Affiliation:
1. DEIB, Politecnico di Milano, Milano, ITA
Abstract
“Cloud-native” is the umbrella adjective describing the standard approach for developing applications that exploit cloud infrastructures’ scalability and elasticity at their best. As the application complexity and user-bases grow, designing for performance becomes a first-class engineering concern. As an answer to these needs, heterogeneous computing platforms gained widespread attention as powerful tools to continue meeting SLAs for compute-intensive cloud-native workloads. We propose BlastFunction, an FPGA-as-a-Service full-stack framework to ease FPGAs’ adoption for cloud-native workloads, integrating with the vast spectrum of fundamental cloud models. At the IaaS level, BlastFunction time-shares FPGA-based accelerators to provide multi-tenant access to accelerated resources without any code rewriting. At the PaaS level, BlastFunction accelerates functionalities leveraging the serverless model and scales functions proactively, depending on the workload’s performance. Further lowering the FPGAs’ adoption barrier, an accelerators’ registry hosts accelerated functions ready to be used within cloud-native applications, bringing the simplicity of a SaaS-like approach to the developers. After an extensive experimental campaign against state-of-the-art cloud scenarios, we show how BlastFunction leads to higher performance metrics (utilization and throughput) against native execution, with minimal latency and overhead differences. Moreover, the scaling scheme we propose outperforms the main serverless autoscaling algorithms in workload performance and scaling operation amount.
Publisher
Association for Computing Machinery (ACM)
Cited by
8 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. In-Storage Domain-Specific Acceleration for Serverless Computing;Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2;2024-04-27
2. The first verification test of space-ground collaborative intelligence via cloud-native satellites;China Communications;2024-04
3. The Future of High Performance Computing in Biomimetics and Some Challenges;Series in BioEngineering;2024
4. Nimblock: Scheduling for Fine-grained FPGA Sharing through Virtualization;Proceedings of the 50th Annual International Symposium on Computer Architecture;2023-06-17
5. FPGA acceleration of deep reinforcement learning using on-chip replay management;Proceedings of the 19th ACM International Conference on Computing Frontiers;2022-05-17