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| Both sides previous revision Previous revision Next revision | Previous revision | ||
| devwiki:nvidia [2022/09/21 03:20] – [Nivdia RTX stack] ying | devwiki:nvidia [2022/09/21 09:00] (current) – [Nvidia for AI] ying | ||
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| * each thread has its thread ID, that its id determine which block of data it works on, and all threads finish the data together at the same data. | * each thread has its thread ID, that its id determine which block of data it works on, and all threads finish the data together at the same data. | ||
| * optimize how code use memory can be important to fit more thing in the fixed size memory by better arrangement and swapping thing in memory blocks. | * optimize how code use memory can be important to fit more thing in the fixed size memory by better arrangement and swapping thing in memory blocks. | ||
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| + | ====== CV-Cuda ====== | ||
| + | |||
| + | * CV cuda: computer vision with cuda. | ||
| ====== Nivdia RTX stack ====== | ====== Nivdia RTX stack ====== | ||
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| * DLSS3: deep learning super resolution, AI frame generator | * DLSS3: deep learning super resolution, AI frame generator | ||
| + | ====== Nvidia GPU architecture ====== | ||
| + | |||
| + | | core ^ turing ^ ampere ^ ada | | ||
| + | | shader | 16 | 40 | 90 | | ||
| + | | RT | 49 | 78 | 200 | | ||
| + | | tensor | 130 | 320 | 1400 | | ||
| + | | OFA | | 126 | 300 | | ||
| + | |||
| + | ====== Nvidia for AI ====== | ||
| + | |||
| + | * large language model: enable single model to do various different task with one single model, context aware output. like text related, image related. | ||
| + | * NeMo LLM service, Prompt learning framework, to promp learn with pre-trained LLM for specific task. | ||
| + | * recommed system: like in shopping, social network | ||