Python-graphblas

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6.1.4

* added section to User Guide: how to get the best performance out of
algorithms based on GraphBLAS
* cpu_features: no longer built as a separate library, but built directly
into libgraphblas.so and libgraphblas.a. Added compile-time flags to
optionally disable the use of cpu_features completely.
* Octave 7: port to Apple Silicon (thanks to Gabor Szarnyas)
* min/max monoids: real case (FP32 and FP64) no longer terminal
* GrB interface: overloaded C=A*B syntax where one matrix is full always
results in a full matrix C, which is faster and matches the Octave/
MATLAB policy.

6.1.3

* performance: task creation for GrB_mxm (saxpy method) didn't
account for any work for A(:,k)*B(k,j) when nnz(A(:,k))==0,
but this takes O(1) work to examine B(k,j). Performance
improvement of up to 10x when nnz(A)<<nnz(B).

6.1.2

* performance: revised swap_rule in GrB_mxm, which decides whether
to compute C=A*B or C=(B'*A')', and variants, resulting in up
to 3x performance gain over v6.1.1 for GrB_mxm (observed;
could be higher in other cases).

6.1.1

* minor revision to AVX2 and AVX512f selection
* cpu_features/Makefile: remove test of list_cpu_features

6.1.0

* added GxB_get options: compiler name and version
* added package: https://github.com/google/cpu_features,
Nov 30, 2021 version
* performance: faster C+=A*B when C is full, A is bitmap/full, and B is
sparse/hyper; added saxpy5 kernel. faster C+=A'*B (dot4 kernel).
* bug fix: deserialization of iso and empty matrices/vectors was broken

6.0.2

bug fix: GrB_Matrix_export; numerical values not properly exported

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