2026-09-19T13:07:53Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/120445 2023-09-05 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Chen, Deming 2023-05 application/pdf en text Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01 The student, Meghna Mandava, accepted the attached license on 2023-05-01 at 10:33. The student, Meghna Mandava, submitted this Thesis for approval on 2023-05-01 at 10:43. This Thesis was approved for publication on 2023-05-01 at 17:27. DSpace SAF Submission Ingestion Package generated from Vireo submission #19273 on 2023-09-01 at 17:15:41 Nimblock 2.0: Serverless computing with multi-tenant FPGAS Mandava, Meghna 2023-05-01 Fpga Serverless Computing Reconfigurable Computing Heterogeneous Cloud Serverless computing has gained significant popularity in recent years, especially in cloud computing environments. Although Field-Programmable Gate Arrays (FPGAs) have become increasingly common in cloud computing environments, there has been limited research into how FPGAs can be integrated into serverless computing frameworks to further improve performance and cost-efficiency. We propose Nimblock 2.0 as a means of integrating FPGAs into serverless platforms, enabling developers to leverage the speed and versatility of FPGAs to build and execute high-performance, customizable applications easily. Our evaluation of the Nimblock 2.0 heterogeneous serverless computing model shows that running FPGA workloads in a serverless environment results in an average overhead of only 13%. Allocating requests to both CPU and FPGA compute resources can provide up to a 12% performance improvement. The ability to allocate requests to different resource types can provide significant performance improvements, while considering workload characteristics and priority can further optimize performance. Nimblock 2.0 can enable the efficient use of FPGAs in serverless computing, enabling support for frameworks such as Library-as-a-Service. Text eng https://hdl.handle.net/2142/120445 Copyright 2023 Meghna Mandava M.S. Thesis Computer Science University of Illinois at Urbana-Champaign Computer Science