Re-posted from: https://www.stochasticlifestyle.com/why-julias-gpu-accelerated-ode-solvers-are-20x-100x-faster-than-jax-and-pytorch/
You may have seen the benchmark results and thought, “how the heck are the Julia ODE solvers on GPUs orders of magnitude faster than the GPU-accelerated Python libraries, that can’t be true?” In this talk I will go into detail about the architectural differences between the Julia approaches to generating GPU-accelerated solvers vs the standard ML library approach to GPU usage. By the end of the talk you’ll have a good enough understanding of models of GPU acceleration to understand why this performance difference exists, and the many applications that can take advantage of this performance improvement.
The post Why Julia’s GPU Accelerated ODE Solvers are 20x-100x Faster than Jax and PyTorch appeared first on Stochastic Lifestyle.