3 ms·
Many GPUs used to have a tiny, fast and very imprecise SFU - it's ok for GLES but useless for anything else.
by sklogic 11y ago
Many GPUs used to have a tiny, fast and very imprecise SFU - it's ok for GLES but useless for anything else.
- boxfire 11y agoAny problem where the data is imprecise or the model itself is very approximate. Machine learning type problems, machine vision, as the paper shows interferometry, lossy image processing. I can think of a few more data processing problems, but I think you might get the point. The use of a precision processor even in single precision when your input data is already 5%+ noise is a huge waste. This has immense application.
- sklogic 11y agoYes, makes sense... These units are accessible via (undocumented) intrinsics in some OpenCL implementations (or in GLSL), but, unfortunately, there is no portable solution. And the FP precision requirements in the OpenCL standard are way too high, even for the FP16 extension.