The neural-cost v0.2.0 GPU benchmark moves from CPU roofline analysis to Apple Silicon's MPS GPU backend — measuring PyTorch and JAX across five architectures, four batch sizes, and both eager and compiled execution modes.
An empirical investigation comparing PyTorch 2.14, JAX 0.11, and TensorFlow across five model architectures and four batch sizes, measuring compiler speedups, kernel overheads, and hardware limits on Apple Silicon.