Nimblock: scheduling for fine-grained FPGA sharing through virtualization

Reckamp, Paul

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https://hdl.handle.net/2142/115575 Copy

Description

Title

Nimblock: scheduling for fine-grained FPGA sharing through virtualization

Author(s)

Reckamp, Paul

Issue Date

2022-04-25

Director of Research (if dissertation) or Advisor (if thesis)

Chen, Deming

Department of Study

Electrical & Computer Eng

Discipline

Electrical & Computer Engr

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• FPGA
• Virtualization
• Scheduling

Abstract

As FPGAs become ubiquitous compute platforms, existing research has focused on enabling virtualization features to facilitate fine-grained FPGA sharing. We employ an overlay architecture which enables arbitrary, independent user logic to share portions of a single FPGA by dividing the FPGA into independently reconfigurable slots. We then explore scheduling possibilities to effectively time-multiplex and space-multiplex the virtualized FPGA by introducing Nimblock. The Nimblock scheduling algorithm balances application priorities and performance degradation to improve response time and reduce deadline violations. Unlike other algorithms, Nimblock explores preemption as a scheduling parameter to dynamically change resource allocations. In our exploration, we evaluate five scheduling algorithms: a baseline, three existing algorithms, and our novel Nimblock algorithm. We demonstrate system feasibility by realizing the complete system on a Xilinx ZCU106 FPGA and evaluating on a set of real-world benchmarks. In our results, we achieve up to 9× lower median response times when compared to the baseline scheduling algorithms. We additionally demonstrate up to 21% fewer deadline violations and up to 2.1× lower tail response times when compared to other high-performance algorithms.

Graduation Semester

2022-05

Type of Resource

Thesis

Handle URL

https://hdl.handle.net/2142/115575

Copyright and License Information

Copyright 2022 Paul Reckamp

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