Introducing field-programmable gate arrays in genotype phasing and imputation

TL;DR

This paper introduces an FPGA-accelerated version of EagleImp, a tool for genotype phasing and imputation, significantly speeding up the process without sacrificing quality.

Contribution

The novel use of FPGAs to accelerate genotype phasing and imputation, achieving up to 93% faster performance.

Findings

FPGA acceleration improves EagleImp's performance by up to 93%.

Phasing and imputation quality remains unchanged with FPGA acceleration.

Users can now trade computation time for better quality using more resource-intensive settings.

Abstract

We recently developed EagleImp, a free software that combines genotype phasing and imputation in a single tool. By introducing algorithmic and technical improvements we accelerated the classical two-step approach using Eagle2 and PBWT. Here, we demonstrate how to use field-programmable gate arrays (FPGAs) to accelerate EagleImp even further by a factor of up to 93% without loss of phasing and imputation quality. Due to the speed advantage over a not accelerated processor-based implementation, the FPGA extension of EagleImp allows the user to choose a more resource-intensive parameter setting in exchange for computation time to further improve phasing and imputation quality.

EagleImp and its FPGA extension are freely available at https://github.com/ikmb/eagleimp and https://github.com/ikmb/eagleimp-fpga.

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