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Programming Languages
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Programming GPU Supercomputers Ten Years From Now
Abstract:
We'll briefly review how programming for GPU computing has progressed over the past ten years, and where it is going over the next ten years, specifically for data management and parallel compute management. CUDA languages expose all aspects of data and compute management, allowing and sometimes requiring programmers to take control of both. Libraries typically internalize all compute management, and some internalize all data management as well. Directives virtualize both data and compute management, but don't completely hide either. Future hardware and software capabilities will allow programs to enjoy automatic data movement between DDR memory and GPU device memory, and enhanced caching hardware reduces the need for explicit scratchpad memory programming. As parallel constructs are added to standard programming languages, writing parallel programs for GPU computing will become no more or less difficult than multicore programming.
 
Topics:
Programming Languages, HPC and Supercomputing
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8273
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