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Abstract:
Learn about NVIDIA's new open source CUDA/C++ library for high-performance computational genomics, NVBIO. NVBIO includes primitives for fast alignment using many variants of Smith-Waterman, text indexing via an FM-Index and related data structures, and approximate string matching with backtracking. It also provides basic services like file IO and inter-thread communication. The design of NVBIO supports pipeline parallelism, where computation is expressed as a sequence of stages with queues to communicate between stages. Using this design concept, we have engineered an implementation of the Bowtie2 aligner on top of NVBIO, which aligns short read data 2-7x faster than the original Bowtie2 running on a high-end multicore CPU at comparable quality. In this talk we will introduce the codebase and demonstrate how to use it for your own applications.
Learn about NVIDIA's new open source CUDA/C++ library for high-performance computational genomics, NVBIO. NVBIO includes primitives for fast alignment using many variants of Smith-Waterman, text indexing via an FM-Index and related data structures, and approximate string matching with backtracking. It also provides basic services like file IO and inter-thread communication. The design of NVBIO supports pipeline parallelism, where computation is expressed as a sequence of stages with queues to communicate between stages. Using this design concept, we have engineered an implementation of the Bowtie2 aligner on top of NVBIO, which aligns short read data 2-7x faster than the original Bowtie2 running on a high-end multicore CPU at comparable quality. In this talk we will introduce the codebase and demonstrate how to use it for your own applications.  Back
 
Topics:
Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2014
Session ID:
S4741
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Abstract:

Please join Jonathan Cohen supported by other members of the NVIDIA engineering team responsible for the new high performance libraries which are part of the CUDA 6 Toolkit. In this webinar, the team will present the latest performance improvements and give attendees a chance to ask questions and even make suggestions for future enhancements - a must attend webinar for any serious GPU Computing Developer. CUDA 6.0 Production is now available download : www.nvidia.com/getcuda

Please join Jonathan Cohen supported by other members of the NVIDIA engineering team responsible for the new high performance libraries which are part of the CUDA 6 Toolkit. In this webinar, the team will present the latest performance improvements and give attendees a chance to ask questions and even make suggestions for future enhancements - a must attend webinar for any serious GPU Computing Developer. CUDA 6.0 Production is now available download : www.nvidia.com/getcuda

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Topics:
Tools & Libraries
Type:
Webinar
Event:
GTC Webinars
Year:
2014
Session ID:
GTCE087
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Abstract:

NVIDIA has been developing a library of high-performance parallel sparse iterative linear solvers, with an emphasis on multilevel and multigrid methods. In this presentation, I will provide an overview of the library''s design and outline many of the challenges we have faced in balancing numerical behavior against parallel scalability. Our library has been integrated into ANSYS Fluent 14.5, and will be released as a fully supported feature in the upcoming Fluent 15. I will describe the collaboration between ANSYS and NVIDIA, and present benchmarking results across a variety of test problems from CFD and other fields. Finally, I will talk about our future plans and discuss some of the open research problems in the area of algebraic multigrid on massively parallel processors.

NVIDIA has been developing a library of high-performance parallel sparse iterative linear solvers, with an emphasis on multilevel and multigrid methods. In this presentation, I will provide an overview of the library''s design and outline many of the challenges we have faced in balancing numerical behavior against parallel scalability. Our library has been integrated into ANSYS Fluent 14.5, and will be released as a fully supported feature in the upcoming Fluent 15. I will describe the collaboration between ANSYS and NVIDIA, and present benchmarking results across a variety of test problems from CFD and other fields. Finally, I will talk about our future plans and discuss some of the open research problems in the area of algebraic multigrid on massively parallel processors.

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Topics:
Developer - Algorithms, Seismic & Geosciences, Computational Fluid Dynamics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2013
Session ID:
S3579
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Abstract:

Because of their inherently parallel and high-throughput nature, NVIDIA GPUs are a natural fit for the types of data-intensive computing required in bioinformatics applications. For many genomics applications, the primary challenge is to map highly divergent and control flow-heavy code to a SIMD architecture. By transforming complex serial flow of control into a sequence of communicating sequential processors running in parallel, we are able to achieve high throughput on very branchy code, while maintaining memory coherence and avoiding execution divergence. I will present initial results from NVIDIA''s internal "nvbio" project to develop efficient computational building blocks for analysis of Next-Generation Sequencing data, with a focus on implementations of BWA and Bowtie2-type aligners.

Because of their inherently parallel and high-throughput nature, NVIDIA GPUs are a natural fit for the types of data-intensive computing required in bioinformatics applications. For many genomics applications, the primary challenge is to map highly divergent and control flow-heavy code to a SIMD architecture. By transforming complex serial flow of control into a sequence of communicating sequential processors running in parallel, we are able to achieve high throughput on very branchy code, while maintaining memory coherence and avoiding execution divergence. I will present initial results from NVIDIA''s internal "nvbio" project to develop efficient computational building blocks for analysis of Next-Generation Sequencing data, with a focus on implementations of BWA and Bowtie2-type aligners.

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Topics:
Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2013
Session ID:
S3580
Streaming:
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Topics:
Tools & Libraries
Type:
Webinar
Event:
GTC Webinars
Year:
2013
Session ID:
GTCE028
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Abstract:

The goal of this session is to compare the performance of graph matching and graph coloring algorithms on massively parallel devices such as GPUs. We present novel algorithms, which produce superior results for certain graphs and also discuss the techniques used to efficiently implement these algorithms on the GPU.

The goal of this session is to compare the performance of graph matching and graph coloring algorithms on massively parallel devices such as GPUs. We present novel algorithms, which produce superior results for certain graphs and also discuss the techniques used to efficiently implement these algorithms on the GPU.

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Topics:
Developer - Algorithms
Type:
Talk
Event:
GTC Silicon Valley
Year:
2012
Session ID:
S2332
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Speakers:
Jonathan Cohen
- NVIDIA Research
Abstract:
OpenCurrent is an open source library with support for structured 3D grids and various PDE solvers that operate on them, including a multigrid Poisson solver and an incompressible Navier-Stokes solver. It also includes extensions for splitting grids across multiple GPUs. This talk will provide a basic introduction to the code base and its design principles.
OpenCurrent is an open source library with support for structured 3D grids and various PDE solvers that operate on them, including a multigrid Poisson solver and an incompressible Navier-Stokes solver. It also includes extensions for splitting grids across multiple GPUs. This talk will provide a basic introduction to the code base and its design principles.  Back
 
Topics:
Computational Fluid Dynamics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2010
Session ID:
2022
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Speakers:
Jonathan Cohen
Abstract:

I will describe tricks for building APIs using C++ metaprogramming that generate custom kernels for complex manipulation of device-side arrays in CUDA. Using a variation of Expression Templates, multiple operations can be fused into a single kernel that executes with reasonable efficiency.

I will describe tricks for building APIs using C++ metaprogramming that generate custom kernels for complex manipulation of device-side arrays in CUDA. Using a variation of Expression Templates, multiple operations can be fused into a single kernel that executes with reasonable efficiency.

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Topics:
Programming Languages, Tools & Libraries
Type:
Talk
Event:
GTC Silicon Valley
Year:
2010
Session ID:
S1020230
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Speakers:
Jonathan Cohen, Michael Garland
- NVIDIA
 
Topics:
HPC and AI
Type:
Talk
Event:
Supercomputing
Year:
2009
Session ID:
SC0914
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Speakers:
Jonathan Cohen, Michael Garland
- NVIDIA
 
Topics:
HPC and AI
Type:
Talk
Event:
Supercomputing
Year:
2009
Session ID:
SC0914
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