Je suis tombé recemment sur quelques confs Nvidia autour de CUDA et du GPU computing qui peuvent en intéresser certains que je sais travailler ces temps ci sur le sujet.
C’est un peu trop spécifique pour le mettre en podcast (ca touche pas forcément tout le monde) alors je vous met les liens dans ce petit post.
Advanced C for CUDA : maximizing memory throughput, kernel launch configuration, using shared memory, and improving GPU/CPU interaction.
GPU Metaprogramming using PyCUDA: Convenient, high-level interface PyCUDA binds all functionality in Nvidia CUDA to a convenient interface in the high-level scripting language Python. Metaprogramming PyCUDA allows GPU code to be generated at run-time code, which makes many advanced programming techniques easy–such as empirical optimization, constant folding, and run-time specialization.
NEXUS, A Powerful IDE for GPU Computing on Windows : NVIDIA’s new development environment for GPU Computing and graphics applications that use CUDA C, OpenCL, DirectCompute, Direct3D, or OpenGL. NEXUS introduces native GPU debugging and platform-wide performance analysis tools for both computing and graphics developers, fully integrated into Visual Studio 2008.
The Art of Performance Tuning for the CUDA Architecture : (pas de résumé)
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