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When FPGA Meets Cloud: A First Look at Performance


Using Big Data Analytics to Cr

Scalable and Secure Big Data I

3D Reconstruction in Canonical
Abstract


Cloud service providers promote their new field programmable gate array (FPGA) infrastructure as a service (IaaS) as the new era of cloud product. This FPGA IaaS wraps virtualized compute resources with FPGA boards, e.g., Amazon AWS F1, and reserves acceleration capability for specific applications. Though this acceleration technique sounds promising, questions like real world performance, best-fit scenarios, portability, etc., still need further clarification. In this paper, we present one of the first few empirical studies that take a close look at FPGA clouds from the tenantsā?? perspective. We have conducted measurement studies on Amazon AWS, Alibaba, and Huawei clouds for over one year. The experimental results show that: (1) Tenants experience severe performance-cost imbalance on FPGA IaaS platforms; (2) The inter-communication performance in FPGA clouds is tightly constrained by hardware drivers, e.g., small optimization of DMA drivers for PCIe can harvest significant performance gain; (3) The virtualized FPGA clouds are far from mature, e.g., small-sized jobs can greatly degrade the performance of FPGA clouds due to underutilized PCIe bandwidth. Our study not only provides useful hints to help tenants with FPGA service selection, but also sheds some lights for cloud providers to improve the performance of FPGA clouds.

KeyWords
FPGA Cloud, FPGA Acceleration, Virtualization, Performance Measurement



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