4 ms·
Matrix math units are a smart use of silicon for many ML applications, true. But Von Neumann compute isn't going away. Neither are fixed function modules for s
by xipix 3y ago
Matrix math units are a smart use of silicon for many ML applications, true.
But Von Neumann compute isn't going away. Neither are fixed function modules for shading, ray tracing and massively parallel GPGPU type applications. Also not video coding.
My point was that if training could emit an efficient video codec as a network of logic gates, rather than as a dense array of neural network weights, it might just produce something practical for video playback on mobile devices and video processing at hyperscale.
- david-gpu 3y agoSince modern chips from cell phone application processors to datacenter GPUs all have significantly invested real estate to accelerate matrix operations, it only makes sense to take advantage of it, whether it is optimal for the task at hand. That is exactly the same path that led us to GPGPU, which in turn derived to using GPUs to accelerate neural nets. In every step of the way it was about repurposing existing hardware that was designed for something else and was thus suboptimal.