4 ms·
That or they could just open their GPU cores to direct programming instead of locking it behind some API.
by bobajeff 4y ago
That or they could just open their GPU cores to direct programming instead of locking it behind some API.
- amluto 4y agoThis depends on the degree to which the underlying hardware remains compatible across generations. nVidia can sell monster GPU systems today to run 5-year-old CUDA code faster without any recompilation or other mandatory engineering work. I don’t know whether this is possible with direct hardware access.
- PaulHoule 4y agoIntel's OneAPI (rebranded OpenCL) can allegedly do this. It also claims to do this across radically different architectures like FPGA and all I can say to that is "I find that very hard to believe"
- buildbot 4y agoYeah it is in practice not really true. Maybe after hacking the code you can watch it compile for _days_ and then perform probably worse than a GPU without extreme tuning, which removes the point anyway.
- pjmlp 4y agoRebranded SYCL, if it was rebranded OpenCL, it wouldn't even be worth a 2nd look.
- greenknight 4y agoDepends... sometimes its built specifically to kernels. One common instance is, blender's Cycles renderer. Every time there is a new NVIDIA GPU. It needs to be recompiled to support it. Sometimes that also requires a new CUDA version to be able to do it. CUDA versions over the years have deprecated different operations and what not.
- wmf 4y agoThat's a "did you just tell me to go fuck myself?" solution. It didn't work for AMD and it won't work for anyone else. Developing a CUDA-to-GPU compiler and runtime stack is an immense amount of work and customers or "the community" can't afford it. Although for completeness I'll note that Intel's GPU architecture is documented: https://01.org/linuxgraphics/documentation/hardware-specification-prms https://01.org/linuxgraphics/documentation/hardware-specific...