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Most likely because the software they use uses CUDA.
by Tenoke 5y ago
Most likely because the software they use uses CUDA.
- capableweb 5y agoI know that CUDA is faster than OpenCL for many tasks, but is there something that is not possible to achieve in OpenCL but possible in CUDA?
- belval 5y ago> is there something that is not possible to achieve in OpenCL but possible in CUDA Developing fast... OpenCL is much harder to learn than CUDA. Take someone who did some programming classes, explain how CUDA works and they'll probably get somewhere. Do the same thing with OpenCL and they'll probably quit.
- immibis 5y agoWhat makes it harder?
- Cthulhu_ 5y agoPossibly, but that's not really the point, the article is part marketing push from nvidia for their HPC department.
- capableweb 5y ago> but that's not really the point That's what I thought as well, so the title on the website ("NVIDIA GPUs Enable Simulation of a Living Cell") is not really truthful then.
- Symmetry 5y agoMy understanding is that CUDA has a lot of optimized libraries for common tasks, think BLAS, that don't currently exist in OpenCL/Vulkan Compute.
- TomVDB 5y agoI’m subscribed to some CUDA email list with weekly updates. One thing that strikes me is how it evolves with new features. Not just higher level libraries, but also more fundamental, low level stuff, such as virtual memory, standard memory models, c++ libraries, new compilers, communication with other GPUs, launching dependent kernels, etc. At their core, OpenCL and CUDA both enable running parallel computing algorithms on a GPU, but CUDA strikes me as much more advanced in terms of peripheral features. Every few years, I think about writing a CUDA program (it never actually happens), and investigate how to do things, and it’s interesting how the old ways of doing things has been superseded by better ways. None of this should be surprising. As I understand it, OpenCL has been put on life support by the industry in general for years now.
- 4gotunameagain 5y agoIf you ever need to reap the benefits of CUDA & GPU computations without getting into the details, check out JAX by our corporate overlords™ (https://github.com/google/jax https://github.com/google/jax), it has a NumPy like syntax and super fast to get started
- p1esk 5y agoWhy would you suggest JAX? CuPy seems like an obvious choice here (simpler and a lot more mature). Jax is only needed if you want automatic differentiation.