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GTC ON-DEMAND

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Abstract:

Nanopore sequencing is a breakthrough technology that marries cutting edge semiconductor processes together with biochemistry, achieving fast, scalable, single molecule DNA sequencing. The challenge is real-time processing of gigabytes of data per second in a compact benchtop instrument. GPUDirect, together with the cuDNN library, enables Roche to maximize the effectiveness of Tesla V100 GPUs in their next generation sequencing instrument. Attendees will learn how these pieces come together to build a streaming AI inference engine to solve a signal processing workflow. Analysis and performance comparisons of the new TensorCore units, available on Volta hardware, will be included.cal cuDNN API

Nanopore sequencing is a breakthrough technology that marries cutting edge semiconductor processes together with biochemistry, achieving fast, scalable, single molecule DNA sequencing. The challenge is real-time processing of gigabytes of data per second in a compact benchtop instrument. GPUDirect, together with the cuDNN library, enables Roche to maximize the effectiveness of Tesla V100 GPUs in their next generation sequencing instrument. Attendees will learn how these pieces come together to build a streaming AI inference engine to solve a signal processing workflow. Analysis and performance comparisons of the new TensorCore units, available on Volta hardware, will be included.cal cuDNN API

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Topics:
AI in Healthcare, Genomics & Bioinformatics
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8947
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Abstract:
Efficiently utilizing one or more GPUs involves finding the right balance in three areas of CUDA programming: data movement, hardware architecture, and multi-level parallelism. CUDA Streams can be a powerful way to increase processor throughput if you can manage them properly. We'll go through some use case examples, synchronization pitfalls, and profiler cases to help identify ways to speed up your application.
Efficiently utilizing one or more GPUs involves finding the right balance in three areas of CUDA programming: data movement, hardware architecture, and multi-level parallelism. CUDA Streams can be a powerful way to increase processor throughput if you can manage them properly. We'll go through some use case examples, synchronization pitfalls, and profiler cases to help identify ways to speed up your application.  Back
 
Topics:
Performance Optimization, Tools & Libraries, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7393
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