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GTC ON-DEMAND

HPC and AI
Presentation
Media
Speakers:
Hatem Ltaief, Stan Tomov
- University of Tennessee
Abstract:
Learn how to develop faster, cheaper and better linear algebra software for GPUs through a hybridization methodology that is built on (1) Representing linear algebra algorithms as directed acyclic graphs where nodes correspond to tasks and edges to dependencies among them, and (2) Scheduling the execution of the tasks over hybrid architectures of GPUs and multicore. Examples will be given using MAGMA, a new generation of linear algebra libraries that extends the sequential LAPACK-style algorithms to the highly parallel GPU and multicore heterogeneous architectures.
 
Topics:
HPC and AI, Tools & Libraries, Developer - Algorithms
Type:
Talk
Event:
GTC Silicon Valley
Year:
2010
Session ID:
S102138
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