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PRODID:-//Microsoft Corporation//Outlook MIMEDIR//EN
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DTSTART:20111114T163000Z
DTEND:20111115T010000Z
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DESCRIPTION;ENCODING=QUOTED-PRINTABLE:ABSTRACT: CUDA is a general-purpose architecture for writing highly parallel applications. It provides several key abstractions – a hierarchy of thread blocks, shared memory, and barrier synchronization – for scalable high-performance parallel computing. Scientists throughout industry and academia use CUDA to achieve dramatic speedups on production and research codes. The CUDA architecture supports many languages, programming environments, and libraries including C/C++, Fortran, OpenCL, DirectCompute, Python, Matlab, FFT, LAPACK, etc.=0A=0AIn this tutorial NVIDIA engineers will partner with academics and industrials to present CUDA and discuss its advanced use for science and engineering domains. The morning session will teach the basics of CUDA C programming, give an overview of CUDA Fortran and the CUDA libraries, and discuss the main optimization techniques. The afternoon session will cover best practices for tuning and profiling CUDA programs and will close with two real-world case studies from academia and industry.=0A=0AThe only prerequisite for this tutorial is basic knowledge of C programming. No prior experience in GPU programming is required.
SUMMARY:M07: High Performance Computing with CUDA
PRIORITY:3
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