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GTC ON-DEMAND

Algorithms & Numerical Techniques
Presentation
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High-Performance Batched Computations for GPUs: Approaches and Applications
Abstract:
Learn techniques for efficient batched computations on GPUs, where small and independent computations must be grouped and executed together to obtain high performance. These problems occur very frequently in scientific applications like machine learning, data mining, dense and sparse solvers, high-order FEM, astrophysics, and more. We will consider the development of batched computations for these applications, stressing innovative GPU techniques and algorithms for uniform, as well as variable-size batches, tensor contractions, batched BLAS, and more. Batched computations can fill up the GPU with work, remove scheduling overheads and costly CPU-GPU communications to accelerate the computation often by an order of magnitude compared to non-batched approaches.
 
Topics:
Algorithms & Numerical Techniques, Tools & Libraries, Performance Optimization
Type:
Talk
Event:
GTC Silicon Valley
Year:
2016
Session ID:
S6509
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