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Nimblock: Scheduling for Fine-grained FPGA Sharing through Virtualization

Meghna Mandava, Paul Reckamp, Deming Chen

2023Year
7Citations
3Top-tier citations

Abstract

As FPGAs become ubiquitous compute platforms, existing research has focused on enabling virtualization features to facilitate finegrained 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- 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, and automatically allocates resources to enable suitable parallelism for an application without additional user input. 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 5.7× lower average response times when compared to a no-sharing and no-virtualization scheduling algorithm and up to 2.1× average response time improvement over competitive scheduling algorithms that support sharing within our virtualization environment. We additionally demonstrate up to 49% fewer deadline violations and up to 2.6× lower tail response times when compared to other high-performance algorithms.

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