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GPU Computing: Past, Present and Future (47 mins, ~21 MB)
MP3•Episod hem
Manage episode 205984219 series 2307601
Innehåll tillhandahållet av Iain Bethune and Iain Bethune (ibethune@exseed.ed.ac.uk). Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Iain Bethune and Iain Bethune (ibethune@exseed.ed.ac.uk) eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.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 episoder
MP3•Episod hem
Manage episode 205984219 series 2307601
Innehåll tillhandahållet av Iain Bethune and Iain Bethune (ibethune@exseed.ed.ac.uk). Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Iain Bethune and Iain Bethune (ibethune@exseed.ed.ac.uk) eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.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 episoder
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