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Processing-in-memory architectures and programming libraries for bioinformatics algorithms

Project description

Innovative computing algorithms based on processing-in-memory technology

High-throughput sequencing (HTS) of DNA and RNA is an indispensable part of the research, development and healthcare system. Personal genome sequencing is used in preventive and personalised medicine; HTS technologies can identify rare disease genetic mutations, cancer subtypes, and infections and antibiotic resistance. There is a need for fast, energy- and cost-efficient technologies for genomics research – without the involvement of data centres and cloud platforms. The EU-funded BioPIM project aims to develop powerful edge computing based on emerging processing-in-memory (PIM) technologies. The project will focus on designing bioinformatics algorithms and data structures and several types of PIM architectures to achieve high cost, energy and time efficiency.

Objective

Low cost, high throughput DNA and RNA sequencing (HTS) data is now the main workforce for various genomics and transcriptomics applications. HTS technologies have already started to impact a broad range of research and clinical use for the life sciences. These include, but are not limited to 1) large-scale sequencing studies for population genomics and disease-causing mutation discovery including cancer, 2) metagenomics, 3) comparative genomics, 5) transcriptome profiling, and 6) outbreak detection and tracking including COVID-19, Ebola, and Zika. HTS also impacts the whole health care system in several directions. Although there is still much room for improvement, sequencing of personal genomes is now becoming a part of preventive and personalized medicine as HTS technologies make it possible to 1) identify genetic mutations that enable rare disease diagnosis, 2) determine cancer subtypes therefore guiding treatment options, and 3) characterize infections and antibiotic resistance. Currently all genomics data are processed in energy-hungry computer clusters and data centers, which also necessitate the transfer of data via the internet, which also consumes substantial amounts of energy and wastes valuable time. Therefore there is a need for fast, energy-efficient, and cost-efficient technologies that enable all forms of genomics research without requiring data centers and cloud platforms. In this project we aim to leverage the emerging processing-in-memory (PIM) technologies to enable such powerful edge computing. We will focus on co-designing algorithms and data structures commonly used in bioinformatics together with several types of PIM architectures to obtain the highest benefit in cost, energy, and time savings. BioPIM will also impact other fields that employ similar algorithms. Our designs and algorithms will not be limited to cheap hardware, and they will impact computation efficiency on all forms of computing environments including cloud platforms.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-EIC - HORIZON EIC Grants

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Call for proposal

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(opens in new window) HORIZON-EIC-2021-PATHFINDEROPEN-01

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Coordinator

BILKENT UNIVERSITESI VAKIF
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 380 000,00
Address
ESKISEHIR YOLU 8 KM
06800 Bilkent Ankara
Türkiye

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Region
Batı Anadolu Ankara Ankara
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 380 000,00

Participants (5)

Partners (2)

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