Learning Chip
Learning Chip
The recently proposed [NEP-47](https://numpy.org/neps/nep-0047-array-api-standard.html) attempts to unify the APIs of various tensor frameworks (NumPy, Tensorflow, PyTorch, Dask, JAX, CuPy, MXNet, etc.), via the [Python array API standard](https://data-apis.github.io/array-api/latest). It is a...
When optimizing a function with `SparseMatrixCSC` input type, the output ("minimizer") is still a sparse matrix type, but with inconsistent sparse patterns depending on the `autodiff` option: 1. With `autodiff...
https://github.com/fluiddyn/transonic can accelerate Python/Numpy code and run on accelerators
https://github.com/weld-project/weld can accelerate Python/numpy code by optimizing data movement.
The Tensor Algebra Compiler (https://github.com/tensor-compiler/taco) seems to be good at sparse/dense linear algebra and has Python frontend: http://tensor-compiler.org/docs/pycomputations/index.html
This project https://github.com/spcl/open-earth-compiler/ provides a DSL frontend for stencil/PDE programs, and rely on MLIR & LLVM to run on NVIDIA and AMD GPUs. It is not a Python frontend, but...
DaCe (https://github.com/spcl/dace) is a parallel computing framework that also support Numpy frontend, similar to JAX and Numba. It runs on CPU/GPU/FPGA. Would be interesting to add it for comparison!
`smoothed_aggregation_solver` supports complex-valued matrix (without converting to equivalent real form), as shown in [this demo](https://github.com/pyamg/pyamg-examples/blob/main/complex/demo.py), but `ruge_stuben_solver` seems to take real-valued matrix only: ```python import pyamg # v4.2.3 A =...
I was looking at the internal code of PMIS, the `maximal_independent_set_parallel` function inside `amg_core/graph.h`: https://github.com/pyamg/pyamg/blob/e9f22184813dbc39ae51bba95b4b8aaa0b805818/pyamg/amg_core/graph.h#L97-L107 However I did not find code related to parallelization / multi-threading / openmp / etc....
I am attempting to port [MFEM examples](https://mfem.org/examples/) to Gridap. They should be useful additions to Gridap's existing tutorial examples. The first step is to read [example mesh files](https://github.com/mfem/mfem/tree/master/data) defined in...