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The Chan Zuckerberg Initiative (CZI) has awarded a two-year grant valued at $400,000 to professors Davide Risso of the Department of Statistical Sciences of the University of Padua and Gabriele Sales of the Department of Biology of the University of Padua, and to collaborator Levi Waldron of City University of New York (USA) as part of the Essential Open Source Software for Science program.
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GPUs were initially used to render high-definition video, but now many have become essential for artificial intelligence, machine learning, and other compute-intensive tasks. Researchers will use the funds to develop and test GPU-accelerated packages for bioinformatics, improve continuous integration for GPU code, and create intuitive tools for managing system-level dependencies.
Professor Davide Risso, co-investigator on the project, said, “This funding will enable hundreds of software developers to harness the power of GPUs for biomedical research as part of the Bioconductor project. Through the development of software packages for GPU programming, we aim to accelerate computer-intensive analyses, particularly in fields such as single-cell genomics".
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Professor Gabriele Sales added, “For over two decades, Bioconductor has been a cornerstone of bioinformatics. This funding will help us future-proof our infrastructure and enable biomedical researchers to use GPU programming in a more accessible way."
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GPUs were initially used to render high-definition video, but now many have become essential for artificial intelligence, machine learning, and other compute-intensive tasks. Researchers will use the funds to develop and test GPU-accelerated packages for bioinformatics, improve continuous integration for GPU code, and create intuitive tools for managing system-level dependencies.
Professor Davide Risso, co-investigator on the project, said, “This funding will enable hundreds of software developers to harness the power of GPUs for biomedical research as part of the Bioconductor project. Through the development of software packages for GPU programming, we aim to accelerate computer-intensive analyses, particularly in fields such as single-cell genomics".
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Professor Gabriele Sales added, “For over two decades, Bioconductor has been a cornerstone of bioinformatics. This funding will help us future-proof our infrastructure and enable biomedical researchers to use GPU programming in a more accessible way."
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This funding will support the expansion of GPU-accelerated Bioconductor packages through continuous integration, user-friendly packaging of system-level dependencies, and foundational packages for Bioconductor GPU programming.
GPUs were initially used to render high-definition video, but now many have become essential for artificial intelligence, machine learning, and other compute-intensive tasks. Researchers will use the funds to develop and test GPU-accelerated packages for bioinformatics, improve continuous integration for GPU code, and create intuitive tools for managing system-level dependencies.
Professor Davide Risso, co-investigator on the project, said, “This funding will enable hundreds of software developers to harness the power of GPUs for biomedical research as part of the Bioconductor project. Through the development of software packages for GPU programming, we aim to accelerate computer-intensive analyses, particularly in fields such as single-cell genomics".
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2. Implement a flexible software packaging system that considers the fact that packages often depend on external tools that need to be installed and configured correctly
3. Develop core packages for GPU programming in Bioconductor
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2. Implement a flexible software packaging system that considers the fact that packages often depend on external tools that need to be installed and configured correctly
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Professor Davide Risso, co-investigator on the project, said, “This funding will enable hundreds of software developers to harness the power of GPUs for biomedical research as part of the Bioconductor project. Through the development of software packages for GPU programming, we aim to accelerate computer-intensive analyses, particularly in fields such as single-cell genomics".
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The Chan Zuckerberg Initiative (CZI) has awarded a two-year grant valued at $400,000 to professors Davide Risso of the Department of Statistical Sciences of the University of Padua and Gabriele Sales of the Department of Biology of the University of Padua, and to collaborator Levi Waldron of City University of New York (USA) as part of the Essential Open Source Software for Science program.
This funding will support the expansion of GPU-accelerated Bioconductor packages through continuous integration, user-friendly packaging of system-level dependencies, and foundational packages for Bioconductor GPU programming.
GPUs were initially used to render high-definition video, but now many have become essential for artificial intelligence, machine learning, and other compute-intensive tasks. Researchers will use the funds to develop and test GPU-accelerated packages for bioinformatics, improve continuous integration for GPU code, and create intuitive tools for managing system-level dependencies.
Professor Davide Risso, co-investigator on the project, said, “This funding will enable hundreds of software developers to harness the power of GPUs for biomedical research as part of the Bioconductor project. Through the development of software packages for GPU programming, we aim to accelerate computer-intensive analyses, particularly in fields such as single-cell genomics".
The project will also improve Bioconductor's build system to ensure the reliability and reproducibility of GPU-accelerated packages across different computing platforms.
