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Julia bindings for the Enzyme automatic differentiator
Optimize Julia Functions With MLIR and XLA for High-Performance Execution on CPU, GPU, TPU and more.
Evaluating Robustness of Neural Networks with Mixed Integer Programming
Fixed-size multidimensional arrays. An Array-like type with less indirection at the cost of resizing capability.
Experimental compiler infrastructure for KernelAbstractions
A common suite of test functions for stressing the robustness of differentiation tools.
Reusable infrastructure for caching code in the Julia compiler.