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GTC ON-DEMAND

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Abstract:
We'll present methods and techniques for profiling CUDA Deep Neural Network (cuDNN) applications using the TAU Performance System. Given cuDNN applications that may take hours or days to execute, it's important to evaluate their performance and the library frameworks used to develop them. Attendees will learn approaches for measuring, analyzing, and tuning the configuration and performance of DNN applictions with TAU's techniques and tools. The DNN characteristics and features that can be exposed by TAU will help to debug faulty or subpar configurations, while informing the user of possible optimization for different GPU architectures. Results will be shown of known DNN benchmarks on a variety of GPUs.
We'll present methods and techniques for profiling CUDA Deep Neural Network (cuDNN) applications using the TAU Performance System. Given cuDNN applications that may take hours or days to execute, it's important to evaluate their performance and the library frameworks used to develop them. Attendees will learn approaches for measuring, analyzing, and tuning the configuration and performance of DNN applictions with TAU's techniques and tools. The DNN characteristics and features that can be exposed by TAU will help to debug faulty or subpar configurations, while informing the user of possible optimization for different GPU architectures. Results will be shown of known DNN benchmarks on a variety of GPUs.  Back
 
Topics:
Tools & Libraries, Artificial Intelligence and Deep Learning
Type:
Talk
Event:
GTC Silicon Valley
Year:
2017
Session ID:
S7684
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Abstract:

Application profiling allows developers to assess the opportunity for improving application performance using GPUs. Attend this session if you are interested in understanding the CUPTI, and how several popular tools (NVIDIA NSite, TAU, Vampir, PAPI, and HPCToolkit) make use of this profiling library. This will be run as a panel session with good opportunity for audience interaction.

Application profiling allows developers to assess the opportunity for improving application performance using GPUs. Attend this session if you are interested in understanding the CUPTI, and how several popular tools (NVIDIA NSite, TAU, Vampir, PAPI, and HPCToolkit) make use of this profiling library. This will be run as a panel session with good opportunity for audience interaction.

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Topics:
Tools & Libraries
Type:
Talk
Event:
GTC Silicon Valley
Year:
2013
Session ID:
S3584
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Abstract:

Discover the latest parallel performance tool technology for understanding and optimizing parallel computations on scalable heterogeneous platforms. The session will present the TAU performance system and its support of measurement and analysis of heterogeneous platforms composed of clusters of shared-memory nodes with GPUs. In particular, TAU's integration of the CUPTI 4.1+ technology will be described and demonstrated through CUDA SDK examples and the SHOC benchmarks. Attendees will be provided LiveDVDs containing the TAU toolsuite and many pre-installed parallel tool packages. It will also include the last CUDA driver, runtime library, and CUPTI.

Discover the latest parallel performance tool technology for understanding and optimizing parallel computations on scalable heterogeneous platforms. The session will present the TAU performance system and its support of measurement and analysis of heterogeneous platforms composed of clusters of shared-memory nodes with GPUs. In particular, TAU's integration of the CUPTI 4.1+ technology will be described and demonstrated through CUDA SDK examples and the SHOC benchmarks. Attendees will be provided LiveDVDs containing the TAU toolsuite and many pre-installed parallel tool packages. It will also include the last CUDA driver, runtime library, and CUPTI.

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Topics:
Tools & Libraries
Type:
Talk
Event:
GTC Silicon Valley
Year:
2012
Session ID:
S2298
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Abstract:
This poster presents a computational environment ACSON that leverages GPU technology to accelerate the solution of the EEG forward problem, which is necessary to solve the neuroimaging inverse problem. Two finite difference algorithms, ADI and VAI, to solve Poisson equation are presented. The ADI algorithm can only handle isotropic conductivities of the head tissue while VAI can hand anisotropic conductivities as well. Their performance on different GPUs are evaluated and compared with OpenMP implementation.
This poster presents a computational environment ACSON that leverages GPU technology to accelerate the solution of the EEG forward problem, which is necessary to solve the neuroimaging inverse problem. Two finite difference algorithms, ADI and VAI, to solve Poisson equation are presented. The ADI algorithm can only handle isotropic conductivities of the head tissue while VAI can hand anisotropic conductivities as well. Their performance on different GPUs are evaluated and compared with OpenMP implementation.   Back
 
Topics:
Neuroscience
Type:
Poster
Event:
GTC Silicon Valley
Year:
2012
Session ID:
P2505
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