Professor Gabriele Sales added, “For over two decades, Bioconductor has been a cornerstone of bioinformatics. This funding will help us future-proof our infrastructure and enable biomedical researchers to use GPU programming in a more accessible way."
The contribution will finance three main objectives:
1. Extend Bioconductor's continuous integration infrastructure to test GPU code
2. Implement a flexible software packaging system that considers the fact that packages often depend on external tools that need to be installed and configured correctly
3. Develop core packages for GPU programming in Bioconductor
This initiative is expected to significantly enhance Bioconductor's capabilities in managing biomedical data at scale, benefiting researchers around the world.
The Chan Zuckerberg Initiative's main areas of work include Science, Education, and Justice and Opportunity, which focuses on promoting housing affordability, criminal justice reform, and immigration reform. The mission of the Chan Zuckerberg Initiative is to "build a more inclusive, just, and healthy future for all" and to "advance human potential and promote equality in areas such as health, education, scientific research, and energy."
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This funding will support the expansion of GPU-accelerated Bioconductor packages through continuous integration, user-friendly packaging of system-level dependencies, and foundational packages for Bioconductor GPU programming.
GPUs were initially used to render high-definition video, but now many have become essential for artificial intelligence, machine learning, and other compute-intensive tasks. Researchers will use the funds to develop and test GPU-accelerated packages for bioinformatics, improve continuous integration for GPU code, and create intuitive tools for managing system-level dependencies.
Professor Davide Risso, co-investigator on the project, said, “This funding will enable hundreds of software developers to harness the power of GPUs for biomedical research as part of the Bioconductor project. Through the development of software packages for GPU programming, we aim to accelerate computer-intensive analyses, particularly in fields such as single-cell genomics".
The project will also improve Bioconductor's build system to ensure the reliability and reproducibility of GPU-accelerated packages across different computing platforms.
Professor Gabriele Sales added, “For over two decades, Bioconductor has been a cornerstone of bioinformatics. This funding will help us future-proof our infrastructure and enable biomedical researchers to use GPU programming in a more accessible way."
The contribution will finance three main objectives:
1. Extend Bioconductor's continuous integration infrastructure to test GPU code
2. Implement a flexible software packaging system that considers the fact that packages often depend on external tools that need to be installed and configured correctly
3. Develop core packages for GPU programming in Bioconductor
This initiative is expected to significantly enhance Bioconductor's capabilities in managing biomedical data at scale, benefiting researchers around the world.
The Chan Zuckerberg Initiative's main areas of work include Science, Education, and Justice and Opportunity, which focuses on promoting housing affordability, criminal justice reform, and immigration reform. The mission of the Chan Zuckerberg Initiative is to "build a more inclusive, just, and healthy future for all" and to "advance human potential and promote equality in areas such as health, education, scientific research, and energy."
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This funding will support the expansion of GPU-accelerated Bioconductor packages through continuous integration, user-friendly packaging of system-level dependencies, and foundational packages for Bioconductor GPU programming.
GPUs were initially used to render high-definition video, but now many have become essential for artificial intelligence, machine learning, and other compute-intensive tasks. Researchers will use the funds to develop and test GPU-accelerated packages for bioinformatics, improve continuous integration for GPU code, and create intuitive tools for managing system-level dependencies.
Professor Davide Risso, co-investigator on the project, said, “This funding will enable hundreds of software developers to harness the power of GPUs for biomedical research as part of the Bioconductor project. Through the development of software packages for GPU programming, we aim to accelerate computer-intensive analyses, particularly in fields such as single-cell genomics".
The project will also improve Bioconductor's build system to ensure the reliability and reproducibility of GPU-accelerated packages across different computing platforms.
Professor Gabriele Sales added, “For over two decades, Bioconductor has been a cornerstone of bioinformatics. This funding will help us future-proof our infrastructure and enable biomedical researchers to use GPU programming in a more accessible way."
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1. Extend Bioconductor's continuous integration infrastructure to test GPU code
2. Implement a flexible software packaging system that considers the fact that packages often depend on external tools that need to be installed and configured correctly
3. Develop core packages for GPU programming in Bioconductor
This initiative is expected to significantly enhance Bioconductor's capabilities in managing biomedical data at scale, benefiting researchers around the world.
The Chan Zuckerberg Initiative's main areas of work include Science, Education, and Justice and Opportunity, which focuses on promoting housing affordability, criminal justice reform, and immigration reform. The mission of the Chan Zuckerberg Initiative is to "build a more inclusive, just, and healthy future for all" and to "advance human potential and promote equality in areas such as health, education, scientific research, and energy."
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