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GPU Computing: Past, Present and Future (47 mins, ~21 MB)
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Manage episode 205984219 series 2307601
Content provided by Iain Bethune and Iain Bethune (ibethune@exseed.ed.ac.uk). All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Iain Bethune and Iain Bethune (ibethune@exseed.ed.ac.uk) or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
The past five years have seen the use of graphical processing units for computation grow from being the interest of handful of early adopters to a mainstream technology used in the world’s largest supercomputers. The CUDA GPU programming ecosystem today provides all that a developer needs to accelerate scientific applications with GPUs. The architecture of a GPU has much to offer to the future of large-scale computing where energy-efficiency is paramount. NVIDIA is the lead contractor for the DARPA-funded Echelon project investigating efficient parallel computer architectures for the exascale era.
Timothy Lanfear is a Solution Architect in NVIDIA’s Professional Solutions Group, promoting the use of the NVIDIA Tesla(TM) computing solution for high-performance computing. He has twenty years’ experience in HPC, starting as a computational scientist in British Aerospace’s corporate research centre, and then moving to technical pre-sales roles with Hitachi, ClearSpeed, and most recently NVIDIA. He has a degree in Electrical Engineering and a PhD for research in the field of graph theory, both from Imperial College London.
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Timothy Lanfear is a Solution Architect in NVIDIA’s Professional Solutions Group, promoting the use of the NVIDIA Tesla(TM) computing solution for high-performance computing. He has twenty years’ experience in HPC, starting as a computational scientist in British Aerospace’s corporate research centre, and then moving to technical pre-sales roles with Hitachi, ClearSpeed, and most recently NVIDIA. He has a degree in Electrical Engineering and a PhD for research in the field of graph theory, both from Imperial College London.
19 episoade
MP3•Pagina episodului
Manage episode 205984219 series 2307601
Content provided by Iain Bethune and Iain Bethune (ibethune@exseed.ed.ac.uk). All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Iain Bethune and Iain Bethune (ibethune@exseed.ed.ac.uk) or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
The past five years have seen the use of graphical processing units for computation grow from being the interest of handful of early adopters to a mainstream technology used in the world’s largest supercomputers. The CUDA GPU programming ecosystem today provides all that a developer needs to accelerate scientific applications with GPUs. The architecture of a GPU has much to offer to the future of large-scale computing where energy-efficiency is paramount. NVIDIA is the lead contractor for the DARPA-funded Echelon project investigating efficient parallel computer architectures for the exascale era.
Timothy Lanfear is a Solution Architect in NVIDIA’s Professional Solutions Group, promoting the use of the NVIDIA Tesla(TM) computing solution for high-performance computing. He has twenty years’ experience in HPC, starting as a computational scientist in British Aerospace’s corporate research centre, and then moving to technical pre-sales roles with Hitachi, ClearSpeed, and most recently NVIDIA. He has a degree in Electrical Engineering and a PhD for research in the field of graph theory, both from Imperial College London.
…
continue reading
Timothy Lanfear is a Solution Architect in NVIDIA’s Professional Solutions Group, promoting the use of the NVIDIA Tesla(TM) computing solution for high-performance computing. He has twenty years’ experience in HPC, starting as a computational scientist in British Aerospace’s corporate research centre, and then moving to technical pre-sales roles with Hitachi, ClearSpeed, and most recently NVIDIA. He has a degree in Electrical Engineering and a PhD for research in the field of graph theory, both from Imperial College London.
19 episoade
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