethernet), as well as protection and isolation support to ensure a secure execution in the multi-user cloud environment. We evaluate ViTAL on a real system - an FPGA cluster composed of the latest Xilinx UltraScale+ FPGAs (XCVU37P). The results show that, compared with the existing management method, ViTAL enables fine-grained resource sharing and reduces the response time by 82% on average (improving Quality-of-Service) with a marginal virtualization overhead. Moreover, ViTAL also reduces the response time by 25% compared to AmorphOS (operating in high-throughput mode), a recently proposed FPGA virtualization method.

Publication
the 24th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, ser. ASPLOS ‘20, March, 2020
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Yue Zha
PhD Candidate

Has explored the full system for reconfigurable computing and processing-in-memory.