Transition State Detection Using Single-Instruction, Multiple-Thread Gpgpu Architectures in Single-Molecule Time-Domain Biophysical Data

26 Pages Posted: 16 Feb 2023

See all articles by Boyan Penkov

Boyan Penkov

Columbia University

David Niedzwiecki

University of Pennsylvania

Nicolae Lari

Columbia University

Marija Drndic

University of Pennsylvania

Kenneth Shepard

Columbia University

Abstract

Discrete amplitude levels in ordered, time-domain data often represent different underlying latent states of the system that is being interrogated. Analysis and feature extraction from these data sets generally required considering the order of each individual point; this approach cannot take advantage of contemporary general-purpose graphics processing units (gpGPU) and single-instruction multiple-data (SIMD) instruction set architectures. Two sources of such data from single-molecule biological measurements are nanopores and single-molecule field effect transistor (smFET) nanotube devices; both generate streams of time-ordered current or voltage data, typically sampled near 1 MS/s, with run times of minutes, yielding terabyte-scale datasets. Here, we present three gpGPU-based algorithms to overcome limitations associated with serial event detection in time series data, resulting in a 250× improvement in the rate with which we can detect salient features in nanopore and smFET datasets. The code is freely available.

Keywords: GPU, nanopore, SIMD, sequencing, event detection

Suggested Citation

Penkov, Boyan and Niedzwiecki, David and Lari, Nicolae and Drndic, Marija and Shepard, Kenneth, Transition State Detection Using Single-Instruction, Multiple-Thread Gpgpu Architectures in Single-Molecule Time-Domain Biophysical Data. Available at SSRN: https://ssrn.com/abstract=4360940 or http://dx.doi.org/10.2139/ssrn.4360940

Boyan Penkov (Contact Author)

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

David Niedzwiecki

University of Pennsylvania ( email )

Philadelphia, PA 19104
United States

Nicolae Lari

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

Marija Drndic

University of Pennsylvania ( email )

Philadelphia, PA 19104
United States

Kenneth Shepard

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

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