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The strategic case for it is that it lets them optimize the software for their hardware and vice versa - same reason they have C and Fortran compilers with a re
by fiatmoney 10y ago
The strategic case for it is that it lets them optimize the software for their hardware and vice versa - same reason they have C and Fortran compilers with a reputation for generally good number-crunching performance.
- yaur 10y agoI wonder to what degree the rise of CUDA played into this. A lot of CV tasks are better performed on the gpu and today nvidia is the goto platform for that.
- fiatmoney 10y agoYeah, they have a parallel strategy (for now) with their Xeon Phi hardware, but there's still a performance penalty vs Nvidia. A big problem is that all the software is written for CUDA and optimized for particular Nvidia cards - hence, software / hardware synergy. Wouldn't be surprised to see them acquire more deep learning algo startups as well.