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Introduction to Parallel Programming with CUDA
This course will help prepare students for developing code that can process large amounts of data in parallel on Graphics Processing Units (GPUs). It will learn on how to implement software that can solve complex problems with the leading consumer to enterprise-grade GPUs available using Nvidia CUDA. They will focus on the hardware and software capabilities, including the use of 100s to 1000s of threads and various forms of memory.
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| Rating | Not enough ratings |
|---|---|
| Length | 6 weeks |
| Effort | 4-5 weeks of study, 4-8 hours/week |
| Starts | Jun 26 (47 weeks ago) |
| Cost | $49 |
| From | Johns Hopkins University via Coursera |
| Instructor | Chancellor Thomas Pascale |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Science Software Development Machine Learning |
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| Rating | Not enough ratings |
|---|---|
| Length | 6 weeks |
| Effort | 4-5 weeks of study, 4-8 hours/week |
| Starts | Jun 26 (47 weeks ago) |
| Cost | $49 |
| From | Johns Hopkins University via Coursera |
| Instructor | Chancellor Thomas Pascale |
| Download Videos | On all desktop and mobile devices |
| Language | English |
| Subjects | Programming Data Science |
| Tags | Computer Science Data Science Software Development Machine Learning |
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